2023
Winograd, Rachel P; Coffey, Bridget; Woolfolk, Candice; Wood, Claire A; Ilavarasan, Vinith; Liss, David; Jain, Subodh; Stringfellow, Erin
To Prescribe or Not to Prescribe?: Barriers and Motivators for Progressing Along Each Stage of the Buprenorphine Training and Prescribing Path Journal Article
In: J Behav Health Serv Res, vol. 50, no. 2, pp. 165–180, 2023, ISSN: 1556-3308.
@article{pmid35060002,
title = {To Prescribe or Not to Prescribe?: Barriers and Motivators for Progressing Along Each Stage of the Buprenorphine Training and Prescribing Path},
author = {Rachel P Winograd and Bridget Coffey and Candice Woolfolk and Claire A Wood and Vinith Ilavarasan and David Liss and Subodh Jain and Erin Stringfellow},
doi = {10.1007/s11414-021-09783-z},
issn = {1556-3308},
year = {2023},
date = {2023-04-01},
journal = {J Behav Health Serv Res},
volume = {50},
number = {2},
pages = {165--180},
abstract = {This study aimed to identify the strongest barriers and motivators associated with each step toward buprenorphine prescribing (1. obtaining a waiver, 2. beginning to prescribe, and 3. prescribing to more people) among a sample of Missouri-based medical professionals (N = 130). Item weights (number of endorsements times mean rank of the item's importance) were calculated based on their responses. Across groups, lack of access to psychosocial support services, need for higher levels of care, and clinical complexity were strong barriers. Among non-prescribers (n = 57, 46.3%), administrative burden, potential of becoming an addiction clinic, and concern about misuse and diversion were most heavily weighted. Among prescribers (n = 66, 53.7%), patients' inability to afford medications was a barrier across phases. Prominent motivators among all groups were the effectiveness of buprenorphine, improvement in other health outcomes, and a personal interest in treating addiction. Only prescribers reported the presence of institutional support and mentors as significant motivators.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This study aimed to identify the strongest barriers and motivators associated with each step toward buprenorphine prescribing (1. obtaining a waiver, 2. beginning to prescribe, and 3. prescribing to more people) among a sample of Missouri-based medical professionals (N = 130). Item weights (number of endorsements times mean rank of the item's importance) were calculated based on their responses. Across groups, lack of access to psychosocial support services, need for higher levels of care, and clinical complexity were strong barriers. Among non-prescribers (n = 57, 46.3%), administrative burden, potential of becoming an addiction clinic, and concern about misuse and diversion were most heavily weighted. Among prescribers (n = 66, 53.7%), patients' inability to afford medications was a barrier across phases. Prominent motivators among all groups were the effectiveness of buprenorphine, improvement in other health outcomes, and a personal interest in treating addiction. Only prescribers reported the presence of institutional support and mentors as significant motivators.
Stringfellow, Erin J; Lim, Tse Yang; DiGennaro, Catherine; Zhang, Ziyuan; Paramasivam, Pritika; Bearnot, Benjamin; Humphreys, Keith; Jalali, Mohammad S
Long-Term Effects of Increasing Buprenorphine Treatment Seeking, Duration, and Capacity on Opioid Overdose Fatalities: A Model-Based Analysis Journal Article
In: J Addict Med, 2023, ISSN: 1935-3227.
@article{pmid36799870,
title = {Long-Term Effects of Increasing Buprenorphine Treatment Seeking, Duration, and Capacity on Opioid Overdose Fatalities: A Model-Based Analysis},
author = {Erin J Stringfellow and Tse Yang Lim and Catherine DiGennaro and Ziyuan Zhang and Pritika Paramasivam and Benjamin Bearnot and Keith Humphreys and Mohammad S Jalali},
doi = {10.1097/ADM.0000000000001153},
issn = {1935-3227},
year = {2023},
date = {2023-02-01},
journal = {J Addict Med},
abstract = {OBJECTIVES: Because buprenorphine treatment of opioid use disorder reduces opioid overdose deaths (OODs), expanding access to care is an important policy and clinical care goal. Policymakers must choose within capacity limitations whether to expand the number of people with opioid use disorder who are treated or extend duration for existing patients. This inherent tradeoff could be made less acute with expanded buprenorphine treatment capacity.
METHODS: To inform such decisions, we used a validated simulation model to project the effects of increasing buprenorphine treatment-seeking, average episode duration, and capacity (patients per provider) on OODs in the United States from 2023 to 2033, varying the start time to assess the effects of implementation delays.
RESULTS: Results show that increasing treatment duration alone could cost lives in the short term by reducing capacity for new admissions yet save more lives in the long term than accomplished by only increasing treatment seeking. Increasing provider capacity had negligible effects. The most effective 2-policy combination was increasing capacity and duration simultaneously, which would reduce OODs up to 18.6% over a decade. By 2033, the greatest reduction in OODs (≥20%) was achieved when capacity was doubled and average duration reached 2 years, but only if the policy changes started in 2023. Delaying even a year diminishes the benefits. Treatment-seeking increases were equally beneficial whether they began in 2023 or 2025 but of only marginal benefit beyond what capacity and duration achieved.
CONCLUSIONS: If policymakers only target 2 policies to reduce OODs, they should be to increase capacity and duration, enacted quickly and aggressively.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
OBJECTIVES: Because buprenorphine treatment of opioid use disorder reduces opioid overdose deaths (OODs), expanding access to care is an important policy and clinical care goal. Policymakers must choose within capacity limitations whether to expand the number of people with opioid use disorder who are treated or extend duration for existing patients. This inherent tradeoff could be made less acute with expanded buprenorphine treatment capacity.
METHODS: To inform such decisions, we used a validated simulation model to project the effects of increasing buprenorphine treatment-seeking, average episode duration, and capacity (patients per provider) on OODs in the United States from 2023 to 2033, varying the start time to assess the effects of implementation delays.
RESULTS: Results show that increasing treatment duration alone could cost lives in the short term by reducing capacity for new admissions yet save more lives in the long term than accomplished by only increasing treatment seeking. Increasing provider capacity had negligible effects. The most effective 2-policy combination was increasing capacity and duration simultaneously, which would reduce OODs up to 18.6% over a decade. By 2033, the greatest reduction in OODs (≥20%) was achieved when capacity was doubled and average duration reached 2 years, but only if the policy changes started in 2023. Delaying even a year diminishes the benefits. Treatment-seeking increases were equally beneficial whether they began in 2023 or 2025 but of only marginal benefit beyond what capacity and duration achieved.
CONCLUSIONS: If policymakers only target 2 policies to reduce OODs, they should be to increase capacity and duration, enacted quickly and aggressively.
METHODS: To inform such decisions, we used a validated simulation model to project the effects of increasing buprenorphine treatment-seeking, average episode duration, and capacity (patients per provider) on OODs in the United States from 2023 to 2033, varying the start time to assess the effects of implementation delays.
RESULTS: Results show that increasing treatment duration alone could cost lives in the short term by reducing capacity for new admissions yet save more lives in the long term than accomplished by only increasing treatment seeking. Increasing provider capacity had negligible effects. The most effective 2-policy combination was increasing capacity and duration simultaneously, which would reduce OODs up to 18.6% over a decade. By 2033, the greatest reduction in OODs (≥20%) was achieved when capacity was doubled and average duration reached 2 years, but only if the policy changes started in 2023. Delaying even a year diminishes the benefits. Treatment-seeking increases were equally beneficial whether they began in 2023 or 2025 but of only marginal benefit beyond what capacity and duration achieved.
CONCLUSIONS: If policymakers only target 2 policies to reduce OODs, they should be to increase capacity and duration, enacted quickly and aggressively.
Toumazis, Iakovos; Cao, Pianpian; de Nijs, Koen; Bastani, Mehrad; Munshi, Vidit; Hemmati, Mehdi; Haaf, Kevin Ten; Jeon, Jihyoun; Tammemägi, Martin; Gazelle, G Scott; Feuer, Eric J; Kong, Chung Yin; Meza, Rafael; de Koning, Harry J; Plevritis, Sylvia K; Han, Summer S
Risk Model-Based Lung Cancer Screening : A Cost-Effectiveness Analysis Journal Article
In: Ann Intern Med, 2023, ISSN: 1539-3704.
@article{pmid36745885,
title = {Risk Model-Based Lung Cancer Screening : A Cost-Effectiveness Analysis},
author = {Iakovos Toumazis and Pianpian Cao and Koen de Nijs and Mehrad Bastani and Vidit Munshi and Mehdi Hemmati and Kevin Ten Haaf and Jihyoun Jeon and Martin Tammem\"{a}gi and G Scott Gazelle and Eric J Feuer and Chung Yin Kong and Rafael Meza and Harry J de Koning and Sylvia K Plevritis and Summer S Han},
doi = {10.7326/M22-2216},
issn = {1539-3704},
year = {2023},
date = {2023-02-01},
journal = {Ann Intern Med},
abstract = {BACKGROUND: In their 2021 lung cancer screening recommendation update, the U.S. Preventive Services Task Force (USPSTF) evaluated strategies that select people based on their personal lung cancer risk (risk model-based strategies), highlighting the need for further research on the benefits and harms of risk model-based screening.
OBJECTIVE: To evaluate and compare the cost-effectiveness of risk model-based lung cancer screening strategies versus the USPSTF recommendation and to explore optimal risk thresholds.
DESIGN: Comparative modeling analysis.
DATA SOURCES: National Lung Screening Trial; Surveillance, Epidemiology, and End Results program; U.S. Smoking History Generator.
TARGET POPULATION: 1960 U.S. birth cohort.
TIME HORIZON: 45 years.
PERSPECTIVE: U.S. health care sector.
INTERVENTION: Annual low-dose computed tomography in risk model-based strategies that start screening at age 50 or 55 years, stop screening at age 80 years, with 6-year risk thresholds between 0.5% and 2.2% using the PLCOm2012 model.
OUTCOME MEASURES: Incremental cost-effectiveness ratio (ICER) and cost-effectiveness efficiency frontier connecting strategies with the highest health benefit at a given cost.
RESULTS OF BASE-CASE ANALYSIS: Risk model-based screening strategies were more cost-effective than the USPSTF recommendation and exclusively comprised the cost-effectiveness efficiency frontier. Among the strategies on the efficiency frontier, those with a 6-year risk threshold of 1.2% or greater were cost-effective with an ICER less than $100 000 per quality-adjusted life-year (QALY). Specifically, the strategy with a 1.2% risk threshold had an ICER of $94 659 (model range, $72 639 to $156 774), yielding more QALYs for less cost than the USPSTF recommendation, while having a similar level of screening coverage (person ever-screened 21.7% vs. USPSTF's 22.6%).
RESULTS OF SENSITIVITY ANALYSES: Risk model-based strategies were robustly more cost-effective than the 2021 USPSTF recommendation under varying modeling assumptions.
LIMITATION: Risk models were restricted to age, sex, and smoking-related risk predictors.
CONCLUSION: Risk model-based screening is more cost-effective than the USPSTF recommendation, thus warranting further consideration.
PRIMARY FUNDING SOURCE: National Cancer Institute (NCI).},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: In their 2021 lung cancer screening recommendation update, the U.S. Preventive Services Task Force (USPSTF) evaluated strategies that select people based on their personal lung cancer risk (risk model-based strategies), highlighting the need for further research on the benefits and harms of risk model-based screening.
OBJECTIVE: To evaluate and compare the cost-effectiveness of risk model-based lung cancer screening strategies versus the USPSTF recommendation and to explore optimal risk thresholds.
DESIGN: Comparative modeling analysis.
DATA SOURCES: National Lung Screening Trial; Surveillance, Epidemiology, and End Results program; U.S. Smoking History Generator.
TARGET POPULATION: 1960 U.S. birth cohort.
TIME HORIZON: 45 years.
PERSPECTIVE: U.S. health care sector.
INTERVENTION: Annual low-dose computed tomography in risk model-based strategies that start screening at age 50 or 55 years, stop screening at age 80 years, with 6-year risk thresholds between 0.5% and 2.2% using the PLCOm2012 model.
OUTCOME MEASURES: Incremental cost-effectiveness ratio (ICER) and cost-effectiveness efficiency frontier connecting strategies with the highest health benefit at a given cost.
RESULTS OF BASE-CASE ANALYSIS: Risk model-based screening strategies were more cost-effective than the USPSTF recommendation and exclusively comprised the cost-effectiveness efficiency frontier. Among the strategies on the efficiency frontier, those with a 6-year risk threshold of 1.2% or greater were cost-effective with an ICER less than $100 000 per quality-adjusted life-year (QALY). Specifically, the strategy with a 1.2% risk threshold had an ICER of $94 659 (model range, $72 639 to $156 774), yielding more QALYs for less cost than the USPSTF recommendation, while having a similar level of screening coverage (person ever-screened 21.7% vs. USPSTF's 22.6%).
RESULTS OF SENSITIVITY ANALYSES: Risk model-based strategies were robustly more cost-effective than the 2021 USPSTF recommendation under varying modeling assumptions.
LIMITATION: Risk models were restricted to age, sex, and smoking-related risk predictors.
CONCLUSION: Risk model-based screening is more cost-effective than the USPSTF recommendation, thus warranting further consideration.
PRIMARY FUNDING SOURCE: National Cancer Institute (NCI).
OBJECTIVE: To evaluate and compare the cost-effectiveness of risk model-based lung cancer screening strategies versus the USPSTF recommendation and to explore optimal risk thresholds.
DESIGN: Comparative modeling analysis.
DATA SOURCES: National Lung Screening Trial; Surveillance, Epidemiology, and End Results program; U.S. Smoking History Generator.
TARGET POPULATION: 1960 U.S. birth cohort.
TIME HORIZON: 45 years.
PERSPECTIVE: U.S. health care sector.
INTERVENTION: Annual low-dose computed tomography in risk model-based strategies that start screening at age 50 or 55 years, stop screening at age 80 years, with 6-year risk thresholds between 0.5% and 2.2% using the PLCOm2012 model.
OUTCOME MEASURES: Incremental cost-effectiveness ratio (ICER) and cost-effectiveness efficiency frontier connecting strategies with the highest health benefit at a given cost.
RESULTS OF BASE-CASE ANALYSIS: Risk model-based screening strategies were more cost-effective than the USPSTF recommendation and exclusively comprised the cost-effectiveness efficiency frontier. Among the strategies on the efficiency frontier, those with a 6-year risk threshold of 1.2% or greater were cost-effective with an ICER less than $100 000 per quality-adjusted life-year (QALY). Specifically, the strategy with a 1.2% risk threshold had an ICER of $94 659 (model range, $72 639 to $156 774), yielding more QALYs for less cost than the USPSTF recommendation, while having a similar level of screening coverage (person ever-screened 21.7% vs. USPSTF's 22.6%).
RESULTS OF SENSITIVITY ANALYSES: Risk model-based strategies were robustly more cost-effective than the 2021 USPSTF recommendation under varying modeling assumptions.
LIMITATION: Risk models were restricted to age, sex, and smoking-related risk predictors.
CONCLUSION: Risk model-based screening is more cost-effective than the USPSTF recommendation, thus warranting further consideration.
PRIMARY FUNDING SOURCE: National Cancer Institute (NCI).
de la Fuente, Rodrigo Paredes; Doolin, James W; Peters, Mary Linton
In: BMJ Case Rep, vol. 16, no. 2, 2023, ISSN: 1757-790X.
@article{pmid36746516,
title = {Partial response in non-resectable adenosquamous carcinoma of the pancreas with high tumour mutation burden treated with gemcitabine, nab-paclitaxel and pembrolizumab},
author = {Rodrigo Paredes de la Fuente and James W Doolin and Mary Linton Peters},
doi = {10.1136/bcr-2022-251936},
issn = {1757-790X},
year = {2023},
date = {2023-02-01},
journal = {BMJ Case Rep},
volume = {16},
number = {2},
abstract = {A previously healthy man in his 60s was diagnosed with a rare histological subtype of pancreatic cancer, adenosquamous carcinoma. After somatic mutation profiling, it was found that the tumour had microsatellite instability status high and a high tumour mutational burden. The patient was started on combination therapy with gemcitabine, nab-paclitaxel and pembrolizumab. Tumour size and biomarkers showed a dramatic response eventually leading to the patient being transitioned to maintenance therapy with pembrolizumab. The patient has demonstrated continued response since the start of the treatment. This is the first report in the literature showing a sustained response in this type of neoplasm that was treated with a checkpoint inhibitor, and thus adds to the evidence supporting universal somatic testing in all pancreatic cancers for a tailored approach to therapy.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A previously healthy man in his 60s was diagnosed with a rare histological subtype of pancreatic cancer, adenosquamous carcinoma. After somatic mutation profiling, it was found that the tumour had microsatellite instability status high and a high tumour mutational burden. The patient was started on combination therapy with gemcitabine, nab-paclitaxel and pembrolizumab. Tumour size and biomarkers showed a dramatic response eventually leading to the patient being transitioned to maintenance therapy with pembrolizumab. The patient has demonstrated continued response since the start of the treatment. This is the first report in the literature showing a sustained response in this type of neoplasm that was treated with a checkpoint inhibitor, and thus adds to the evidence supporting universal somatic testing in all pancreatic cancers for a tailored approach to therapy.
Castellano, Tara; Moore, Kathleen; Ting, Jie; Washington, Christina; Yildiz, Yasin; Surinach, Andy; Sonawane, Kalyani; Chhatwal, Jagpreet; Ayer, Turgay
In: Gynecol Oncol, vol. 169, pp. 113–117, 2023, ISSN: 1095-6859.
@article{pmid36549175,
title = {Cervical cancer geographical burden analyzer: An interactive, open-access tool for understanding geographical disease burden in patients with recurrent or metastatic cervical cancer},
author = {Tara Castellano and Kathleen Moore and Jie Ting and Christina Washington and Yasin Yildiz and Andy Surinach and Kalyani Sonawane and Jagpreet Chhatwal and Turgay Ayer},
doi = {10.1016/j.ygyno.2022.12.004},
issn = {1095-6859},
year = {2023},
date = {2023-02-01},
urldate = {2022-12-01},
journal = {Gynecol Oncol},
volume = {169},
pages = {113--117},
abstract = {OBJECTIVE: Cervical cancer (CC) disproportionately affects women based on socioeconomic status and racial/ethnic background. There is limited research in quantifying and visualizing whether substantial geographical disparities in the US exist with respect to CC burden, and especially with respect to recurrent or metastatic CC (r/mCC) disease burden. Identifying regions with higher r/mCC burden may help inform effective healthcare resource allocation and navigating patients to appropriate care.
METHODS: We conducted a retrospective analysis of the 2015-2020 MarketScan® Commercial and Supplemental Medicare claims data; r/mCC burden was estimated as the number of patients initiating r/mCC systemic therapy over CC-diagnosed patients for each of the 410 metropolitan statistical areas (MSAs) considered. We developed a public, web-based tool, the Cervical Cancer Geographical Disease Burden Analyzer (Cervical Cancer Geo-Analyzer, http://www.geo-analyzer.org), that allows users to visualize r/mCC burden across MSAs over multiple years.
RESULTS: There was considerable variation in r/mCC burden across MSAs, with a range of 0-83.3%. Burden increased in Boston-Cambridge-Newton, MA (r/mCC to CC ratio: 41% in 2018 to 50% in 2020), and Sacramento-Roseville-Arden-Arcade, CA (33% in 2018 to 50% in 2020). On the other hand, while r/mCC burden remained high, it decreased in Grand Rapids, MI (55% in 2018 to 31% in 2020) and San Francisco-Oakland-Hayward, CA (40% in 2018 to 26% in 2020). There were regions with sparse or no data, suggesting a need for more representative data capture.
CONCLUSION: The Cervical Geo-Analyzer is a tool to visualize areas with high need for CC interventions. It also builds the foundation for further work to understand local risk factors of disease burden, identify populations of interest, characterize health disparities of CC or r/mCC and inform targeted interventions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
OBJECTIVE: Cervical cancer (CC) disproportionately affects women based on socioeconomic status and racial/ethnic background. There is limited research in quantifying and visualizing whether substantial geographical disparities in the US exist with respect to CC burden, and especially with respect to recurrent or metastatic CC (r/mCC) disease burden. Identifying regions with higher r/mCC burden may help inform effective healthcare resource allocation and navigating patients to appropriate care.
METHODS: We conducted a retrospective analysis of the 2015-2020 MarketScan® Commercial and Supplemental Medicare claims data; r/mCC burden was estimated as the number of patients initiating r/mCC systemic therapy over CC-diagnosed patients for each of the 410 metropolitan statistical areas (MSAs) considered. We developed a public, web-based tool, the Cervical Cancer Geographical Disease Burden Analyzer (Cervical Cancer Geo-Analyzer, http://www.geo-analyzer.org), that allows users to visualize r/mCC burden across MSAs over multiple years.
RESULTS: There was considerable variation in r/mCC burden across MSAs, with a range of 0-83.3%. Burden increased in Boston-Cambridge-Newton, MA (r/mCC to CC ratio: 41% in 2018 to 50% in 2020), and Sacramento-Roseville-Arden-Arcade, CA (33% in 2018 to 50% in 2020). On the other hand, while r/mCC burden remained high, it decreased in Grand Rapids, MI (55% in 2018 to 31% in 2020) and San Francisco-Oakland-Hayward, CA (40% in 2018 to 26% in 2020). There were regions with sparse or no data, suggesting a need for more representative data capture.
CONCLUSION: The Cervical Geo-Analyzer is a tool to visualize areas with high need for CC interventions. It also builds the foundation for further work to understand local risk factors of disease burden, identify populations of interest, characterize health disparities of CC or r/mCC and inform targeted interventions.
METHODS: We conducted a retrospective analysis of the 2015-2020 MarketScan® Commercial and Supplemental Medicare claims data; r/mCC burden was estimated as the number of patients initiating r/mCC systemic therapy over CC-diagnosed patients for each of the 410 metropolitan statistical areas (MSAs) considered. We developed a public, web-based tool, the Cervical Cancer Geographical Disease Burden Analyzer (Cervical Cancer Geo-Analyzer, http://www.geo-analyzer.org), that allows users to visualize r/mCC burden across MSAs over multiple years.
RESULTS: There was considerable variation in r/mCC burden across MSAs, with a range of 0-83.3%. Burden increased in Boston-Cambridge-Newton, MA (r/mCC to CC ratio: 41% in 2018 to 50% in 2020), and Sacramento-Roseville-Arden-Arcade, CA (33% in 2018 to 50% in 2020). On the other hand, while r/mCC burden remained high, it decreased in Grand Rapids, MI (55% in 2018 to 31% in 2020) and San Francisco-Oakland-Hayward, CA (40% in 2018 to 26% in 2020). There were regions with sparse or no data, suggesting a need for more representative data capture.
CONCLUSION: The Cervical Geo-Analyzer is a tool to visualize areas with high need for CC interventions. It also builds the foundation for further work to understand local risk factors of disease burden, identify populations of interest, characterize health disparities of CC or r/mCC and inform targeted interventions.
Yoon, Byung C; Pomerantz, Stuart R; Mercaldo, Nathaniel D; Goyal, Swati; L'Italien, Eric M; Lev, Michael H; Buch, Karen A; Buchbinder, Bradley R; Chen, John W; Conklin, John; Gupta, Rajiv; Hunter, George J; Kamalian, Shahmir C; Kelly, Hillary R; Rapalino, Otto; Rincon, Sandra P; Romero, Javier M; He, Julian; Schaefer, Pamela W; Do, Synho; González, Ramon Gilberto
Incorporating algorithmic uncertainty into a clinical machine deep learning algorithm for urgent head CTs Journal Article
In: PLoS One, vol. 18, no. 3, pp. e0281900, 2023, ISSN: 1932-6203.
@article{pmid36913348,
title = {Incorporating algorithmic uncertainty into a clinical machine deep learning algorithm for urgent head CTs},
author = {Byung C Yoon and Stuart R Pomerantz and Nathaniel D Mercaldo and Swati Goyal and Eric M L'Italien and Michael H Lev and Karen A Buch and Bradley R Buchbinder and John W Chen and John Conklin and Rajiv Gupta and George J Hunter and Shahmir C Kamalian and Hillary R Kelly and Otto Rapalino and Sandra P Rincon and Javier M Romero and Julian He and Pamela W Schaefer and Synho Do and Ramon Gilberto Gonz\'{a}lez},
doi = {10.1371/journal.pone.0281900},
issn = {1932-6203},
year = {2023},
date = {2023-01-01},
journal = {PLoS One},
volume = {18},
number = {3},
pages = {e0281900},
abstract = {Machine learning (ML) algorithms to detect critical findings on head CTs may expedite patient management. Most ML algorithms for diagnostic imaging analysis utilize dichotomous classifications to determine whether a specific abnormality is present. However, imaging findings may be indeterminate, and algorithmic inferences may have substantial uncertainty. We incorporated awareness of uncertainty into an ML algorithm that detects intracranial hemorrhage or other urgent intracranial abnormalities and evaluated prospectively identified, 1000 consecutive noncontrast head CTs assigned to Emergency Department Neuroradiology for interpretation. The algorithm classified the scans into high (IC+) and low (IC-) probabilities for intracranial hemorrhage or other urgent abnormalities. All other cases were designated as No Prediction (NP) by the algorithm. The positive predictive value for IC+ cases (N = 103) was 0.91 (CI: 0.84-0.96), and the negative predictive value for IC- cases (N = 729) was 0.94 (0.91-0.96). Admission, neurosurgical intervention, and 30-day mortality rates for IC+ was 75% (63-84), 35% (24-47), and 10% (4-20), compared to 43% (40-47), 4% (3-6), and 3% (2-5) for IC-. There were 168 NP cases, of which 32% had intracranial hemorrhage or other urgent abnormalities, 31% had artifacts and postoperative changes, and 29% had no abnormalities. An ML algorithm incorporating uncertainty classified most head CTs into clinically relevant groups with high predictive values and may help accelerate the management of patients with intracranial hemorrhage or other urgent intracranial abnormalities.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Machine learning (ML) algorithms to detect critical findings on head CTs may expedite patient management. Most ML algorithms for diagnostic imaging analysis utilize dichotomous classifications to determine whether a specific abnormality is present. However, imaging findings may be indeterminate, and algorithmic inferences may have substantial uncertainty. We incorporated awareness of uncertainty into an ML algorithm that detects intracranial hemorrhage or other urgent intracranial abnormalities and evaluated prospectively identified, 1000 consecutive noncontrast head CTs assigned to Emergency Department Neuroradiology for interpretation. The algorithm classified the scans into high (IC+) and low (IC-) probabilities for intracranial hemorrhage or other urgent abnormalities. All other cases were designated as No Prediction (NP) by the algorithm. The positive predictive value for IC+ cases (N = 103) was 0.91 (CI: 0.84-0.96), and the negative predictive value for IC- cases (N = 729) was 0.94 (0.91-0.96). Admission, neurosurgical intervention, and 30-day mortality rates for IC+ was 75% (63-84), 35% (24-47), and 10% (4-20), compared to 43% (40-47), 4% (3-6), and 3% (2-5) for IC-. There were 168 NP cases, of which 32% had intracranial hemorrhage or other urgent abnormalities, 31% had artifacts and postoperative changes, and 29% had no abnormalities. An ML algorithm incorporating uncertainty classified most head CTs into clinically relevant groups with high predictive values and may help accelerate the management of patients with intracranial hemorrhage or other urgent intracranial abnormalities.
Dong, Huiru; Stringfellow, Erin J; Russell, W Alton; Jalali, Mohammad S
Racial and Ethnic Disparities in Buprenorphine Treatment Duration in the US Journal Article
In: JAMA Psychiatry, vol. 80, iss. 1, pp. 93-95, 2023, ISSN: 2168-6238.
@article{pmid36350592,
title = {Racial and Ethnic Disparities in Buprenorphine Treatment Duration in the US},
author = {Huiru Dong and Erin J Stringfellow and W Alton Russell and Mohammad S Jalali},
doi = {10.1001/jamapsychiatry.2022.3673},
issn = {2168-6238},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
journal = {JAMA Psychiatry},
volume = {80},
issue = {1},
pages = {93-95},
abstract = {Buprenorphine is used to treat opioid use disorder (OUD) and reduce overdose risk.1 Duration of buprenorphine treatment is a measure of quality of care; longer retention is associated with superior clinical outcomes. Racial and ethnic minority patients are more likely to discontinue buprenorphine treatment earlier than White patients. To our knowledge, no nationally representative studies have examined buprenorphine treatment duration over time across racial and ethnic groups. This information is needed to close the racial and ethnic gap in treatment retention for OUD.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Buprenorphine is used to treat opioid use disorder (OUD) and reduce overdose risk.1 Duration of buprenorphine treatment is a measure of quality of care; longer retention is associated with superior clinical outcomes. Racial and ethnic minority patients are more likely to discontinue buprenorphine treatment earlier than White patients. To our knowledge, no nationally representative studies have examined buprenorphine treatment duration over time across racial and ethnic groups. This information is needed to close the racial and ethnic gap in treatment retention for OUD.
Collins, Reagan A; DiGennaro, Catherine; Beninato, Toni; Gartland, Rajshri M; Chaves, Natalia; Broekhuis, Jordan M; Reddy, Lekha; Lee, Jenna; Deimiller, Angelina; Alterio, Maeve M; Campbell, Michael J; Lee, Yeon Joo; Khilnani, Tyler K; Stewart, Latoya A; O'Brien, Mollie A; Alvarado, Miguel Valdivia Y; Zheng, Feibi; McAneny, David; Liou, Rachel; McManus, Catherine; Dream, Sophie Y; Wang, Tracy S; Yen, Tina W; Alhefdhi, Amal; Finnerty, Brendan M; Fahey, Thomas J; Graves, Claire E; Laird, Amanda M; Nehs, Matthew A; Drake, Frederick Thurston; Lee, James A; McHenry, Christopher R; James, Benjamin C; Pasieka, Janice L; Kuo, Jennifer H; Lubitz, Carrie Cunningham
Limited disease progression in endocrine surgery patients with treatment delays due to COVID-19 Journal Article
In: Surgery, vol. 173, no. 1, pp. 93–100, 2023, ISSN: 1532-7361.
@article{pmid36210185,
title = {Limited disease progression in endocrine surgery patients with treatment delays due to COVID-19},
author = {Reagan A Collins and Catherine DiGennaro and Toni Beninato and Rajshri M Gartland and Natalia Chaves and Jordan M Broekhuis and Lekha Reddy and Jenna Lee and Angelina Deimiller and Maeve M Alterio and Michael J Campbell and Yeon Joo Lee and Tyler K Khilnani and Latoya A Stewart and Mollie A O'Brien and Miguel Valdivia Y Alvarado and Feibi Zheng and David McAneny and Rachel Liou and Catherine McManus and Sophie Y Dream and Tracy S Wang and Tina W Yen and Amal Alhefdhi and Brendan M Finnerty and Thomas J Fahey and Claire E Graves and Amanda M Laird and Matthew A Nehs and Frederick Thurston Drake and James A Lee and Christopher R McHenry and Benjamin C James and Janice L Pasieka and Jennifer H Kuo and Carrie Cunningham Lubitz},
doi = {10.1016/j.surg.2022.06.043},
issn = {1532-7361},
year = {2023},
date = {2023-01-01},
journal = {Surgery},
volume = {173},
number = {1},
pages = {93--100},
abstract = {BACKGROUND: The COVID-19 pandemic profoundly impacted the delivery of care and timing of elective surgical procedures. Most endocrine-related operations were considered elective and safe to postpone, providing a unique opportunity to assess clinical outcomes under protracted treatment plans.
METHODS: American Association of Endocrine Surgeon members were surveyed for participation. A Research Electronic Data Capture survey was developed and distributed to 27 institutions to assess the impact of COVID-19-related delays. The information collected included patient demographics, primary diagnosis, resumption of care, and assessment of disease progression by the surgeon.
RESULTS: Twelve out of 27 institutions completed the survey (44.4%). Of 850 patients, 74.8% (636) were female; median age was 56 (interquartile range, 44-66) years. Forty percent (34) of patients had not been seen since their original surgical appointment was delayed; 86.2% (733) of patients had a delay in care with women more likely to have a delay (87.6% vs 82.2% of men, χ = 3.84, P = .05). Median duration of delay was 70 (interquartile range, 42-118) days. Among patients with a delay in care, primary disease site included thyroid (54.2%), parathyroid (37.2%), adrenal (6.5%), and pancreatic/gastrointestinal neuroendocrine tumors (1.3%). In addition, 4.0% (26) of patients experienced disease progression and 4.1% (24) had a change from the initial operative plan. The duration of delay was not associated with disease progression (P = .96) or a change in operative plan (P = .66).
CONCLUSION: Although some patients experienced disease progression during COVID-19 delays to endocrine disease-related care, most patients with follow-up did not. Our analysis indicated that temporary delay may be an acceptable course of action in extreme circumstances for most endocrine-related surgical disease.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: The COVID-19 pandemic profoundly impacted the delivery of care and timing of elective surgical procedures. Most endocrine-related operations were considered elective and safe to postpone, providing a unique opportunity to assess clinical outcomes under protracted treatment plans.
METHODS: American Association of Endocrine Surgeon members were surveyed for participation. A Research Electronic Data Capture survey was developed and distributed to 27 institutions to assess the impact of COVID-19-related delays. The information collected included patient demographics, primary diagnosis, resumption of care, and assessment of disease progression by the surgeon.
RESULTS: Twelve out of 27 institutions completed the survey (44.4%). Of 850 patients, 74.8% (636) were female; median age was 56 (interquartile range, 44-66) years. Forty percent (34) of patients had not been seen since their original surgical appointment was delayed; 86.2% (733) of patients had a delay in care with women more likely to have a delay (87.6% vs 82.2% of men, χ = 3.84, P = .05). Median duration of delay was 70 (interquartile range, 42-118) days. Among patients with a delay in care, primary disease site included thyroid (54.2%), parathyroid (37.2%), adrenal (6.5%), and pancreatic/gastrointestinal neuroendocrine tumors (1.3%). In addition, 4.0% (26) of patients experienced disease progression and 4.1% (24) had a change from the initial operative plan. The duration of delay was not associated with disease progression (P = .96) or a change in operative plan (P = .66).
CONCLUSION: Although some patients experienced disease progression during COVID-19 delays to endocrine disease-related care, most patients with follow-up did not. Our analysis indicated that temporary delay may be an acceptable course of action in extreme circumstances for most endocrine-related surgical disease.
METHODS: American Association of Endocrine Surgeon members were surveyed for participation. A Research Electronic Data Capture survey was developed and distributed to 27 institutions to assess the impact of COVID-19-related delays. The information collected included patient demographics, primary diagnosis, resumption of care, and assessment of disease progression by the surgeon.
RESULTS: Twelve out of 27 institutions completed the survey (44.4%). Of 850 patients, 74.8% (636) were female; median age was 56 (interquartile range, 44-66) years. Forty percent (34) of patients had not been seen since their original surgical appointment was delayed; 86.2% (733) of patients had a delay in care with women more likely to have a delay (87.6% vs 82.2% of men, χ = 3.84, P = .05). Median duration of delay was 70 (interquartile range, 42-118) days. Among patients with a delay in care, primary disease site included thyroid (54.2%), parathyroid (37.2%), adrenal (6.5%), and pancreatic/gastrointestinal neuroendocrine tumors (1.3%). In addition, 4.0% (26) of patients experienced disease progression and 4.1% (24) had a change from the initial operative plan. The duration of delay was not associated with disease progression (P = .96) or a change in operative plan (P = .66).
CONCLUSION: Although some patients experienced disease progression during COVID-19 delays to endocrine disease-related care, most patients with follow-up did not. Our analysis indicated that temporary delay may be an acceptable course of action in extreme circumstances for most endocrine-related surgical disease.
McCandlish, John Austin; Ayer, Turgay; Chhatwal, Jagpreet
Cost-Effectiveness and Value-of-Information Analysis Using Machine Learning-Based Metamodeling: A Case of Hepatitis C Treatment Journal Article
In: Med Decis Making, vol. 43, no. 1, pp. 68–77, 2023, ISSN: 1552-681X.
@article{pmid36113098,
title = {Cost-Effectiveness and Value-of-Information Analysis Using Machine Learning-Based Metamodeling: A Case of Hepatitis C Treatment},
author = {John Austin McCandlish and Turgay Ayer and Jagpreet Chhatwal},
doi = {10.1177/0272989X221125418},
issn = {1552-681X},
year = {2023},
date = {2023-01-01},
journal = {Med Decis Making},
volume = {43},
number = {1},
pages = {68--77},
abstract = {BACKGROUND: Metamodels can address some of the limitations of complex simulation models by formulating a mathematical relationship between input parameters and simulation model outcomes. Our objective was to develop and compare the performance of a machine learning (ML)-based metamodel against a conventional metamodeling approach in replicating the findings of a complex simulation model.
METHODS: We constructed 3 ML-based metamodels using random forest, support vector regression, and artificial neural networks and a linear regression-based metamodel from a previously validated microsimulation model of the natural history hepatitis C virus (HCV) consisting of 40 input parameters. Outcomes of interest included societal costs and quality-adjusted life-years (QALYs), the incremental cost-effectiveness (ICER) of HCV treatment versus no treatment, cost-effectiveness analysis curve (CEAC), and expected value of perfect information (EVPI). We evaluated metamodel performance using root mean squared error (RMSE) and Pearson's on the normalized data.
RESULTS: The values for the linear regression metamodel for QALYs without treatment, QALYs with treatment, societal cost without treatment, societal cost with treatment, and ICER were 0.92, 0.98, 0.85, 0.92, and 0.60, respectively. The corresponding values for our ML-based metamodels were 0.96, 0.97, 0.90, 0.95, and 0.49 for support vector regression; 0.99, 0.83, 0.99, 0.99, and 0.82 for artificial neural network; and 0.99, 0.99, 0.99, 0.99, and 0.98 for random forest. Similar trends were observed for RMSE. The CEAC and EVPI curves produced by the random forest metamodel matched the results of the simulation output more closely than the linear regression metamodel.
CONCLUSIONS: ML-based metamodels generally outperformed traditional linear regression metamodels at replicating results from complex simulation models, with random forest metamodels performing best.
HIGHLIGHTS: Decision-analytic models are frequently used by policy makers and other stakeholders to assess the impact of new medical technologies and interventions. However, complex models can impose limitations on conducting probabilistic sensitivity analysis and value-of-information analysis, and may not be suitable for developing online decision-support tools.Metamodels, which accurately formulate a mathematical relationship between input parameters and model outcomes, can replicate complex simulation models and address the above limitation.The machine learning-based random forest model can outperform linear regression in replicating the findings of a complex simulation model. Such a metamodel can be used for conducting cost-effectiveness and value-of-information analyses or developing online decision support tools.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: Metamodels can address some of the limitations of complex simulation models by formulating a mathematical relationship between input parameters and simulation model outcomes. Our objective was to develop and compare the performance of a machine learning (ML)-based metamodel against a conventional metamodeling approach in replicating the findings of a complex simulation model.
METHODS: We constructed 3 ML-based metamodels using random forest, support vector regression, and artificial neural networks and a linear regression-based metamodel from a previously validated microsimulation model of the natural history hepatitis C virus (HCV) consisting of 40 input parameters. Outcomes of interest included societal costs and quality-adjusted life-years (QALYs), the incremental cost-effectiveness (ICER) of HCV treatment versus no treatment, cost-effectiveness analysis curve (CEAC), and expected value of perfect information (EVPI). We evaluated metamodel performance using root mean squared error (RMSE) and Pearson's on the normalized data.
RESULTS: The values for the linear regression metamodel for QALYs without treatment, QALYs with treatment, societal cost without treatment, societal cost with treatment, and ICER were 0.92, 0.98, 0.85, 0.92, and 0.60, respectively. The corresponding values for our ML-based metamodels were 0.96, 0.97, 0.90, 0.95, and 0.49 for support vector regression; 0.99, 0.83, 0.99, 0.99, and 0.82 for artificial neural network; and 0.99, 0.99, 0.99, 0.99, and 0.98 for random forest. Similar trends were observed for RMSE. The CEAC and EVPI curves produced by the random forest metamodel matched the results of the simulation output more closely than the linear regression metamodel.
CONCLUSIONS: ML-based metamodels generally outperformed traditional linear regression metamodels at replicating results from complex simulation models, with random forest metamodels performing best.
HIGHLIGHTS: Decision-analytic models are frequently used by policy makers and other stakeholders to assess the impact of new medical technologies and interventions. However, complex models can impose limitations on conducting probabilistic sensitivity analysis and value-of-information analysis, and may not be suitable for developing online decision-support tools.Metamodels, which accurately formulate a mathematical relationship between input parameters and model outcomes, can replicate complex simulation models and address the above limitation.The machine learning-based random forest model can outperform linear regression in replicating the findings of a complex simulation model. Such a metamodel can be used for conducting cost-effectiveness and value-of-information analyses or developing online decision support tools.
METHODS: We constructed 3 ML-based metamodels using random forest, support vector regression, and artificial neural networks and a linear regression-based metamodel from a previously validated microsimulation model of the natural history hepatitis C virus (HCV) consisting of 40 input parameters. Outcomes of interest included societal costs and quality-adjusted life-years (QALYs), the incremental cost-effectiveness (ICER) of HCV treatment versus no treatment, cost-effectiveness analysis curve (CEAC), and expected value of perfect information (EVPI). We evaluated metamodel performance using root mean squared error (RMSE) and Pearson's on the normalized data.
RESULTS: The values for the linear regression metamodel for QALYs without treatment, QALYs with treatment, societal cost without treatment, societal cost with treatment, and ICER were 0.92, 0.98, 0.85, 0.92, and 0.60, respectively. The corresponding values for our ML-based metamodels were 0.96, 0.97, 0.90, 0.95, and 0.49 for support vector regression; 0.99, 0.83, 0.99, 0.99, and 0.82 for artificial neural network; and 0.99, 0.99, 0.99, 0.99, and 0.98 for random forest. Similar trends were observed for RMSE. The CEAC and EVPI curves produced by the random forest metamodel matched the results of the simulation output more closely than the linear regression metamodel.
CONCLUSIONS: ML-based metamodels generally outperformed traditional linear regression metamodels at replicating results from complex simulation models, with random forest metamodels performing best.
HIGHLIGHTS: Decision-analytic models are frequently used by policy makers and other stakeholders to assess the impact of new medical technologies and interventions. However, complex models can impose limitations on conducting probabilistic sensitivity analysis and value-of-information analysis, and may not be suitable for developing online decision-support tools.Metamodels, which accurately formulate a mathematical relationship between input parameters and model outcomes, can replicate complex simulation models and address the above limitation.The machine learning-based random forest model can outperform linear regression in replicating the findings of a complex simulation model. Such a metamodel can be used for conducting cost-effectiveness and value-of-information analyses or developing online decision support tools.
2022
Haslwanter, Veronika; Rochau, Ursula; Siebert, Uwe; Schönherr, Hans-Robert; Oberaigner, Willi
A population-based cohort of adult patients with diabetes mellitus in a Western District of Austria: The Diabetes Landeck cohort Journal Article
In: Endocrinol Diabetes Metab, pp. e395, 2022, ISSN: 2398-9238.
@article{pmid36527244,
title = {A population-based cohort of adult patients with diabetes mellitus in a Western District of Austria: The Diabetes Landeck cohort},
author = {Veronika Haslwanter and Ursula Rochau and Uwe Siebert and Hans-Robert Sch\"{o}nherr and Willi Oberaigner},
doi = {10.1002/edm2.395},
issn = {2398-9238},
year = {2022},
date = {2022-12-01},
journal = {Endocrinol Diabetes Metab},
pages = {e395},
abstract = {INTRODUCTION: Diabetes mellitus (DM) has become an important and exacerbating health epidemic, with severe consequences for both patients and health systems. The National Diabetes Strategy of Austria addresses the lack of high-quality data on DM in Austria and the need for developing a national data network. The aims of our study are to establish a cohort including all adult diabetes patients in a district in western Austria, describe the demographic and clinical characteristics of this cohort, and provide an estimation of diabetes prevalence.
METHODS: We recruited a population-based cohort of adult patients with a diagnosis of DM in cooperation with a network of all caregivers. Data collection was based on a case report form, including patient characteristics, clinical parameters and long-term complications.
RESULTS: In total, 1845 patients with DM were recruited and analysed. We observed an overall prevalence of 5.3% [95% CI: 5.0%-5.5%]. For the subsequent main analysis, we included 1755 patients with DM after excluding 90 patients with gestational DM. There were significant differences between genders in the distribution of specific clinical parameters, patient characteristics, and the long-term complications diabetic foot, amputation and cardiovascular disease.
CONCLUSION: To the best of our knowledge, we established the first diabetes cohort study in Austria. Prevalence and the proportion of specific long-term complications were lower when compared to the international context. We assume that the Diabetes Landeck Cohort has reached a high degree of completeness; however, we were not able to identify independent data sources for a valid check of completeness.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
INTRODUCTION: Diabetes mellitus (DM) has become an important and exacerbating health epidemic, with severe consequences for both patients and health systems. The National Diabetes Strategy of Austria addresses the lack of high-quality data on DM in Austria and the need for developing a national data network. The aims of our study are to establish a cohort including all adult diabetes patients in a district in western Austria, describe the demographic and clinical characteristics of this cohort, and provide an estimation of diabetes prevalence.
METHODS: We recruited a population-based cohort of adult patients with a diagnosis of DM in cooperation with a network of all caregivers. Data collection was based on a case report form, including patient characteristics, clinical parameters and long-term complications.
RESULTS: In total, 1845 patients with DM were recruited and analysed. We observed an overall prevalence of 5.3% [95% CI: 5.0%-5.5%]. For the subsequent main analysis, we included 1755 patients with DM after excluding 90 patients with gestational DM. There were significant differences between genders in the distribution of specific clinical parameters, patient characteristics, and the long-term complications diabetic foot, amputation and cardiovascular disease.
CONCLUSION: To the best of our knowledge, we established the first diabetes cohort study in Austria. Prevalence and the proportion of specific long-term complications were lower when compared to the international context. We assume that the Diabetes Landeck Cohort has reached a high degree of completeness; however, we were not able to identify independent data sources for a valid check of completeness.
METHODS: We recruited a population-based cohort of adult patients with a diagnosis of DM in cooperation with a network of all caregivers. Data collection was based on a case report form, including patient characteristics, clinical parameters and long-term complications.
RESULTS: In total, 1845 patients with DM were recruited and analysed. We observed an overall prevalence of 5.3% [95% CI: 5.0%-5.5%]. For the subsequent main analysis, we included 1755 patients with DM after excluding 90 patients with gestational DM. There were significant differences between genders in the distribution of specific clinical parameters, patient characteristics, and the long-term complications diabetic foot, amputation and cardiovascular disease.
CONCLUSION: To the best of our knowledge, we established the first diabetes cohort study in Austria. Prevalence and the proportion of specific long-term complications were lower when compared to the international context. We assume that the Diabetes Landeck Cohort has reached a high degree of completeness; however, we were not able to identify independent data sources for a valid check of completeness.
Efficace, Fabio; Koinig, Karin; Cottone, Francesco; Bowen, David; Mittelman, Moshe; Sommer, Kathrin; Langemeijer, Saskia; Culligan, Dominic; Filanovsky, Kalman; Storck, Michael; Smith, Alexandra; van Marrewijk, Corine; Dugas, Martin; Stojkov, Igor; Siebert, Uwe; de Witte, Theo; Stauder, Reinhard
In: Cancer Med, 2022, ISSN: 2045-7634.
@article{pmid36533415,
title = {Raising the standards of patient-centered outcomes research in myelodysplastic syndromes: Clinical utility and validation of the subscales of the QUALMS from the MDS-RIGHT project},
author = {Fabio Efficace and Karin Koinig and Francesco Cottone and David Bowen and Moshe Mittelman and Kathrin Sommer and Saskia Langemeijer and Dominic Culligan and Kalman Filanovsky and Michael Storck and Alexandra Smith and Corine van Marrewijk and Martin Dugas and Igor Stojkov and Uwe Siebert and Theo de Witte and Reinhard Stauder},
doi = {10.1002/cam4.5487},
issn = {2045-7634},
year = {2022},
date = {2022-12-01},
journal = {Cancer Med},
abstract = {BACKGROUND: Clinical decision-making for patients with myelodysplastic syndromes (MDS) is challenging, and both disease and treatment effects heavily impact health-related quality of life (HRQoL) of these patients. Therefore, disease-specific HRQoL measures can be critical to harness the patient voice in MDS research.
METHODS: We report a prospective international validation study of the Quality of Life in Myelodysplasia Scale (QUALMS) with a main focus on providing information on the psychometric characteristics of its three subscales: physical burden (QUALMS-P), emotional burden (QUALMS-E), and benefit finding (QUALMS-BF). The analysis is based on patients enrolled from three European countries and Israel, participating to the MDS-RIGHT Project. The scale structure and psychometric properties of the QUALMS were assessed.
RESULTS: Overall, 270 patients with a median age of 74 years were analyzed and the majority of them (60.3%) had a low MDS-Comorbidity Index score. Results of the confirmatory factor analysis supported the underlying scale structure of the QUALMS, which, in addition to a total score, includes three subscales: QUALMS-P, QUALMS-E, and the QUALMS-BF. The QUALMS-P exhibited the highest Cronbach's alpha coefficients. Discriminant validity analysis indicated good results with the QUALMS-P and QUALMS-E distinguishing between patients with different performance status, comorbidity, anemia, and transfusion dependency status. No floor and ceiling effects were observed. Responsiveness to change analysis supported the validity of the measure. Patients with a hemoglobin (Hb) level of <11 g/dL at study entry, who subsequently showed an improvement in their Hb levels, also reported a mean score change of 9 and 8 points (scales ranging between 0 and 100) in the expected direction of the QUALMS-E and QUALMS-P, respectively.
CONCLUSIONS: Our study provides additional validation data on the QUALMS from the international MDS-RIGHT Project. The use of this disease-specific HRQoL measure may contribute to raise quality standards of patient-centered outcomes research in MDS.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: Clinical decision-making for patients with myelodysplastic syndromes (MDS) is challenging, and both disease and treatment effects heavily impact health-related quality of life (HRQoL) of these patients. Therefore, disease-specific HRQoL measures can be critical to harness the patient voice in MDS research.
METHODS: We report a prospective international validation study of the Quality of Life in Myelodysplasia Scale (QUALMS) with a main focus on providing information on the psychometric characteristics of its three subscales: physical burden (QUALMS-P), emotional burden (QUALMS-E), and benefit finding (QUALMS-BF). The analysis is based on patients enrolled from three European countries and Israel, participating to the MDS-RIGHT Project. The scale structure and psychometric properties of the QUALMS were assessed.
RESULTS: Overall, 270 patients with a median age of 74 years were analyzed and the majority of them (60.3%) had a low MDS-Comorbidity Index score. Results of the confirmatory factor analysis supported the underlying scale structure of the QUALMS, which, in addition to a total score, includes three subscales: QUALMS-P, QUALMS-E, and the QUALMS-BF. The QUALMS-P exhibited the highest Cronbach's alpha coefficients. Discriminant validity analysis indicated good results with the QUALMS-P and QUALMS-E distinguishing between patients with different performance status, comorbidity, anemia, and transfusion dependency status. No floor and ceiling effects were observed. Responsiveness to change analysis supported the validity of the measure. Patients with a hemoglobin (Hb) level of <11 g/dL at study entry, who subsequently showed an improvement in their Hb levels, also reported a mean score change of 9 and 8 points (scales ranging between 0 and 100) in the expected direction of the QUALMS-E and QUALMS-P, respectively.
CONCLUSIONS: Our study provides additional validation data on the QUALMS from the international MDS-RIGHT Project. The use of this disease-specific HRQoL measure may contribute to raise quality standards of patient-centered outcomes research in MDS.
METHODS: We report a prospective international validation study of the Quality of Life in Myelodysplasia Scale (QUALMS) with a main focus on providing information on the psychometric characteristics of its three subscales: physical burden (QUALMS-P), emotional burden (QUALMS-E), and benefit finding (QUALMS-BF). The analysis is based on patients enrolled from three European countries and Israel, participating to the MDS-RIGHT Project. The scale structure and psychometric properties of the QUALMS were assessed.
RESULTS: Overall, 270 patients with a median age of 74 years were analyzed and the majority of them (60.3%) had a low MDS-Comorbidity Index score. Results of the confirmatory factor analysis supported the underlying scale structure of the QUALMS, which, in addition to a total score, includes three subscales: QUALMS-P, QUALMS-E, and the QUALMS-BF. The QUALMS-P exhibited the highest Cronbach's alpha coefficients. Discriminant validity analysis indicated good results with the QUALMS-P and QUALMS-E distinguishing between patients with different performance status, comorbidity, anemia, and transfusion dependency status. No floor and ceiling effects were observed. Responsiveness to change analysis supported the validity of the measure. Patients with a hemoglobin (Hb) level of <11 g/dL at study entry, who subsequently showed an improvement in their Hb levels, also reported a mean score change of 9 and 8 points (scales ranging between 0 and 100) in the expected direction of the QUALMS-E and QUALMS-P, respectively.
CONCLUSIONS: Our study provides additional validation data on the QUALMS from the international MDS-RIGHT Project. The use of this disease-specific HRQoL measure may contribute to raise quality standards of patient-centered outcomes research in MDS.
Sonawane, Kalyani; Castellano, Tara; Washington, Christina; Ting, Jie; Surinach, Andy; Kirshner, Carol; Chhatwal, Jagpreet; Ayer, Turgay; Moore, Kathleen
In: Gynecol Oncol Rep, vol. 44, no. Suppl 1, pp. 101101, 2022, ISSN: 2352-5789.
@article{pmid36506039,
title = {Factors associated with receipt of second-line recurrent or metastatic cervical cancer treatment in the United States: A retrospective administrative claims analysis},
author = {Kalyani Sonawane and Tara Castellano and Christina Washington and Jie Ting and Andy Surinach and Carol Kirshner and Jagpreet Chhatwal and Turgay Ayer and Kathleen Moore},
doi = {10.1016/j.gore.2022.101101},
issn = {2352-5789},
year = {2022},
date = {2022-12-01},
journal = {Gynecol Oncol Rep},
volume = {44},
number = {Suppl 1},
pages = {101101},
abstract = {PURPOSE: Contemporary, real-world data on eligible patients receiving treatment following progression on first-line (1L) recurrent or metastatic cervical cancer (r/mCC) therapy are needed to inform treatment algorithms and identify potential gaps in the r/mCC care continuum.
METHODS: This study estimated the prevalence and predictors of second-line (2L) r/mCC therapy among 1L-treated patients using the 2015-2020 IBM MarketScan® commercial claims database. Women ≥ 18 years diagnosed with cervical cancer and treated with first-line systemic therapies were identified and followed for 12 months from their 1L therapy end date. Women with claims for a new therapy after 60 days but no later than 365 days from the end of 1L treatment were identified as those who progressed and received 2L therapy for r/mCC. Descriptive statistics examined baseline cohort characteristics and multivariable logistic regression model examined the factors associated with receiving 2L treatment.
RESULTS: We identified 384 1L-treated patients with r/mCC with ≥ 12 months of follow-up post-1L treatment. During follow-up, over half (51.0 %) of the 1L-treated r/mCC patients received 2L treatment. Patients from the South and Midwest had a lower likelihood of receiving 2L treatment compared with those living in the Northeast (adjusted odds ratio [aOR] = 0.43; 0.23-0.84) and (aOR = 0.52; 0.28-0.95, respectively). Patients not treated with bevacizumab in 1L were also less likely to receive 2L therapy (aOR = 0.65; 0.43-0.99).
CONCLUSION: Additional research and targeted outreach efforts are needed to understand geography-, population-, or practice-specific barriers impacting access to 2L therapy among patients with r/mCC.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: Contemporary, real-world data on eligible patients receiving treatment following progression on first-line (1L) recurrent or metastatic cervical cancer (r/mCC) therapy are needed to inform treatment algorithms and identify potential gaps in the r/mCC care continuum.
METHODS: This study estimated the prevalence and predictors of second-line (2L) r/mCC therapy among 1L-treated patients using the 2015-2020 IBM MarketScan® commercial claims database. Women ≥ 18 years diagnosed with cervical cancer and treated with first-line systemic therapies were identified and followed for 12 months from their 1L therapy end date. Women with claims for a new therapy after 60 days but no later than 365 days from the end of 1L treatment were identified as those who progressed and received 2L therapy for r/mCC. Descriptive statistics examined baseline cohort characteristics and multivariable logistic regression model examined the factors associated with receiving 2L treatment.
RESULTS: We identified 384 1L-treated patients with r/mCC with ≥ 12 months of follow-up post-1L treatment. During follow-up, over half (51.0 %) of the 1L-treated r/mCC patients received 2L treatment. Patients from the South and Midwest had a lower likelihood of receiving 2L treatment compared with those living in the Northeast (adjusted odds ratio [aOR] = 0.43; 0.23-0.84) and (aOR = 0.52; 0.28-0.95, respectively). Patients not treated with bevacizumab in 1L were also less likely to receive 2L therapy (aOR = 0.65; 0.43-0.99).
CONCLUSION: Additional research and targeted outreach efforts are needed to understand geography-, population-, or practice-specific barriers impacting access to 2L therapy among patients with r/mCC.
METHODS: This study estimated the prevalence and predictors of second-line (2L) r/mCC therapy among 1L-treated patients using the 2015-2020 IBM MarketScan® commercial claims database. Women ≥ 18 years diagnosed with cervical cancer and treated with first-line systemic therapies were identified and followed for 12 months from their 1L therapy end date. Women with claims for a new therapy after 60 days but no later than 365 days from the end of 1L treatment were identified as those who progressed and received 2L therapy for r/mCC. Descriptive statistics examined baseline cohort characteristics and multivariable logistic regression model examined the factors associated with receiving 2L treatment.
RESULTS: We identified 384 1L-treated patients with r/mCC with ≥ 12 months of follow-up post-1L treatment. During follow-up, over half (51.0 %) of the 1L-treated r/mCC patients received 2L treatment. Patients from the South and Midwest had a lower likelihood of receiving 2L treatment compared with those living in the Northeast (adjusted odds ratio [aOR] = 0.43; 0.23-0.84) and (aOR = 0.52; 0.28-0.95, respectively). Patients not treated with bevacizumab in 1L were also less likely to receive 2L therapy (aOR = 0.65; 0.43-0.99).
CONCLUSION: Additional research and targeted outreach efforts are needed to understand geography-, population-, or practice-specific barriers impacting access to 2L therapy among patients with r/mCC.
Steigenberger, Caroline; Flatscher-Thoeni, Magdalena; Siebert, Uwe; Leiter, Andrea M
Determinants of willingness to pay for health services: a systematic review of contingent valuation studies Journal Article
In: Eur J Health Econ, vol. 23, no. 9, pp. 1455–1482, 2022, ISSN: 1618-7601.
@article{pmid35166973,
title = {Determinants of willingness to pay for health services: a systematic review of contingent valuation studies},
author = {Caroline Steigenberger and Magdalena Flatscher-Thoeni and Uwe Siebert and Andrea M Leiter},
doi = {10.1007/s10198-022-01437-x},
issn = {1618-7601},
year = {2022},
date = {2022-12-01},
journal = {Eur J Health Econ},
volume = {23},
number = {9},
pages = {1455--1482},
abstract = {INTRODUCTION: Stated preference studies are a valuable tool to elicit respondents' willingness to pay (WTP) for goods or services, especially in situations where no market valuation exists. Contingent valuation (CV) is a widely used approach among stated-preference techniques for eliciting WTP if prices do not exist or do not reflect actual costs, for example, when services are covered by insurance. This review aimed to provide an overview of relevant factors determining WTP for health services to support variable selection.
METHODS: A comprehensive systematic literature search and review of CV studies assessing determinants of WTP for health services was conducted, including 11 electronic databases. Two of the authors made independent decisions on the eligibility of studies. We extracted all determinants used and related p values for the effect sizes (e.g. reported in regression models with WTP for a health service as outcome variable). Determinants were summarised in systematic evidence tables and structured by thematic domains.
RESULTS: We identified 2082 publications, of which 202 full texts were checked for eligibility. We included 62 publications on 61 studies in the review. Across all studies, we identified 22 WTP determinants and other factors from 5 thematic domains: sociodemographic characteristics, perceived threat, perceived benefit, perceived barriers, and other information.
CONCLUSION: Our review provides evidence on 22 relevant determinants of WTP for health services, which may be used for variable selection and as guidance for planning CV surveys. Endogeneity should be carefully considered before interpreting these determinants as causal factors and potential intervention targets.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
INTRODUCTION: Stated preference studies are a valuable tool to elicit respondents' willingness to pay (WTP) for goods or services, especially in situations where no market valuation exists. Contingent valuation (CV) is a widely used approach among stated-preference techniques for eliciting WTP if prices do not exist or do not reflect actual costs, for example, when services are covered by insurance. This review aimed to provide an overview of relevant factors determining WTP for health services to support variable selection.
METHODS: A comprehensive systematic literature search and review of CV studies assessing determinants of WTP for health services was conducted, including 11 electronic databases. Two of the authors made independent decisions on the eligibility of studies. We extracted all determinants used and related p values for the effect sizes (e.g. reported in regression models with WTP for a health service as outcome variable). Determinants were summarised in systematic evidence tables and structured by thematic domains.
RESULTS: We identified 2082 publications, of which 202 full texts were checked for eligibility. We included 62 publications on 61 studies in the review. Across all studies, we identified 22 WTP determinants and other factors from 5 thematic domains: sociodemographic characteristics, perceived threat, perceived benefit, perceived barriers, and other information.
CONCLUSION: Our review provides evidence on 22 relevant determinants of WTP for health services, which may be used for variable selection and as guidance for planning CV surveys. Endogeneity should be carefully considered before interpreting these determinants as causal factors and potential intervention targets.
METHODS: A comprehensive systematic literature search and review of CV studies assessing determinants of WTP for health services was conducted, including 11 electronic databases. Two of the authors made independent decisions on the eligibility of studies. We extracted all determinants used and related p values for the effect sizes (e.g. reported in regression models with WTP for a health service as outcome variable). Determinants were summarised in systematic evidence tables and structured by thematic domains.
RESULTS: We identified 2082 publications, of which 202 full texts were checked for eligibility. We included 62 publications on 61 studies in the review. Across all studies, we identified 22 WTP determinants and other factors from 5 thematic domains: sociodemographic characteristics, perceived threat, perceived benefit, perceived barriers, and other information.
CONCLUSION: Our review provides evidence on 22 relevant determinants of WTP for health services, which may be used for variable selection and as guidance for planning CV surveys. Endogeneity should be carefully considered before interpreting these determinants as causal factors and potential intervention targets.
Kuehne, Felicitas; Arvandi, Marjan; Hess, Lisa M; Faries, Douglas E; Gothe, Raffaella Matteucci; Gothe, Holger; Beyrer, Julie; Zeimet, Alain Gustave; Stojkov, Igor; Mühlberger, Nikolai; Oberaigner, Willi; Marth, Christian; Siebert, Uwe
In: J Clin Epidemiol, vol. 152, pp. 269-280, 2022, ISSN: 1878-5921.
@article{pmid36252741,
title = {Causal analyses with target trial emulation for real-world evidence removed large self-inflicted biases: Systematic bias assessment of ovarian cancer treatment effectiveness},
author = {Felicitas Kuehne and Marjan Arvandi and Lisa M Hess and Douglas E Faries and Raffaella Matteucci Gothe and Holger Gothe and Julie Beyrer and Alain Gustave Zeimet and Igor Stojkov and Nikolai M\"{u}hlberger and Willi Oberaigner and Christian Marth and Uwe Siebert},
doi = {10.1016/j.jclinepi.2022.10.005},
issn = {1878-5921},
year = {2022},
date = {2022-12-01},
urldate = {2022-10-01},
journal = {J Clin Epidemiol},
volume = {152},
pages = {269-280},
abstract = {BACKGROUND: Drawing causal conclusions from real-world data (RWD) poses methodological challenges and risk of bias. We aimed to systematically assess the type and impact of potential biases that may occur when analyzing RWD using the case of progressive ovarian cancer.
METHODS: We retrospectively compared overall survival with and without second-line chemotherapy using electronic medical records. Potential biases were determined using directed acyclic graphs. We followed a stepwise analytic approach ranging from crude analysis and multivariable-adjusted Cox model up to a full causal analysis using a marginal-structural-Cox-model (MSCM) with replicates emulating a reference randomized controlled trial. To assess biases, we compared effect estimates (hazard ratios [HRs]) of each approach to the HR of the reference trial.
RESULTS: The reference trial showed a HR for second-line versus delayed-therapy of 1.01 (95% confidence interval [95%CI]: 0.82-1.25). The corresponding HRs from the RWD analysis ranged from 0.51 for simple baseline adjustments to 1.41 (95%CI 1.22-1.64) accounting for immortal time bias with time-varying covariates. Causal trial emulation yielded a HR of 1.12 (95%CI: 0.96-1.28).
CONCLUSIONS: Our study, using ovarian cancer as an example, shows the importance of a thorough causal design and analysis if one is expecting RWD to emulate clinical trial results.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: Drawing causal conclusions from real-world data (RWD) poses methodological challenges and risk of bias. We aimed to systematically assess the type and impact of potential biases that may occur when analyzing RWD using the case of progressive ovarian cancer.
METHODS: We retrospectively compared overall survival with and without second-line chemotherapy using electronic medical records. Potential biases were determined using directed acyclic graphs. We followed a stepwise analytic approach ranging from crude analysis and multivariable-adjusted Cox model up to a full causal analysis using a marginal-structural-Cox-model (MSCM) with replicates emulating a reference randomized controlled trial. To assess biases, we compared effect estimates (hazard ratios [HRs]) of each approach to the HR of the reference trial.
RESULTS: The reference trial showed a HR for second-line versus delayed-therapy of 1.01 (95% confidence interval [95%CI]: 0.82-1.25). The corresponding HRs from the RWD analysis ranged from 0.51 for simple baseline adjustments to 1.41 (95%CI 1.22-1.64) accounting for immortal time bias with time-varying covariates. Causal trial emulation yielded a HR of 1.12 (95%CI: 0.96-1.28).
CONCLUSIONS: Our study, using ovarian cancer as an example, shows the importance of a thorough causal design and analysis if one is expecting RWD to emulate clinical trial results.
METHODS: We retrospectively compared overall survival with and without second-line chemotherapy using electronic medical records. Potential biases were determined using directed acyclic graphs. We followed a stepwise analytic approach ranging from crude analysis and multivariable-adjusted Cox model up to a full causal analysis using a marginal-structural-Cox-model (MSCM) with replicates emulating a reference randomized controlled trial. To assess biases, we compared effect estimates (hazard ratios [HRs]) of each approach to the HR of the reference trial.
RESULTS: The reference trial showed a HR for second-line versus delayed-therapy of 1.01 (95% confidence interval [95%CI]: 0.82-1.25). The corresponding HRs from the RWD analysis ranged from 0.51 for simple baseline adjustments to 1.41 (95%CI 1.22-1.64) accounting for immortal time bias with time-varying covariates. Causal trial emulation yielded a HR of 1.12 (95%CI: 0.96-1.28).
CONCLUSIONS: Our study, using ovarian cancer as an example, shows the importance of a thorough causal design and analysis if one is expecting RWD to emulate clinical trial results.
Rainer, Lukas; Bachner, Florian; Eglau, Karin; Ostermann, Herwig; Siebert, Uwe; Zuba, Martin
Comorbidities and COVID-19 hospitalization, ICU admission and hospital mortality in Austria : A retrospective cohort study Journal Article
In: Wien Klin Wochenschr, vol. 134, no. 23-24, pp. 856–867, 2022, ISSN: 1613-7671.
@article{pmid35608673,
title = {Comorbidities and COVID-19 hospitalization, ICU admission and hospital mortality in Austria : A retrospective cohort study},
author = {Lukas Rainer and Florian Bachner and Karin Eglau and Herwig Ostermann and Uwe Siebert and Martin Zuba},
doi = {10.1007/s00508-022-02036-9},
issn = {1613-7671},
year = {2022},
date = {2022-12-01},
journal = {Wien Klin Wochenschr},
volume = {134},
number = {23-24},
pages = {856--867},
abstract = {BACKGROUND: The protection of vulnerable populations is a central task in managing the Coronavirus disease 2019 (COVID-19) pandemic to avoid severe courses of COVID-19 and the risk of healthcare system capacity being exceeded. To identify factors of vulnerability in Austria, we assessed the impact of comorbidities on COVID-19 hospitalization, intensive care unit (ICU) admission, and hospital mortality.
METHODS: A retrospective cohort study was performed including all patients with COVID-19 in the period February 2020 to December 2021 who had a previous inpatient stay in the period 2015-2019 in Austria. All patients with COVID-19 were matched to population controls on age, sex, and healthcare region. Multiple logistic regression was used to estimate adjusted odds ratios (OR) of included factors with 95% confidence intervals (CI).
RESULTS: Hemiplegia or paraplegia constitutes the highest risk factor for hospitalization (OR 1.61, 95% CI 1.44-1.79), followed by COPD (OR 1.48, 95% CI 1.43-1.53) and diabetes without complications (OR 1.41, 95% CI 1.37-1.46). The highest risk factors for ICU admission are renal diseases (OR 1.76, 95% CI 1.61-1.92), diabetes without complications (OR 1.57, 95% CI 1.46-1.69) and COPD (OR 1.53, 95% CI 1.41-1.66). Hemiplegia or paraplegia, renal disease and COPD constitute the highest risk factors for hospital mortality, with ORs of 1.5. Diabetes without complications constitutes a significantly higher risk factor for women with respect to all three endpoints.
CONCLUSION: We contribute to the literature by identifying sex-specific risk factors. In general, our results are consistent with the literature, particularly regarding diabetes as a risk factor for severe courses of COVID-19. Due to the observational nature of our data, caution is warranted regarding causal interpretation. Our results contribute to the protection of vulnerable populations and may be used for targeting further pharmaceutical interventions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: The protection of vulnerable populations is a central task in managing the Coronavirus disease 2019 (COVID-19) pandemic to avoid severe courses of COVID-19 and the risk of healthcare system capacity being exceeded. To identify factors of vulnerability in Austria, we assessed the impact of comorbidities on COVID-19 hospitalization, intensive care unit (ICU) admission, and hospital mortality.
METHODS: A retrospective cohort study was performed including all patients with COVID-19 in the period February 2020 to December 2021 who had a previous inpatient stay in the period 2015-2019 in Austria. All patients with COVID-19 were matched to population controls on age, sex, and healthcare region. Multiple logistic regression was used to estimate adjusted odds ratios (OR) of included factors with 95% confidence intervals (CI).
RESULTS: Hemiplegia or paraplegia constitutes the highest risk factor for hospitalization (OR 1.61, 95% CI 1.44-1.79), followed by COPD (OR 1.48, 95% CI 1.43-1.53) and diabetes without complications (OR 1.41, 95% CI 1.37-1.46). The highest risk factors for ICU admission are renal diseases (OR 1.76, 95% CI 1.61-1.92), diabetes without complications (OR 1.57, 95% CI 1.46-1.69) and COPD (OR 1.53, 95% CI 1.41-1.66). Hemiplegia or paraplegia, renal disease and COPD constitute the highest risk factors for hospital mortality, with ORs of 1.5. Diabetes without complications constitutes a significantly higher risk factor for women with respect to all three endpoints.
CONCLUSION: We contribute to the literature by identifying sex-specific risk factors. In general, our results are consistent with the literature, particularly regarding diabetes as a risk factor for severe courses of COVID-19. Due to the observational nature of our data, caution is warranted regarding causal interpretation. Our results contribute to the protection of vulnerable populations and may be used for targeting further pharmaceutical interventions.
METHODS: A retrospective cohort study was performed including all patients with COVID-19 in the period February 2020 to December 2021 who had a previous inpatient stay in the period 2015-2019 in Austria. All patients with COVID-19 were matched to population controls on age, sex, and healthcare region. Multiple logistic regression was used to estimate adjusted odds ratios (OR) of included factors with 95% confidence intervals (CI).
RESULTS: Hemiplegia or paraplegia constitutes the highest risk factor for hospitalization (OR 1.61, 95% CI 1.44-1.79), followed by COPD (OR 1.48, 95% CI 1.43-1.53) and diabetes without complications (OR 1.41, 95% CI 1.37-1.46). The highest risk factors for ICU admission are renal diseases (OR 1.76, 95% CI 1.61-1.92), diabetes without complications (OR 1.57, 95% CI 1.46-1.69) and COPD (OR 1.53, 95% CI 1.41-1.66). Hemiplegia or paraplegia, renal disease and COPD constitute the highest risk factors for hospital mortality, with ORs of 1.5. Diabetes without complications constitutes a significantly higher risk factor for women with respect to all three endpoints.
CONCLUSION: We contribute to the literature by identifying sex-specific risk factors. In general, our results are consistent with the literature, particularly regarding diabetes as a risk factor for severe courses of COVID-19. Due to the observational nature of our data, caution is warranted regarding causal interpretation. Our results contribute to the protection of vulnerable populations and may be used for targeting further pharmaceutical interventions.
Garcia, Gian-Gabriel P; Stringfellow, Erin J; DiGennaro, Catherine; Poellinger, Nicole; Wood, Jaden; Wakeman, Sarah; Jalali, Mohammad S
Opioid overdose decedent characteristics during COVID-19 Journal Article
In: Ann Med, vol. 54, no. 1, pp. 1081–1088, 2022, ISSN: 1365-2060.
@article{pmid35467475,
title = {Opioid overdose decedent characteristics during COVID-19},
author = {Gian-Gabriel P Garcia and Erin J Stringfellow and Catherine DiGennaro and Nicole Poellinger and Jaden Wood and Sarah Wakeman and Mohammad S Jalali},
doi = {10.1080/07853890.2022.2067350},
issn = {1365-2060},
year = {2022},
date = {2022-12-01},
journal = {Ann Med},
volume = {54},
number = {1},
pages = {1081--1088},
abstract = {INTRODUCTION: Alongside the emergence of COVID-19 in the United States, several reports highlighted increasing rates of opioid overdose from preliminary data. Yet, little is known about how state-level opioid overdose death trends and decedent characteristics have evolved using official death records.
METHODS: We requested vital statistics data from 2018-2020 from all 50 states and the District of Columbia, receiving data from 14 states. Accounting for COVID-19, we excluded states without data past March 2020, leaving 11 states for analysis. We defined state-specific analysis periods from March 13 until the latest reliable date in each state's data, then conducted retrospective year-over-year analyses comparing opioid-related overdose death rates, the presence of specific opioids and other psychoactive substances, and decedents' sex, race, and age from 2020 to 2019 and 2019 to 2018 within each state's analysis period. We assessed whether significant changes in 2020 vs. 2019 in opioid overdose deaths were new or continuing trends using joinpoint regression.
RESULTS: We found significant increases in opioid-related overdose death rates in Alaska (55.3%), Colorado (80.2%), Indiana (40.1%), Nevada (50.0%), North Carolina (30.5%), Rhode Island (29.6%), and Virginia (66.4%) - all continuing previous trends. Increases in synthetic opioid-involved overdose deaths were new in Alaska (136.5%), Indiana (27.6%), and Virginia (16.5%), whilst continuing in Colorado (44.4%), Connecticut (3.6%), Nevada (75.0%), and North Carolina (14.6%). We found new increases in male decedents in Indiana (12.0%), and continuing increases in Colorado (15.2%). We also found continuing increases in Black non-Hispanic decedents in Massachusetts (43.9%) and Virginia (33.7%).
CONCLUSION: This research analyzes vital statistics data from 11 states, highlighting new trends in opioid overdose deaths and decedent characteristics across 10 of these states. These findings can inform state-specific public health interventions and highlight the need for timely and comprehensive fatal opioid overdose data, especially amidst concurrent crises such as COVID-19. Key messages:Our results highlight shifts in opioid overdose trends during the COVID-19 pandemic that cannot otherwise be extracted from aggregated or provisional opioid overdose death data such as those published by the Centres for Disease Control and Prevention.Fentanyl and other synthetic opioids continue to drive increases in fatal overdoses, making it difficult to separate these trends from any possible COVID-19-related factors.Black non-Hispanic people are making up an increasing proportion of opioid overdose deaths in some states.State-specific limitations and variations in data-reporting for vital statistics make it challenging to acquire and analyse up-to-date data on opioid-related overdose deaths. More timely and comprehensive data are needed to generate broader insights on the nature of the intersecting opioid and COVID-19 crises.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
INTRODUCTION: Alongside the emergence of COVID-19 in the United States, several reports highlighted increasing rates of opioid overdose from preliminary data. Yet, little is known about how state-level opioid overdose death trends and decedent characteristics have evolved using official death records.
METHODS: We requested vital statistics data from 2018-2020 from all 50 states and the District of Columbia, receiving data from 14 states. Accounting for COVID-19, we excluded states without data past March 2020, leaving 11 states for analysis. We defined state-specific analysis periods from March 13 until the latest reliable date in each state's data, then conducted retrospective year-over-year analyses comparing opioid-related overdose death rates, the presence of specific opioids and other psychoactive substances, and decedents' sex, race, and age from 2020 to 2019 and 2019 to 2018 within each state's analysis period. We assessed whether significant changes in 2020 vs. 2019 in opioid overdose deaths were new or continuing trends using joinpoint regression.
RESULTS: We found significant increases in opioid-related overdose death rates in Alaska (55.3%), Colorado (80.2%), Indiana (40.1%), Nevada (50.0%), North Carolina (30.5%), Rhode Island (29.6%), and Virginia (66.4%) - all continuing previous trends. Increases in synthetic opioid-involved overdose deaths were new in Alaska (136.5%), Indiana (27.6%), and Virginia (16.5%), whilst continuing in Colorado (44.4%), Connecticut (3.6%), Nevada (75.0%), and North Carolina (14.6%). We found new increases in male decedents in Indiana (12.0%), and continuing increases in Colorado (15.2%). We also found continuing increases in Black non-Hispanic decedents in Massachusetts (43.9%) and Virginia (33.7%).
CONCLUSION: This research analyzes vital statistics data from 11 states, highlighting new trends in opioid overdose deaths and decedent characteristics across 10 of these states. These findings can inform state-specific public health interventions and highlight the need for timely and comprehensive fatal opioid overdose data, especially amidst concurrent crises such as COVID-19. Key messages:Our results highlight shifts in opioid overdose trends during the COVID-19 pandemic that cannot otherwise be extracted from aggregated or provisional opioid overdose death data such as those published by the Centres for Disease Control and Prevention.Fentanyl and other synthetic opioids continue to drive increases in fatal overdoses, making it difficult to separate these trends from any possible COVID-19-related factors.Black non-Hispanic people are making up an increasing proportion of opioid overdose deaths in some states.State-specific limitations and variations in data-reporting for vital statistics make it challenging to acquire and analyse up-to-date data on opioid-related overdose deaths. More timely and comprehensive data are needed to generate broader insights on the nature of the intersecting opioid and COVID-19 crises.
METHODS: We requested vital statistics data from 2018-2020 from all 50 states and the District of Columbia, receiving data from 14 states. Accounting for COVID-19, we excluded states without data past March 2020, leaving 11 states for analysis. We defined state-specific analysis periods from March 13 until the latest reliable date in each state's data, then conducted retrospective year-over-year analyses comparing opioid-related overdose death rates, the presence of specific opioids and other psychoactive substances, and decedents' sex, race, and age from 2020 to 2019 and 2019 to 2018 within each state's analysis period. We assessed whether significant changes in 2020 vs. 2019 in opioid overdose deaths were new or continuing trends using joinpoint regression.
RESULTS: We found significant increases in opioid-related overdose death rates in Alaska (55.3%), Colorado (80.2%), Indiana (40.1%), Nevada (50.0%), North Carolina (30.5%), Rhode Island (29.6%), and Virginia (66.4%) - all continuing previous trends. Increases in synthetic opioid-involved overdose deaths were new in Alaska (136.5%), Indiana (27.6%), and Virginia (16.5%), whilst continuing in Colorado (44.4%), Connecticut (3.6%), Nevada (75.0%), and North Carolina (14.6%). We found new increases in male decedents in Indiana (12.0%), and continuing increases in Colorado (15.2%). We also found continuing increases in Black non-Hispanic decedents in Massachusetts (43.9%) and Virginia (33.7%).
CONCLUSION: This research analyzes vital statistics data from 11 states, highlighting new trends in opioid overdose deaths and decedent characteristics across 10 of these states. These findings can inform state-specific public health interventions and highlight the need for timely and comprehensive fatal opioid overdose data, especially amidst concurrent crises such as COVID-19. Key messages:Our results highlight shifts in opioid overdose trends during the COVID-19 pandemic that cannot otherwise be extracted from aggregated or provisional opioid overdose death data such as those published by the Centres for Disease Control and Prevention.Fentanyl and other synthetic opioids continue to drive increases in fatal overdoses, making it difficult to separate these trends from any possible COVID-19-related factors.Black non-Hispanic people are making up an increasing proportion of opioid overdose deaths in some states.State-specific limitations and variations in data-reporting for vital statistics make it challenging to acquire and analyse up-to-date data on opioid-related overdose deaths. More timely and comprehensive data are needed to generate broader insights on the nature of the intersecting opioid and COVID-19 crises.
Chen, Qiushi; Griffin, Paul M; Kawasaki, Sarah S
Disability-Adjusted Life Years for Drug Overdose Crisis and COVID-19 Are Comparable During the Two Years of Pandemic in the United States Journal Article
In: Value Health, 2022, ISSN: 1524-4733.
@article{pmid36436793,
title = {Disability-Adjusted Life Years for Drug Overdose Crisis and COVID-19 Are Comparable During the Two Years of Pandemic in the United States},
author = {Qiushi Chen and Paul M Griffin and Sarah S Kawasaki},
doi = {10.1016/j.jval.2022.11.010},
issn = {1524-4733},
year = {2022},
date = {2022-11-01},
journal = {Value Health},
abstract = {OBJECTIVES: The drug overdose crisis with shifting patterns from primarily opioid to polysubstance uses and COVID-19 infections are two concurrent public health crises in the United States, affecting the population of sizes in different magnitudes (approximately <10 million for substance use disorder (SUD) and drug overdoses vs. 80 million for COVID-19 within two years of the pandemic). Our objective is to compare the relative scale of disease burden for the two crises within a common framework, which could help inform policymakers with resource allocation and prioritization strategies.
METHODS: We calculated disability-adjusted life years (DALYs) for SUD (including opioids and stimulants) and COVID-19 infections, respectively. We collected estimates for SUD prevalence, overdose deaths, COVID-19 cases and deaths, disability weights, and life expectancy from multiple publicly available sources. We then compared age distributions of estimated DALYs.
RESULTS: We estimated a total burden of 13.83 million DALYs for SUD and drug overdoses and 15.03 million DALYs for COVID-19 in two years since March 2020. COVID-19 burden was dominated by the fatal burden (>95% of total DALYs), whereas SUD burden was attributed to both fatal (53%) and non-fatal burdens (47%). The highest disease burden was among individuals aged 30-39 for SUD (27%) and 50-64 for COVID-19 (31%).
CONCLUSIONS: Despite the smaller size of the affected population, SUD and drug overdoses resulted in comparable disease burden to the COVID-19 pandemic. Additional resources supporting evidence-based interventions in prevention and treatment may be warranted to ameliorate SUD and drug overdoses during both the pandemic and post-pandemic recovery.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
OBJECTIVES: The drug overdose crisis with shifting patterns from primarily opioid to polysubstance uses and COVID-19 infections are two concurrent public health crises in the United States, affecting the population of sizes in different magnitudes (approximately <10 million for substance use disorder (SUD) and drug overdoses vs. 80 million for COVID-19 within two years of the pandemic). Our objective is to compare the relative scale of disease burden for the two crises within a common framework, which could help inform policymakers with resource allocation and prioritization strategies.
METHODS: We calculated disability-adjusted life years (DALYs) for SUD (including opioids and stimulants) and COVID-19 infections, respectively. We collected estimates for SUD prevalence, overdose deaths, COVID-19 cases and deaths, disability weights, and life expectancy from multiple publicly available sources. We then compared age distributions of estimated DALYs.
RESULTS: We estimated a total burden of 13.83 million DALYs for SUD and drug overdoses and 15.03 million DALYs for COVID-19 in two years since March 2020. COVID-19 burden was dominated by the fatal burden (>95% of total DALYs), whereas SUD burden was attributed to both fatal (53%) and non-fatal burdens (47%). The highest disease burden was among individuals aged 30-39 for SUD (27%) and 50-64 for COVID-19 (31%).
CONCLUSIONS: Despite the smaller size of the affected population, SUD and drug overdoses resulted in comparable disease burden to the COVID-19 pandemic. Additional resources supporting evidence-based interventions in prevention and treatment may be warranted to ameliorate SUD and drug overdoses during both the pandemic and post-pandemic recovery.
METHODS: We calculated disability-adjusted life years (DALYs) for SUD (including opioids and stimulants) and COVID-19 infections, respectively. We collected estimates for SUD prevalence, overdose deaths, COVID-19 cases and deaths, disability weights, and life expectancy from multiple publicly available sources. We then compared age distributions of estimated DALYs.
RESULTS: We estimated a total burden of 13.83 million DALYs for SUD and drug overdoses and 15.03 million DALYs for COVID-19 in two years since March 2020. COVID-19 burden was dominated by the fatal burden (>95% of total DALYs), whereas SUD burden was attributed to both fatal (53%) and non-fatal burdens (47%). The highest disease burden was among individuals aged 30-39 for SUD (27%) and 50-64 for COVID-19 (31%).
CONCLUSIONS: Despite the smaller size of the affected population, SUD and drug overdoses resulted in comparable disease burden to the COVID-19 pandemic. Additional resources supporting evidence-based interventions in prevention and treatment may be warranted to ameliorate SUD and drug overdoses during both the pandemic and post-pandemic recovery.
Herzog, Chiara; Sundström, Karin; Jones, Allison; Evans, Iona; Barrett, James E; Wang, Jiangrong; Redl, Elisa; Schreiberhuber, Lena; Costas, Laura; Paytubi, Sonia; Dostalek, Lukas; Zikan, Michal; Cibula, David; Sroczynski, Gaby; Siebert, Uwe; Dillner, Joakim; Widschwendter, Martin
In: Clin Epigenetics, vol. 14, no. 1, pp. 150, 2022, ISSN: 1868-7083.
@article{pmid36414968,
title = {DNA methylation-based detection and prediction of cervical intraepithelial neoplasia grade 3 and invasive cervical cancer with the WID™-qCIN test},
author = {Chiara Herzog and Karin Sundstr\"{o}m and Allison Jones and Iona Evans and James E Barrett and Jiangrong Wang and Elisa Redl and Lena Schreiberhuber and Laura Costas and Sonia Paytubi and Lukas Dostalek and Michal Zikan and David Cibula and Gaby Sroczynski and Uwe Siebert and Joakim Dillner and Martin Widschwendter},
doi = {10.1186/s13148-022-01353-0},
issn = {1868-7083},
year = {2022},
date = {2022-11-01},
journal = {Clin Epigenetics},
volume = {14},
number = {1},
pages = {150},
abstract = {BACKGROUND: Cervical screening using primary human papilloma virus (HPV) testing and cytology is being implemented in several countries. Cytology as triage for colposcopy referral suffers from several shortcomings. HPV testing overcomes some of these but lacks specificity in women under 30. Here, we aimed to develop and validate an automatable triage test that is highly sensitive and specific independently of age and sample heterogeneity, and predicts progression to CIN3+ in HPV+ patients.
RESULTS: The WID™-qCIN, assessing three regions in human genes DPP6, RALYL, and GSX1, was validated in both a diagnostic (case-control) and predictive setting (nested case-control), in a total of 761 samples. Using a predefined threshold, the sensitivity of the WID™-qCIN test was 100% and 78% to detect invasive cancer and CIN3, respectively. Sensitivity to detect CIN3+ was 65% and 83% for women < and ≥ 30 years of age. The specificity was 90%. Importantly, the WID™-qCIN test identified 52% of ≥ 30-year-old women with a cytology negative (cyt-) index sample who were diagnosed with CIN3 1-4 years after sample donation.
CONCLUSION: We identified suitable DNAme regions in an epigenome-wide discovery using HPV+ controls and CIN3+ cases and established the WID™-qCIN, a PCR-based DNAme test. The WID™-qCIN test has a high sensitivity and specificity that may outperform conventional cervical triage tests and can in an objective, cheap, and scalable fashion identify most women with and at risk of (pre-)invasive cervical cancer. However, evaluation was limited to case-control settings and future studies will assess performance and generalisability in a randomised controlled trial.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: Cervical screening using primary human papilloma virus (HPV) testing and cytology is being implemented in several countries. Cytology as triage for colposcopy referral suffers from several shortcomings. HPV testing overcomes some of these but lacks specificity in women under 30. Here, we aimed to develop and validate an automatable triage test that is highly sensitive and specific independently of age and sample heterogeneity, and predicts progression to CIN3+ in HPV+ patients.
RESULTS: The WID™-qCIN, assessing three regions in human genes DPP6, RALYL, and GSX1, was validated in both a diagnostic (case-control) and predictive setting (nested case-control), in a total of 761 samples. Using a predefined threshold, the sensitivity of the WID™-qCIN test was 100% and 78% to detect invasive cancer and CIN3, respectively. Sensitivity to detect CIN3+ was 65% and 83% for women < and ≥ 30 years of age. The specificity was 90%. Importantly, the WID™-qCIN test identified 52% of ≥ 30-year-old women with a cytology negative (cyt-) index sample who were diagnosed with CIN3 1-4 years after sample donation.
CONCLUSION: We identified suitable DNAme regions in an epigenome-wide discovery using HPV+ controls and CIN3+ cases and established the WID™-qCIN, a PCR-based DNAme test. The WID™-qCIN test has a high sensitivity and specificity that may outperform conventional cervical triage tests and can in an objective, cheap, and scalable fashion identify most women with and at risk of (pre-)invasive cervical cancer. However, evaluation was limited to case-control settings and future studies will assess performance and generalisability in a randomised controlled trial.
RESULTS: The WID™-qCIN, assessing three regions in human genes DPP6, RALYL, and GSX1, was validated in both a diagnostic (case-control) and predictive setting (nested case-control), in a total of 761 samples. Using a predefined threshold, the sensitivity of the WID™-qCIN test was 100% and 78% to detect invasive cancer and CIN3, respectively. Sensitivity to detect CIN3+ was 65% and 83% for women < and ≥ 30 years of age. The specificity was 90%. Importantly, the WID™-qCIN test identified 52% of ≥ 30-year-old women with a cytology negative (cyt-) index sample who were diagnosed with CIN3 1-4 years after sample donation.
CONCLUSION: We identified suitable DNAme regions in an epigenome-wide discovery using HPV+ controls and CIN3+ cases and established the WID™-qCIN, a PCR-based DNAme test. The WID™-qCIN test has a high sensitivity and specificity that may outperform conventional cervical triage tests and can in an objective, cheap, and scalable fashion identify most women with and at risk of (pre-)invasive cervical cancer. However, evaluation was limited to case-control settings and future studies will assess performance and generalisability in a randomised controlled trial.
Kramer, Jennifer R; Cao, Yumei; Li, Liang; Smith, Donna; Chhatwal, Jagpreet; El-Serag, Hashem B; Kanwal, Fasiha
Longitudinal Associations of Risk Factors and Hepatocellular Carcinoma in Patients With Cured Hepatitis C Virus Infection Journal Article
In: Am J Gastroenterol, vol. 117, no. 11, pp. 1834–1844, 2022, ISSN: 1572-0241.
@article{pmid36327437,
title = {Longitudinal Associations of Risk Factors and Hepatocellular Carcinoma in Patients With Cured Hepatitis C Virus Infection},
author = {Jennifer R Kramer and Yumei Cao and Liang Li and Donna Smith and Jagpreet Chhatwal and Hashem B El-Serag and Fasiha Kanwal},
doi = {10.14309/ajg.0000000000001968},
issn = {1572-0241},
year = {2022},
date = {2022-11-01},
journal = {Am J Gastroenterol},
volume = {117},
number = {11},
pages = {1834--1844},
abstract = {INTRODUCTION: There are limited data on the effect and evolution of risk factors for hepatocellular carcinoma (HCC) in patients with virologically cured hepatitis C virus (HCV) infection.
METHODS: We conducted a retrospective cohort study of patients with HCV who achieved sustained virological response with direct-acting antivirals from 130 Veterans Administration hospitals during 2014-2018, followed through 2021. Cox proportional hazards models were constructed at 3 landmark times (baseline and 12 and 24 months after sustained virological response) to examine associations between demographic, clinical, and behavioral factors and HCC risk, stratified by cirrhosis status.
RESULTS: Among 92,567 patients (32% cirrhosis), 3,247 cases of HCC were diagnosed during a mean follow-up of 2.5 years. In patients with cirrhosis, male sex (hazard ratios [HR]: 1.89, 1.93, and 1.99), cirrhosis duration ≥5 years (HR: 1.71, 1.79, and 1.34), varices (HR: 1.73, 1.60, and 1.56), baseline albumin (HR: 0.48, 0.47, and 0.49), and change in albumin (HR: 0.82 and 0.90) predicted HCC risk at each landmark time. HCV genotype 3, previous treatment, bilirubin, smoking, and race influenced HCC risk at baseline, but their effects attenuated over time. In patients without cirrhosis, diabetes (HR: 1.54, 1.42, and 1.47) and hypertension (HR: 1.59, 1.65, and 1.74) were associated with HCC risk at all landmark times. Changes in fibrosis-4 scores over time were associated with HCC risk both in patients with and without cirrhosis.
DISCUSSION: Risk factors for HCC were different in patients with and without cirrhosis and some also evolved during follow-up. These factors can help with risk stratification and HCC surveillance decisions in patients with cured HCV.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
INTRODUCTION: There are limited data on the effect and evolution of risk factors for hepatocellular carcinoma (HCC) in patients with virologically cured hepatitis C virus (HCV) infection.
METHODS: We conducted a retrospective cohort study of patients with HCV who achieved sustained virological response with direct-acting antivirals from 130 Veterans Administration hospitals during 2014-2018, followed through 2021. Cox proportional hazards models were constructed at 3 landmark times (baseline and 12 and 24 months after sustained virological response) to examine associations between demographic, clinical, and behavioral factors and HCC risk, stratified by cirrhosis status.
RESULTS: Among 92,567 patients (32% cirrhosis), 3,247 cases of HCC were diagnosed during a mean follow-up of 2.5 years. In patients with cirrhosis, male sex (hazard ratios [HR]: 1.89, 1.93, and 1.99), cirrhosis duration ≥5 years (HR: 1.71, 1.79, and 1.34), varices (HR: 1.73, 1.60, and 1.56), baseline albumin (HR: 0.48, 0.47, and 0.49), and change in albumin (HR: 0.82 and 0.90) predicted HCC risk at each landmark time. HCV genotype 3, previous treatment, bilirubin, smoking, and race influenced HCC risk at baseline, but their effects attenuated over time. In patients without cirrhosis, diabetes (HR: 1.54, 1.42, and 1.47) and hypertension (HR: 1.59, 1.65, and 1.74) were associated with HCC risk at all landmark times. Changes in fibrosis-4 scores over time were associated with HCC risk both in patients with and without cirrhosis.
DISCUSSION: Risk factors for HCC were different in patients with and without cirrhosis and some also evolved during follow-up. These factors can help with risk stratification and HCC surveillance decisions in patients with cured HCV.
METHODS: We conducted a retrospective cohort study of patients with HCV who achieved sustained virological response with direct-acting antivirals from 130 Veterans Administration hospitals during 2014-2018, followed through 2021. Cox proportional hazards models were constructed at 3 landmark times (baseline and 12 and 24 months after sustained virological response) to examine associations between demographic, clinical, and behavioral factors and HCC risk, stratified by cirrhosis status.
RESULTS: Among 92,567 patients (32% cirrhosis), 3,247 cases of HCC were diagnosed during a mean follow-up of 2.5 years. In patients with cirrhosis, male sex (hazard ratios [HR]: 1.89, 1.93, and 1.99), cirrhosis duration ≥5 years (HR: 1.71, 1.79, and 1.34), varices (HR: 1.73, 1.60, and 1.56), baseline albumin (HR: 0.48, 0.47, and 0.49), and change in albumin (HR: 0.82 and 0.90) predicted HCC risk at each landmark time. HCV genotype 3, previous treatment, bilirubin, smoking, and race influenced HCC risk at baseline, but their effects attenuated over time. In patients without cirrhosis, diabetes (HR: 1.54, 1.42, and 1.47) and hypertension (HR: 1.59, 1.65, and 1.74) were associated with HCC risk at all landmark times. Changes in fibrosis-4 scores over time were associated with HCC risk both in patients with and without cirrhosis.
DISCUSSION: Risk factors for HCC were different in patients with and without cirrhosis and some also evolved during follow-up. These factors can help with risk stratification and HCC surveillance decisions in patients with cured HCV.
Javed, Sumreen; Soukhtehzari, Sepideh; Fernandes, Nazarine; Williams, Karla C
Longitudinal bioluminescence imaging to monitor breast tumor growth and treatment response using the chick chorioallantoic membrane model Journal Article
In: Sci Rep, vol. 12, no. 1, pp. 17192, 2022, ISSN: 2045-2322.
@article{pmid36229503,
title = {Longitudinal bioluminescence imaging to monitor breast tumor growth and treatment response using the chick chorioallantoic membrane model},
author = {Sumreen Javed and Sepideh Soukhtehzari and Nazarine Fernandes and Karla C Williams},
doi = {10.1038/s41598-022-20854-9},
issn = {2045-2322},
year = {2022},
date = {2022-10-01},
journal = {Sci Rep},
volume = {12},
number = {1},
pages = {17192},
abstract = {The development of successful treatment regimens for breast cancer requires strong pre-clinical data generated in physiologically relevant pre-clinical models. Here we report the development of the chick embryo chorioallantoic membrane (CAM) model to study tumor growth and angiogenesis using breast cancer cell lines. MDA-MB-231 and MCF7 tumor cell lines were engrafted onto the chick embryo CAM to study tumor growth and treatment response. Tumor growth was evaluated through bioluminescence imaging and a significant increase in tumor size and vascularization was found over a 9-day period. We then evaluated the impact of anti-angiogenic drugs, axitinib and bevacizumab, on tumor growth and angiogenesis. Drug treatment significantly reduced tumor vascularization and size. Overall, our findings demonstrate that the chick embryo CAM is a clinically relevant model to monitor therapeutic response in breast cancer and can be used as a platform for drug screening to evaluate not only gross changes in tumor burden but physiological processes such as angiogenesis.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The development of successful treatment regimens for breast cancer requires strong pre-clinical data generated in physiologically relevant pre-clinical models. Here we report the development of the chick embryo chorioallantoic membrane (CAM) model to study tumor growth and angiogenesis using breast cancer cell lines. MDA-MB-231 and MCF7 tumor cell lines were engrafted onto the chick embryo CAM to study tumor growth and treatment response. Tumor growth was evaluated through bioluminescence imaging and a significant increase in tumor size and vascularization was found over a 9-day period. We then evaluated the impact of anti-angiogenic drugs, axitinib and bevacizumab, on tumor growth and angiogenesis. Drug treatment significantly reduced tumor vascularization and size. Overall, our findings demonstrate that the chick embryo CAM is a clinically relevant model to monitor therapeutic response in breast cancer and can be used as a platform for drug screening to evaluate not only gross changes in tumor burden but physiological processes such as angiogenesis.
Anderson, Mark A; Mercaldo, Sarah; Chung, Ryan; Ulrich, Ethan; Jones, Randall W; Harisinghani, Mukesh
Improving Prostate Cancer Detection With MRI: A Multi-Reader, Multi-Case Study Using Computer-Aided Detection (CAD) Journal Article
In: Acad Radiol, 2022, ISSN: 1878-4046.
@article{pmid36216684,
title = {Improving Prostate Cancer Detection With MRI: A Multi-Reader, Multi-Case Study Using Computer-Aided Detection (CAD)},
author = {Mark A Anderson and Sarah Mercaldo and Ryan Chung and Ethan Ulrich and Randall W Jones and Mukesh Harisinghani},
doi = {10.1016/j.acra.2022.09.009},
issn = {1878-4046},
year = {2022},
date = {2022-10-01},
journal = {Acad Radiol},
abstract = {RATIONALE AND OBJECTIVES: To evaluate whether addition of a computer-aided diagnostic (CAD) generated MRI series improves detection of clinically significant prostate cancer.
MATERIALS AND METHODS: Nine radiologists retrospectively interpreted 150 prostate MRI examinations without and then with an additional random forest-based CAD model-generated MRI series. Characteristics of biopsy negative versus positive (Gleason ≥ 7 adenocarcinoma) groups were compared using the Wilcoxon test for continuous and Pearson's chi-squared test for categorical variables. The diagnostic performance of readers was compared without versus with CAD using MRMC methods to estimate the area under the receiver operator characteristic curve (AUC). Inter-reader agreement was assessed using weighted inter-rater agreement statistics. Analyses were repeated in peripheral and transition zone subgroups.
RESULTS: Among 150 men with median age 67 ± 7.4 years, those with clinically significant prostate cancer were older (68 ± 7.6 years vs. 66 ± 7.0 years; p < .02), had smaller prostate volume (43.9 mL vs. 60.6 mL; p < .001), and no difference in prostate specific antigen (PSA) levels (7.8 ng/mL vs. 6.9 ng/mL; p = .08), but higher PSA density (0.17 ng/mL/cc vs. 0.10 ng/mL/cc; p < .001). Inter-rater agreement (IRA) for PI-RADS scores was moderate without CAD and significantly improved to substantial with CAD (IRA = 0.47 vs. 0.65; p < .001). CAD also significantly improved average reader AUC (AUC = 0.72, vs. AUC = 0.67; p = .02).
CONCLUSION: Addition of a random forest method-based, CAD-generated MRI image series improved inter-reader agreement and diagnostic performance for detection of clinically significant prostate cancer, particularly in the transition zone.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
RATIONALE AND OBJECTIVES: To evaluate whether addition of a computer-aided diagnostic (CAD) generated MRI series improves detection of clinically significant prostate cancer.
MATERIALS AND METHODS: Nine radiologists retrospectively interpreted 150 prostate MRI examinations without and then with an additional random forest-based CAD model-generated MRI series. Characteristics of biopsy negative versus positive (Gleason ≥ 7 adenocarcinoma) groups were compared using the Wilcoxon test for continuous and Pearson's chi-squared test for categorical variables. The diagnostic performance of readers was compared without versus with CAD using MRMC methods to estimate the area under the receiver operator characteristic curve (AUC). Inter-reader agreement was assessed using weighted inter-rater agreement statistics. Analyses were repeated in peripheral and transition zone subgroups.
RESULTS: Among 150 men with median age 67 ± 7.4 years, those with clinically significant prostate cancer were older (68 ± 7.6 years vs. 66 ± 7.0 years; p < .02), had smaller prostate volume (43.9 mL vs. 60.6 mL; p < .001), and no difference in prostate specific antigen (PSA) levels (7.8 ng/mL vs. 6.9 ng/mL; p = .08), but higher PSA density (0.17 ng/mL/cc vs. 0.10 ng/mL/cc; p < .001). Inter-rater agreement (IRA) for PI-RADS scores was moderate without CAD and significantly improved to substantial with CAD (IRA = 0.47 vs. 0.65; p < .001). CAD also significantly improved average reader AUC (AUC = 0.72, vs. AUC = 0.67; p = .02).
CONCLUSION: Addition of a random forest method-based, CAD-generated MRI image series improved inter-reader agreement and diagnostic performance for detection of clinically significant prostate cancer, particularly in the transition zone.
MATERIALS AND METHODS: Nine radiologists retrospectively interpreted 150 prostate MRI examinations without and then with an additional random forest-based CAD model-generated MRI series. Characteristics of biopsy negative versus positive (Gleason ≥ 7 adenocarcinoma) groups were compared using the Wilcoxon test for continuous and Pearson's chi-squared test for categorical variables. The diagnostic performance of readers was compared without versus with CAD using MRMC methods to estimate the area under the receiver operator characteristic curve (AUC). Inter-reader agreement was assessed using weighted inter-rater agreement statistics. Analyses were repeated in peripheral and transition zone subgroups.
RESULTS: Among 150 men with median age 67 ± 7.4 years, those with clinically significant prostate cancer were older (68 ± 7.6 years vs. 66 ± 7.0 years; p < .02), had smaller prostate volume (43.9 mL vs. 60.6 mL; p < .001), and no difference in prostate specific antigen (PSA) levels (7.8 ng/mL vs. 6.9 ng/mL; p = .08), but higher PSA density (0.17 ng/mL/cc vs. 0.10 ng/mL/cc; p < .001). Inter-rater agreement (IRA) for PI-RADS scores was moderate without CAD and significantly improved to substantial with CAD (IRA = 0.47 vs. 0.65; p < .001). CAD also significantly improved average reader AUC (AUC = 0.72, vs. AUC = 0.67; p = .02).
CONCLUSION: Addition of a random forest method-based, CAD-generated MRI image series improved inter-reader agreement and diagnostic performance for detection of clinically significant prostate cancer, particularly in the transition zone.
DiGennaro, Catherine; Vahdat, Vahab; Jalali, Mohammad; Toumi, Asmae; Watson, Tina; Gazelle, G Scott; Mercaldo, Nathaniel; Lubitz, Carrie C
In: Thyroid, vol. 32, iss. 10, pp. 1144-1157, 2022, ISSN: 1557-9077.
@article{pmid35999710,
title = {Assessing Bias and Limitations of Clinical Validation Studies of Molecular Diagnostic Tests for Indeterminate Thyroid Nodules: Systematic Review and Meta-Analysis},
author = {Catherine DiGennaro and Vahab Vahdat and Mohammad Jalali and Asmae Toumi and Tina Watson and G Scott Gazelle and Nathaniel Mercaldo and Carrie C Lubitz},
doi = {10.1089/thy.2022.0269},
issn = {1557-9077},
year = {2022},
date = {2022-10-01},
urldate = {2022-09-26},
journal = {Thyroid},
volume = {32},
issue = {10},
pages = {1144-1157},
abstract = {BACKGROUND: Molecular tests for thyroid nodules with indeterminate fine needle aspiration results are increasingly used in clinical practice; however, true diagnostic summaries of these tests are unknown. A systematic review and meta-analysis were completed to (1) evaluate the accuracy of commercially available molecular tests for malignancy in indeterminate thyroid nodules and (2) quantify biases and limitations in studies which validate those tests.
METHODS: PubMed, EMBASE, and Web of Science were systematically searched through July 2021. English language articles that reported original clinical validation attempts of molecular tests for indeterminate thyroid nodules were included if they reported counts of true negative, true positive, false negative, and false positive results. We performed screening and full text review, followed by assessment of eight common biases and limitations, extraction of diagnostic and histopathological information, and meta-analysis of clinical validity using a bivariate linear mixed-effects model.
RESULTS: 49 studies were included. Meta-analysis of Afirma GEC (n=38 studies) revealed a sensitivity of 0.92 (95% CI: 0.90-0.94), specificity of 0.26 (0.20-0.32), negative likelihood ratio (LR-) of 0.32 (0.23-0.44), positive likelihood ratio (LR+) of 1.24 (1.15-1.35), and AUC of 0.83 (0.74-0.89). Afirma GSC (n=10) had a sensitivity of 0.94 (0.89-0.96), specificity of 0.38 (0.27-0.50), LR- of 0.18 (0.10-0.30), LR+ of 1.52 (1.28-1.87), and AUC of 0.91 (0.62-0.92). ThyroSeq v1 and v2 (n=10) had a sensitivity of 0.86 (0.82-0.90), specificity of 0.74 (0.59-0.85), LR- of 0.19 (0.13-0.26), LR+ of 3.52 (2.08-5.92), and AUC of 0.86 (0.81-0.90). ThyroSeq v3 (n=6) had a sensitivity of 0.92 (0.86-0.95), specificity of 0.41 (0.18-0.69), LR- of 0.24 (0.09-0.62), LR+ of 1.67 (1.09-2.98), and AUC of 0.90 (0.63-0.92). 14% of studies conducted blinded histopathologic review of excised thyroid nodules, and 8% made the decision to go to surgery blind to molecular test results.
CONCLUSIONS: Meta-analyses reveal high diagnostic accuracy of molecular tests for thyroid nodule assessment of malignancy risk; however, these studies are subject to several limitations. Limitations and their potential clinical impacts must be addressed and, when feasible, adjusted for using valid statistical methodologies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: Molecular tests for thyroid nodules with indeterminate fine needle aspiration results are increasingly used in clinical practice; however, true diagnostic summaries of these tests are unknown. A systematic review and meta-analysis were completed to (1) evaluate the accuracy of commercially available molecular tests for malignancy in indeterminate thyroid nodules and (2) quantify biases and limitations in studies which validate those tests.
METHODS: PubMed, EMBASE, and Web of Science were systematically searched through July 2021. English language articles that reported original clinical validation attempts of molecular tests for indeterminate thyroid nodules were included if they reported counts of true negative, true positive, false negative, and false positive results. We performed screening and full text review, followed by assessment of eight common biases and limitations, extraction of diagnostic and histopathological information, and meta-analysis of clinical validity using a bivariate linear mixed-effects model.
RESULTS: 49 studies were included. Meta-analysis of Afirma GEC (n=38 studies) revealed a sensitivity of 0.92 (95% CI: 0.90-0.94), specificity of 0.26 (0.20-0.32), negative likelihood ratio (LR-) of 0.32 (0.23-0.44), positive likelihood ratio (LR+) of 1.24 (1.15-1.35), and AUC of 0.83 (0.74-0.89). Afirma GSC (n=10) had a sensitivity of 0.94 (0.89-0.96), specificity of 0.38 (0.27-0.50), LR- of 0.18 (0.10-0.30), LR+ of 1.52 (1.28-1.87), and AUC of 0.91 (0.62-0.92). ThyroSeq v1 and v2 (n=10) had a sensitivity of 0.86 (0.82-0.90), specificity of 0.74 (0.59-0.85), LR- of 0.19 (0.13-0.26), LR+ of 3.52 (2.08-5.92), and AUC of 0.86 (0.81-0.90). ThyroSeq v3 (n=6) had a sensitivity of 0.92 (0.86-0.95), specificity of 0.41 (0.18-0.69), LR- of 0.24 (0.09-0.62), LR+ of 1.67 (1.09-2.98), and AUC of 0.90 (0.63-0.92). 14% of studies conducted blinded histopathologic review of excised thyroid nodules, and 8% made the decision to go to surgery blind to molecular test results.
CONCLUSIONS: Meta-analyses reveal high diagnostic accuracy of molecular tests for thyroid nodule assessment of malignancy risk; however, these studies are subject to several limitations. Limitations and their potential clinical impacts must be addressed and, when feasible, adjusted for using valid statistical methodologies.
METHODS: PubMed, EMBASE, and Web of Science were systematically searched through July 2021. English language articles that reported original clinical validation attempts of molecular tests for indeterminate thyroid nodules were included if they reported counts of true negative, true positive, false negative, and false positive results. We performed screening and full text review, followed by assessment of eight common biases and limitations, extraction of diagnostic and histopathological information, and meta-analysis of clinical validity using a bivariate linear mixed-effects model.
RESULTS: 49 studies were included. Meta-analysis of Afirma GEC (n=38 studies) revealed a sensitivity of 0.92 (95% CI: 0.90-0.94), specificity of 0.26 (0.20-0.32), negative likelihood ratio (LR-) of 0.32 (0.23-0.44), positive likelihood ratio (LR+) of 1.24 (1.15-1.35), and AUC of 0.83 (0.74-0.89). Afirma GSC (n=10) had a sensitivity of 0.94 (0.89-0.96), specificity of 0.38 (0.27-0.50), LR- of 0.18 (0.10-0.30), LR+ of 1.52 (1.28-1.87), and AUC of 0.91 (0.62-0.92). ThyroSeq v1 and v2 (n=10) had a sensitivity of 0.86 (0.82-0.90), specificity of 0.74 (0.59-0.85), LR- of 0.19 (0.13-0.26), LR+ of 3.52 (2.08-5.92), and AUC of 0.86 (0.81-0.90). ThyroSeq v3 (n=6) had a sensitivity of 0.92 (0.86-0.95), specificity of 0.41 (0.18-0.69), LR- of 0.24 (0.09-0.62), LR+ of 1.67 (1.09-2.98), and AUC of 0.90 (0.63-0.92). 14% of studies conducted blinded histopathologic review of excised thyroid nodules, and 8% made the decision to go to surgery blind to molecular test results.
CONCLUSIONS: Meta-analyses reveal high diagnostic accuracy of molecular tests for thyroid nodule assessment of malignancy risk; however, these studies are subject to several limitations. Limitations and their potential clinical impacts must be addressed and, when feasible, adjusted for using valid statistical methodologies.
Peters, Mary Linton B.; Eckel, Andrew; Lietz, Anna; Seguin, Claudia; Mueller, Peter; Hur, Chin; Pandharipande, Pari V.
In: Pancreatology, vol. 22, iss. 6, pp. 760-769, 2022, ISSN: 1424-3903.
@article{PETERS2022,
title = {Genetic testing to guide screening for pancreatic ductal adenocarcinoma: Results of a microsimulation model},
author = {Mary Linton B. Peters and Andrew Eckel and Anna Lietz and Claudia Seguin and Peter Mueller and Chin Hur and Pari V. Pandharipande},
url = {https://www.sciencedirect.com/science/article/pii/S1424390322001703},
doi = {https://doi.org/10.1016/j.pan.2022.05.003},
issn = {1424-3903},
year = {2022},
date = {2022-09-22},
urldate = {2022-05-31},
journal = {Pancreatology},
volume = {22},
issue = {6},
pages = {760-769},
abstract = {Background
First-degree relatives (FDRs) of patients with pancreatic ductal adenocarcinoma (PDAC) have elevated PDAC risk, partially due to germline genetic variants. We evaluated the potential effectiveness of genetic testing to target MRI-based screening among FDRs.
Methods
We used a microsimulation model of PDAC, calibrated to Surveillance, Epidemiology, and End Results (SEER) data, to estimate the potential life expectancy (LE) gain of screening for each of the following groups of FDRs: indviduals who test positive for each of eight variants associated with elevated PDAC risk (e.g., BRCA2, CDKN2A); individuals who test negative; and individuals who do not test. Screening was assumed to take place if LE gains were achievable. We simulated multiple screening approaches, defined by starting age and frequency. Sensitivity analysis evaluated changes in results given varying model assumptions.
Results
For women, 92% of mutation carriers had projected LE gains from screening for PDAC, if screening strategies (start age, frequency) were optimized. Among carriers, LE gains ranged from 0.1 days (ATM + women screened once at age 70) to 510 days (STK11+ women screened annually from age 40). For men, LE gains were projected for all mutation carriers, ranging from 0.2 days (BRCA1+ men screened once at age 70) to 620 days (STK11+ men screened annually from age 40). For men and women who did not undergo genetic testing, or for whom testing showed no variant, screening yielded small LE benefit (0\textendash2.1 days).
Conclusions
Genetic testing of FDRs can inform targeted PDAC screening by identifying which FDRs may benefit.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Background
First-degree relatives (FDRs) of patients with pancreatic ductal adenocarcinoma (PDAC) have elevated PDAC risk, partially due to germline genetic variants. We evaluated the potential effectiveness of genetic testing to target MRI-based screening among FDRs.
Methods
We used a microsimulation model of PDAC, calibrated to Surveillance, Epidemiology, and End Results (SEER) data, to estimate the potential life expectancy (LE) gain of screening for each of the following groups of FDRs: indviduals who test positive for each of eight variants associated with elevated PDAC risk (e.g., BRCA2, CDKN2A); individuals who test negative; and individuals who do not test. Screening was assumed to take place if LE gains were achievable. We simulated multiple screening approaches, defined by starting age and frequency. Sensitivity analysis evaluated changes in results given varying model assumptions.
Results
For women, 92% of mutation carriers had projected LE gains from screening for PDAC, if screening strategies (start age, frequency) were optimized. Among carriers, LE gains ranged from 0.1 days (ATM + women screened once at age 70) to 510 days (STK11+ women screened annually from age 40). For men, LE gains were projected for all mutation carriers, ranging from 0.2 days (BRCA1+ men screened once at age 70) to 620 days (STK11+ men screened annually from age 40). For men and women who did not undergo genetic testing, or for whom testing showed no variant, screening yielded small LE benefit (0–2.1 days).
Conclusions
Genetic testing of FDRs can inform targeted PDAC screening by identifying which FDRs may benefit.
First-degree relatives (FDRs) of patients with pancreatic ductal adenocarcinoma (PDAC) have elevated PDAC risk, partially due to germline genetic variants. We evaluated the potential effectiveness of genetic testing to target MRI-based screening among FDRs.
Methods
We used a microsimulation model of PDAC, calibrated to Surveillance, Epidemiology, and End Results (SEER) data, to estimate the potential life expectancy (LE) gain of screening for each of the following groups of FDRs: indviduals who test positive for each of eight variants associated with elevated PDAC risk (e.g., BRCA2, CDKN2A); individuals who test negative; and individuals who do not test. Screening was assumed to take place if LE gains were achievable. We simulated multiple screening approaches, defined by starting age and frequency. Sensitivity analysis evaluated changes in results given varying model assumptions.
Results
For women, 92% of mutation carriers had projected LE gains from screening for PDAC, if screening strategies (start age, frequency) were optimized. Among carriers, LE gains ranged from 0.1 days (ATM + women screened once at age 70) to 510 days (STK11+ women screened annually from age 40). For men, LE gains were projected for all mutation carriers, ranging from 0.2 days (BRCA1+ men screened once at age 70) to 620 days (STK11+ men screened annually from age 40). For men and women who did not undergo genetic testing, or for whom testing showed no variant, screening yielded small LE benefit (0–2.1 days).
Conclusions
Genetic testing of FDRs can inform targeted PDAC screening by identifying which FDRs may benefit.
Singal, Amit G; Haaland, Benjamin; Parikh, Neehar D; Ozbay, A Burak; Kirshner, Carol; Chakankar, Shubham; Porter, Kyle; Chhatwal, Jagpreet; Ayer, Turgay
In: Hepatol Commun, 2022, ISSN: 2471-254X.
@article{pmid35945907,
title = {Comparison of a multitarget blood test to ultrasound and alpha-fetoprotein for hepatocellular carcinoma surveillance: Results of a network meta-analysis},
author = {Amit G Singal and Benjamin Haaland and Neehar D Parikh and A Burak Ozbay and Carol Kirshner and Shubham Chakankar and Kyle Porter and Jagpreet Chhatwal and Turgay Ayer},
doi = {10.1002/hep4.2045},
issn = {2471-254X},
year = {2022},
date = {2022-08-01},
journal = {Hepatol Commun},
abstract = {Ultrasound-based surveillance has suboptimal sensitivity for early detection of hepatocellular carcinoma (HCC) in patients with cirrhosis. There are several emerging alternatives, including a novel multitarget HCC blood test (Mt-HBT). We compared performance of mt-HBT against ultrasound with or without alpha-fetoprotein (AFP) for early HCC detection in patients with cirrhosis. Per the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, two reviewers searched PubMed, Cochrane, Embase, and clinicaltrials.gov databases from January 1990 through December 2020 to identify studies reporting sensitivity and/or specificity of ultrasound and AFP for overall and early stage HCC detection in patients with cirrhosis. Mt-HBT diagnostic performance was derived from a clinical validation study. A network meta-analysis model was built for comparative assessment, and pooled estimates of sensitivity at a fixed specificity were estimated based on Bayesian binormal receiver operating characteristic models for each modality. Forty-one studies (comprising 62,517 patients with cirrhosis) met inclusion criteria. Ultrasound-alone sensitivity was 51.6% (95% credible interval [CrI], 43.3%-60.5%) for early stage HCC detection, which increased with the addition of AFP to 74.1% (95% CrI, 62.6%-82.4%); however, this was offset by decreased specificity (87.9% vs. 83.9%, respectively). With specificity fixed at 90%, mt-HBT sensitivity for early stage HCC detection was higher than ultrasound alone (18.2%; 95% CrI, 0.2%-37.7%) and similar to ultrasound with AFP (-3.3%; 95% CrI, -22.3%-17.4%). Pairwise posterior probabilities suggested a preference for mt-HBT over ultrasound alone in 97.4% of cases but only 36.3% of cases versus ultrasound with AFP. Conclusion: A blood-based mt-HBT has higher sensitivity than ultrasound alone for early stage HCC detection but similar sensitivity compared to ultrasound and AFP. Mt-HBT could be a comparable alternative to existing methods for HCC surveillance in patients who are at risk.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Ultrasound-based surveillance has suboptimal sensitivity for early detection of hepatocellular carcinoma (HCC) in patients with cirrhosis. There are several emerging alternatives, including a novel multitarget HCC blood test (Mt-HBT). We compared performance of mt-HBT against ultrasound with or without alpha-fetoprotein (AFP) for early HCC detection in patients with cirrhosis. Per the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, two reviewers searched PubMed, Cochrane, Embase, and clinicaltrials.gov databases from January 1990 through December 2020 to identify studies reporting sensitivity and/or specificity of ultrasound and AFP for overall and early stage HCC detection in patients with cirrhosis. Mt-HBT diagnostic performance was derived from a clinical validation study. A network meta-analysis model was built for comparative assessment, and pooled estimates of sensitivity at a fixed specificity were estimated based on Bayesian binormal receiver operating characteristic models for each modality. Forty-one studies (comprising 62,517 patients with cirrhosis) met inclusion criteria. Ultrasound-alone sensitivity was 51.6% (95% credible interval [CrI], 43.3%-60.5%) for early stage HCC detection, which increased with the addition of AFP to 74.1% (95% CrI, 62.6%-82.4%); however, this was offset by decreased specificity (87.9% vs. 83.9%, respectively). With specificity fixed at 90%, mt-HBT sensitivity for early stage HCC detection was higher than ultrasound alone (18.2%; 95% CrI, 0.2%-37.7%) and similar to ultrasound with AFP (-3.3%; 95% CrI, -22.3%-17.4%). Pairwise posterior probabilities suggested a preference for mt-HBT over ultrasound alone in 97.4% of cases but only 36.3% of cases versus ultrasound with AFP. Conclusion: A blood-based mt-HBT has higher sensitivity than ultrasound alone for early stage HCC detection but similar sensitivity compared to ultrasound and AFP. Mt-HBT could be a comparable alternative to existing methods for HCC surveillance in patients who are at risk.
Rajakumar, Timothy; Horos, Rastislav; Kittner, Paul; Kahraman, Mustafa; Sikosek, Tobias; Hinkfoth, Franziska; Tikk, Kaja; Mercaldo, Nathaniel D; Stenzinger, Albrecht; Rabe, Klaus F; Reck, Martin; Thomas, Michael; Christopoulos, Petros; Steinkraus, Bruno R
In: JTO Clin Res Rep, vol. 3, no. 8, pp. 100369, 2022, ISSN: 2666-3643.
@article{pmid35880086,
title = {Brief Report: A Blood-Based MicroRNA Complementary Diagnostic Predicts Immunotherapy Efficacy in Advanced-Stage NSCLC With High Programmed Death-Ligand 1 Expression},
author = {Timothy Rajakumar and Rastislav Horos and Paul Kittner and Mustafa Kahraman and Tobias Sikosek and Franziska Hinkfoth and Kaja Tikk and Nathaniel D Mercaldo and Albrecht Stenzinger and Klaus F Rabe and Martin Reck and Michael Thomas and Petros Christopoulos and Bruno R Steinkraus},
doi = {10.1016/j.jtocrr.2022.100369},
issn = {2666-3643},
year = {2022},
date = {2022-08-01},
urldate = {2022-08-01},
journal = {JTO Clin Res Rep},
volume = {3},
number = {8},
pages = {100369},
abstract = {Introduction: Patients with advanced, non-oncogene-driven NSCLC with high programmed death-ligand 1 (PD-L1) expression are eligible for treatment with immunotherapy. There is, however, an urgent medical need for biomarkers identifying cases that require additional combination with chemotherapy. We previously uncovered a myeloid-based 5-microRNA (5-miRNA) signature that identified responders to immunotherapy in PD-L1 unstratified patients; however, its potential utility in treatment guidance for patients with PD-L1 high tumors remained unclear.
Methods: We trained (n = 68) and validated (n = 56) a 5-miRNA multivariable Cox proportional hazards model predictive of overall survival on small RNA sequencing data of whole blood samples prospectively collected before the commencement of immunotherapy for stage IV NSCLC with PD-L1 tumor proportion score greater than or equal to 50%, treated with PD-1 inhibitor monotherapy (immunotherapy alone [IO]). Specificity was demonstrated in a control cohort treated with immunochemotherapy (ICT) (n = 31).
Results: The revised 5-miRNA risk score (miRisk) stratified IO-treated patients and identified a high-risk group with significantly shorter overall survival (hazard ratio = 5.24, 95% confidence interval: 2.17-12.66, < 0.001). There was a significant interaction between the miRisk score and type of treatment (IO or ICT, = 0.036), indicating that the miRisk score may serve as a predictive biomarker for immunotherapy response. Furthermore, the miRisk score could identify a group of high-risk patients who may benefit from treatment with ICT as opposed to IO (hazard ratio = 0.35, 95% confidence interval: 0.15-0.82, = 0.018).
Conclusions: The miRisk score can distinguish a group of patients with PD-L1 high, stage IV NSCLC likely to benefit from adding chemotherapy to immunotherapy and may support treatment decisions as a blood-based complementary diagnostic.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Introduction: Patients with advanced, non-oncogene-driven NSCLC with high programmed death-ligand 1 (PD-L1) expression are eligible for treatment with immunotherapy. There is, however, an urgent medical need for biomarkers identifying cases that require additional combination with chemotherapy. We previously uncovered a myeloid-based 5-microRNA (5-miRNA) signature that identified responders to immunotherapy in PD-L1 unstratified patients; however, its potential utility in treatment guidance for patients with PD-L1 high tumors remained unclear.
Methods: We trained (n = 68) and validated (n = 56) a 5-miRNA multivariable Cox proportional hazards model predictive of overall survival on small RNA sequencing data of whole blood samples prospectively collected before the commencement of immunotherapy for stage IV NSCLC with PD-L1 tumor proportion score greater than or equal to 50%, treated with PD-1 inhibitor monotherapy (immunotherapy alone [IO]). Specificity was demonstrated in a control cohort treated with immunochemotherapy (ICT) (n = 31).
Results: The revised 5-miRNA risk score (miRisk) stratified IO-treated patients and identified a high-risk group with significantly shorter overall survival (hazard ratio = 5.24, 95% confidence interval: 2.17-12.66, < 0.001). There was a significant interaction between the miRisk score and type of treatment (IO or ICT, = 0.036), indicating that the miRisk score may serve as a predictive biomarker for immunotherapy response. Furthermore, the miRisk score could identify a group of high-risk patients who may benefit from treatment with ICT as opposed to IO (hazard ratio = 0.35, 95% confidence interval: 0.15-0.82, = 0.018).
Conclusions: The miRisk score can distinguish a group of patients with PD-L1 high, stage IV NSCLC likely to benefit from adding chemotherapy to immunotherapy and may support treatment decisions as a blood-based complementary diagnostic.
Methods: We trained (n = 68) and validated (n = 56) a 5-miRNA multivariable Cox proportional hazards model predictive of overall survival on small RNA sequencing data of whole blood samples prospectively collected before the commencement of immunotherapy for stage IV NSCLC with PD-L1 tumor proportion score greater than or equal to 50%, treated with PD-1 inhibitor monotherapy (immunotherapy alone [IO]). Specificity was demonstrated in a control cohort treated with immunochemotherapy (ICT) (n = 31).
Results: The revised 5-miRNA risk score (miRisk) stratified IO-treated patients and identified a high-risk group with significantly shorter overall survival (hazard ratio = 5.24, 95% confidence interval: 2.17-12.66, < 0.001). There was a significant interaction between the miRisk score and type of treatment (IO or ICT, = 0.036), indicating that the miRisk score may serve as a predictive biomarker for immunotherapy response. Furthermore, the miRisk score could identify a group of high-risk patients who may benefit from treatment with ICT as opposed to IO (hazard ratio = 0.35, 95% confidence interval: 0.15-0.82, = 0.018).
Conclusions: The miRisk score can distinguish a group of patients with PD-L1 high, stage IV NSCLC likely to benefit from adding chemotherapy to immunotherapy and may support treatment decisions as a blood-based complementary diagnostic.
Jahn, Beate; Santamaria, Júlia; Dieplinger, Hans; Binder, Christoph J; Ebenbichler, Christoph; Scholl-Bürgi, Sabine; Conrads-Frank, Annette; Rochau, Ursula; Kühne, Felicitas; Stojkov, Igor; Todorovic, Jovan; James, Lyndon; Siebert, Uwe
Familial hypercholesterolemia: A systematic review of modeling studies on screening interventions Journal Article
In: Atherosclerosis, vol. 355, pp. 15–29, 2022, ISSN: 1879-1484.
@article{pmid35870306,
title = {Familial hypercholesterolemia: A systematic review of modeling studies on screening interventions},
author = {Beate Jahn and J\'{u}lia Santamaria and Hans Dieplinger and Christoph J Binder and Christoph Ebenbichler and Sabine Scholl-B\"{u}rgi and Annette Conrads-Frank and Ursula Rochau and Felicitas K\"{u}hne and Igor Stojkov and Jovan Todorovic and Lyndon James and Uwe Siebert},
doi = {10.1016/j.atherosclerosis.2022.06.1011},
issn = {1879-1484},
year = {2022},
date = {2022-08-01},
urldate = {2022-06-01},
journal = {Atherosclerosis},
volume = {355},
pages = {15--29},
abstract = {BACKGROUND AND AIMS: FH is still underdiagnosed. Cost-effectiveness results of preventive screening strategies vary. We aimed at systematically assessing the benefits, harms and cost effectiveness of screening for familial hypercholesterolemia (FH) and at providing an overview of the main characteristics and methodological approaches of applied decision-analytic models.
METHODS: A systematic literature search was conducted in MEDLINE, EconLit, CRD-databases and the CEA-registry for FH screening starting 2012. Earlier studies were included from a published systematic review. Results were reported in standardized semi-quantitative evidence tables. Costs were converted to current euros. Incremental cost-effectiveness ratios (ICERs) were recalculated according to economic guidelines.
RESULTS: Out of our 211 retrieved studies, eight were included in the review in addition to six studies from an earlier review. Studies were conducted in Europe (UK, The Netherlands, Spain, Poland), USA and Australia evaluating cascade (CS), opportunistic (OS), universal screening (UniS), or combinations using genetic testing, clinical criteria or combinations. Studies evaluating only CS identified strategies with an ICER of up to 37,100 EUR/quality-adjusted life-year (QALY) but some strategies were dominated depending on test combinations. UniS of newborns in combination with CS had an ICER≤15,000 EUR/QALY for sequential cholesterol-genetic screening. In other studies, UniS was dominated by OS/CS.
CONCLUSIONS: Our systematic review demonstrates the values of FH screening and provides an overview of potentially relevant screening strategies to be tested using a decision-analytic model for the respective country or region. Future research is needed on the transferability of results to other countries and modeling spillover effects to newborns.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND AND AIMS: FH is still underdiagnosed. Cost-effectiveness results of preventive screening strategies vary. We aimed at systematically assessing the benefits, harms and cost effectiveness of screening for familial hypercholesterolemia (FH) and at providing an overview of the main characteristics and methodological approaches of applied decision-analytic models.
METHODS: A systematic literature search was conducted in MEDLINE, EconLit, CRD-databases and the CEA-registry for FH screening starting 2012. Earlier studies were included from a published systematic review. Results were reported in standardized semi-quantitative evidence tables. Costs were converted to current euros. Incremental cost-effectiveness ratios (ICERs) were recalculated according to economic guidelines.
RESULTS: Out of our 211 retrieved studies, eight were included in the review in addition to six studies from an earlier review. Studies were conducted in Europe (UK, The Netherlands, Spain, Poland), USA and Australia evaluating cascade (CS), opportunistic (OS), universal screening (UniS), or combinations using genetic testing, clinical criteria or combinations. Studies evaluating only CS identified strategies with an ICER of up to 37,100 EUR/quality-adjusted life-year (QALY) but some strategies were dominated depending on test combinations. UniS of newborns in combination with CS had an ICER≤15,000 EUR/QALY for sequential cholesterol-genetic screening. In other studies, UniS was dominated by OS/CS.
CONCLUSIONS: Our systematic review demonstrates the values of FH screening and provides an overview of potentially relevant screening strategies to be tested using a decision-analytic model for the respective country or region. Future research is needed on the transferability of results to other countries and modeling spillover effects to newborns.
METHODS: A systematic literature search was conducted in MEDLINE, EconLit, CRD-databases and the CEA-registry for FH screening starting 2012. Earlier studies were included from a published systematic review. Results were reported in standardized semi-quantitative evidence tables. Costs were converted to current euros. Incremental cost-effectiveness ratios (ICERs) were recalculated according to economic guidelines.
RESULTS: Out of our 211 retrieved studies, eight were included in the review in addition to six studies from an earlier review. Studies were conducted in Europe (UK, The Netherlands, Spain, Poland), USA and Australia evaluating cascade (CS), opportunistic (OS), universal screening (UniS), or combinations using genetic testing, clinical criteria or combinations. Studies evaluating only CS identified strategies with an ICER of up to 37,100 EUR/quality-adjusted life-year (QALY) but some strategies were dominated depending on test combinations. UniS of newborns in combination with CS had an ICER≤15,000 EUR/QALY for sequential cholesterol-genetic screening. In other studies, UniS was dominated by OS/CS.
CONCLUSIONS: Our systematic review demonstrates the values of FH screening and provides an overview of potentially relevant screening strategies to be tested using a decision-analytic model for the respective country or region. Future research is needed on the transferability of results to other countries and modeling spillover effects to newborns.
Stafford, Celia; Marrero, Wesley J; Naumann, Rebecca B; Lich, Kristen Hassmiller; Wakeman, Sarah; Jalali, Mohammad S
Identifying key risk factors for premature discontinuation of opioid use disorder treatment in the United States: A predictive modeling study Journal Article
In: Drug Alcohol Depend, vol. 237, pp. 109507, 2022, ISSN: 1879-0046.
@article{pmid35660221,
title = {Identifying key risk factors for premature discontinuation of opioid use disorder treatment in the United States: A predictive modeling study},
author = {Celia Stafford and Wesley J Marrero and Rebecca B Naumann and Kristen Hassmiller Lich and Sarah Wakeman and Mohammad S Jalali},
doi = {10.1016/j.drugalcdep.2022.109507},
issn = {1879-0046},
year = {2022},
date = {2022-08-01},
urldate = {2022-05-01},
journal = {Drug Alcohol Depend},
volume = {237},
pages = {109507},
abstract = {BACKGROUND: Treatment for opioid use disorder (OUD), particularly medication for OUD, is highly effective; however, retention in OUD treatment is a significant challenge. We aimed to identify key risk factors for premature exit from OUD treatment.
METHODS: We analyzed 2,381,902 cross-sectional treatment episodes for individuals in the U.S., discharged between Jan/1/2015 and Dec/31/2019. We developed classification models (Random Forest, Classification and Regression Trees (CART), Bagged CART, and Boosted CART), and analyzed 31 potential risk factors for premature treatment exit, including treatment characteristics, substance use history, socioeconomic status, and demographic characteristics. We stratified our analysis based on length of stay in treatment and service setting. Models were compared using cross-validation and the receiver operating characteristic area under the curve (ROC-AUC).
RESULTS: Random Forest outperformed other methods (ROC-AUC: 74%). The most influential risk factors included characteristics of service setting, geographic region, primary source of payment, and referral source. Race, ethnicity, and sex had far weaker predictive impacts. When stratified by treatment setting and length of stay, employment status and delay (days waited) to enter treatment were among the most influential factors. Their importance increased as treatment duration decreased. Notably, importance of referral source increased as the treatment duration increased. Finally, age and age of first use were important factors for lengths of stay of 2-7 days and in detox treatment settings.
CONCLUSIONS: The key factors of OUD treatment attrition identified in this analysis should be more closely explored (e.g., in causal studies) to inform targeted policies and interventions to improve models of care.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: Treatment for opioid use disorder (OUD), particularly medication for OUD, is highly effective; however, retention in OUD treatment is a significant challenge. We aimed to identify key risk factors for premature exit from OUD treatment.
METHODS: We analyzed 2,381,902 cross-sectional treatment episodes for individuals in the U.S., discharged between Jan/1/2015 and Dec/31/2019. We developed classification models (Random Forest, Classification and Regression Trees (CART), Bagged CART, and Boosted CART), and analyzed 31 potential risk factors for premature treatment exit, including treatment characteristics, substance use history, socioeconomic status, and demographic characteristics. We stratified our analysis based on length of stay in treatment and service setting. Models were compared using cross-validation and the receiver operating characteristic area under the curve (ROC-AUC).
RESULTS: Random Forest outperformed other methods (ROC-AUC: 74%). The most influential risk factors included characteristics of service setting, geographic region, primary source of payment, and referral source. Race, ethnicity, and sex had far weaker predictive impacts. When stratified by treatment setting and length of stay, employment status and delay (days waited) to enter treatment were among the most influential factors. Their importance increased as treatment duration decreased. Notably, importance of referral source increased as the treatment duration increased. Finally, age and age of first use were important factors for lengths of stay of 2-7 days and in detox treatment settings.
CONCLUSIONS: The key factors of OUD treatment attrition identified in this analysis should be more closely explored (e.g., in causal studies) to inform targeted policies and interventions to improve models of care.
METHODS: We analyzed 2,381,902 cross-sectional treatment episodes for individuals in the U.S., discharged between Jan/1/2015 and Dec/31/2019. We developed classification models (Random Forest, Classification and Regression Trees (CART), Bagged CART, and Boosted CART), and analyzed 31 potential risk factors for premature treatment exit, including treatment characteristics, substance use history, socioeconomic status, and demographic characteristics. We stratified our analysis based on length of stay in treatment and service setting. Models were compared using cross-validation and the receiver operating characteristic area under the curve (ROC-AUC).
RESULTS: Random Forest outperformed other methods (ROC-AUC: 74%). The most influential risk factors included characteristics of service setting, geographic region, primary source of payment, and referral source. Race, ethnicity, and sex had far weaker predictive impacts. When stratified by treatment setting and length of stay, employment status and delay (days waited) to enter treatment were among the most influential factors. Their importance increased as treatment duration decreased. Notably, importance of referral source increased as the treatment duration increased. Finally, age and age of first use were important factors for lengths of stay of 2-7 days and in detox treatment settings.
CONCLUSIONS: The key factors of OUD treatment attrition identified in this analysis should be more closely explored (e.g., in causal studies) to inform targeted policies and interventions to improve models of care.
Beaulieu, Elizabeth; Naumann, Rebecca B; Deveaux, Genevieve; Wang, Lindsay; Stringfellow, Erin J; Lich, Kristen Hassmiller; Jalali, Mohammad S
Impacts of alcohol and opioid polysubstance use on road safety: Systematic review Journal Article
In: Accid Anal Prev, vol. 173, pp. 106713, 2022, ISSN: 1879-2057.
@article{pmid35640366,
title = {Impacts of alcohol and opioid polysubstance use on road safety: Systematic review},
author = {Elizabeth Beaulieu and Rebecca B Naumann and Genevieve Deveaux and Lindsay Wang and Erin J Stringfellow and Kristen Hassmiller Lich and Mohammad S Jalali},
doi = {10.1016/j.aap.2022.106713},
issn = {1879-2057},
year = {2022},
date = {2022-08-01},
urldate = {2022-05-01},
journal = {Accid Anal Prev},
volume = {173},
pages = {106713},
abstract = {Connections between substance use, impairment, and road safety have been frequently researched. Yet, little is known about how simultaneous use of opioids and alcohol affects road safety outcomes, which is an increasingly critical link within the current landscape of the substance use environment and public health. Lack of this understanding is partly due to testing complications and data limitations. We define polysubstance use here as alcohol and opioids consumed together or within a small-time window such that both are present in the system. This polysubstance use is on the rise and produces greater health risks than when the substances are consumed separately. Given the increasing rate of opioid use, high prevalence of alcohol use, and dangers of polysubstance use, we aim to synthesize literature on the prevalence and impact of this polysubstance on road safety-related outcomes. We performed a systematic review of studies published between 1974 and 2020 that examined opioid and alcohol use exposures and road safety-related outcomes. Out of 644 initial findings, 20 studies were included in this review. Outcomes included motor vehicle crash injuries, deaths, or driver culpability; suspected driving under the influence; and simulated driving performance. Evidence from multiple sources showed a significant rise, approximately 1% to 7%, in the prevalence of opioids among fatally injured drivers in the U.S. from 1995 to 2016. Information published on the simultaneous presence of opioids and alcohol in people involved in crashes was scarce. The limited available findings point toward an overlap where up to 30% of opioid-positive people involved in a crash were also positive for alcohol. Studies also suggest a possibly elevated risk presented by this polysubstance use relative to the substances used alone, though the majority of identified studies did not estimate this association. The synthesized research indicates that alcohol and opioid use is not uncommon and may be increasing among people involved in adverse driving events. More research and better data are needed to improve estimates of association with road traffic-related outcomes, potentially improving substance testing in current surveillance systems or using linked data sets and other novel data sources to improve estimates.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Connections between substance use, impairment, and road safety have been frequently researched. Yet, little is known about how simultaneous use of opioids and alcohol affects road safety outcomes, which is an increasingly critical link within the current landscape of the substance use environment and public health. Lack of this understanding is partly due to testing complications and data limitations. We define polysubstance use here as alcohol and opioids consumed together or within a small-time window such that both are present in the system. This polysubstance use is on the rise and produces greater health risks than when the substances are consumed separately. Given the increasing rate of opioid use, high prevalence of alcohol use, and dangers of polysubstance use, we aim to synthesize literature on the prevalence and impact of this polysubstance on road safety-related outcomes. We performed a systematic review of studies published between 1974 and 2020 that examined opioid and alcohol use exposures and road safety-related outcomes. Out of 644 initial findings, 20 studies were included in this review. Outcomes included motor vehicle crash injuries, deaths, or driver culpability; suspected driving under the influence; and simulated driving performance. Evidence from multiple sources showed a significant rise, approximately 1% to 7%, in the prevalence of opioids among fatally injured drivers in the U.S. from 1995 to 2016. Information published on the simultaneous presence of opioids and alcohol in people involved in crashes was scarce. The limited available findings point toward an overlap where up to 30% of opioid-positive people involved in a crash were also positive for alcohol. Studies also suggest a possibly elevated risk presented by this polysubstance use relative to the substances used alone, though the majority of identified studies did not estimate this association. The synthesized research indicates that alcohol and opioid use is not uncommon and may be increasing among people involved in adverse driving events. More research and better data are needed to improve estimates of association with road traffic-related outcomes, potentially improving substance testing in current surveillance systems or using linked data sets and other novel data sources to improve estimates.
Weiner, Scott G; Carroll, Aleta D; Brisbon, Nicholas M; Rodriguez, Claudia P; Covahey, Charles; Stringfellow, Erin J; DiGennaro, Catherine; Jalali, Mohammad S; Wakeman, Sarah E
Evaluating disparities in prescribing of naloxone after emergency department treatment of opioid overdose Journal Article
In: J Subst Abuse Treat, vol. 139, pp. 108785, 2022, ISSN: 1873-6483.
@article{pmid35537918,
title = {Evaluating disparities in prescribing of naloxone after emergency department treatment of opioid overdose},
author = {Scott G Weiner and Aleta D Carroll and Nicholas M Brisbon and Claudia P Rodriguez and Charles Covahey and Erin J Stringfellow and Catherine DiGennaro and Mohammad S Jalali and Sarah E Wakeman},
doi = {10.1016/j.jsat.2022.108785},
issn = {1873-6483},
year = {2022},
date = {2022-08-01},
urldate = {2022-04-01},
journal = {J Subst Abuse Treat},
volume = {139},
pages = {108785},
abstract = {INTRODUCTION: Patients who initially survive opioid-related overdose are at high risk for subsequent mortality. Our health system aimed to evaluate the presence of disparities in prescribing naloxone following opioid overdose.
METHODS: This was a retrospective cohort study of patients seen in our health system, which comprises two academic centers and eight community hospitals. Eligible patients had at least one visit to any of our hospital's emergency departments (EDs) with a diagnosis code indicating opioid-related overdose between May 1, 2018, and April 30, 2021. The primary outcome measure was prescription of nasal naloxone after at least one visit for opioid-related overdose during the study period.
RESULTS: The health system had 1348 unique patients who presented 1593 times to at least one of the EDs with opioid overdose. Of included patients, 580 (43.2%) received one or more prescriptions for naloxone. The majority (68.9%, n = 925) were male. For race/ethnicity, 74.5% (1000) were Non-Hispanic White, 8.0% (n = 108) were Non-Hispanic Black, and 13.0% (n = 175) were Hispanic/Latinx. Compared with the reference age group of 16-24 years, only those 65+ were less likely to receive naloxone (adjusted odds ratio [aOR] 0.41, 95% confidence interval [CI] 0.20-0.84). The study found no difference for gender (male aOR 1.23, 95% CI 0.97-1.57 compared to female). Hispanic/Latinx patients were more likely to receive a prescription when compared to Non-Hispanic White patients (aOR 1.72, 95% CI 1.22-2.44), while no difference occurred between Non-Hispanic Black compared to Non-Hispanic White patients (aOR 1.31, 95% CI 0.87-1.98).
CONCLUSIONS: Naloxone prescribing after overdose in our system was suboptimal, with fewer than half of patients with an overdose diagnosis code receiving this lifesaving and evidence-based intervention. Patients who were Hispanic/Latinx were more likely to receive naloxone than other race and ethnicity groups, and patients who were older were less likely to receive it. Health systems need ongoing equity-informed implementation of programs to expand access to naloxone to all patients at risk.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
INTRODUCTION: Patients who initially survive opioid-related overdose are at high risk for subsequent mortality. Our health system aimed to evaluate the presence of disparities in prescribing naloxone following opioid overdose.
METHODS: This was a retrospective cohort study of patients seen in our health system, which comprises two academic centers and eight community hospitals. Eligible patients had at least one visit to any of our hospital's emergency departments (EDs) with a diagnosis code indicating opioid-related overdose between May 1, 2018, and April 30, 2021. The primary outcome measure was prescription of nasal naloxone after at least one visit for opioid-related overdose during the study period.
RESULTS: The health system had 1348 unique patients who presented 1593 times to at least one of the EDs with opioid overdose. Of included patients, 580 (43.2%) received one or more prescriptions for naloxone. The majority (68.9%, n = 925) were male. For race/ethnicity, 74.5% (1000) were Non-Hispanic White, 8.0% (n = 108) were Non-Hispanic Black, and 13.0% (n = 175) were Hispanic/Latinx. Compared with the reference age group of 16-24 years, only those 65+ were less likely to receive naloxone (adjusted odds ratio [aOR] 0.41, 95% confidence interval [CI] 0.20-0.84). The study found no difference for gender (male aOR 1.23, 95% CI 0.97-1.57 compared to female). Hispanic/Latinx patients were more likely to receive a prescription when compared to Non-Hispanic White patients (aOR 1.72, 95% CI 1.22-2.44), while no difference occurred between Non-Hispanic Black compared to Non-Hispanic White patients (aOR 1.31, 95% CI 0.87-1.98).
CONCLUSIONS: Naloxone prescribing after overdose in our system was suboptimal, with fewer than half of patients with an overdose diagnosis code receiving this lifesaving and evidence-based intervention. Patients who were Hispanic/Latinx were more likely to receive naloxone than other race and ethnicity groups, and patients who were older were less likely to receive it. Health systems need ongoing equity-informed implementation of programs to expand access to naloxone to all patients at risk.
METHODS: This was a retrospective cohort study of patients seen in our health system, which comprises two academic centers and eight community hospitals. Eligible patients had at least one visit to any of our hospital's emergency departments (EDs) with a diagnosis code indicating opioid-related overdose between May 1, 2018, and April 30, 2021. The primary outcome measure was prescription of nasal naloxone after at least one visit for opioid-related overdose during the study period.
RESULTS: The health system had 1348 unique patients who presented 1593 times to at least one of the EDs with opioid overdose. Of included patients, 580 (43.2%) received one or more prescriptions for naloxone. The majority (68.9%, n = 925) were male. For race/ethnicity, 74.5% (1000) were Non-Hispanic White, 8.0% (n = 108) were Non-Hispanic Black, and 13.0% (n = 175) were Hispanic/Latinx. Compared with the reference age group of 16-24 years, only those 65+ were less likely to receive naloxone (adjusted odds ratio [aOR] 0.41, 95% confidence interval [CI] 0.20-0.84). The study found no difference for gender (male aOR 1.23, 95% CI 0.97-1.57 compared to female). Hispanic/Latinx patients were more likely to receive a prescription when compared to Non-Hispanic White patients (aOR 1.72, 95% CI 1.22-2.44), while no difference occurred between Non-Hispanic Black compared to Non-Hispanic White patients (aOR 1.31, 95% CI 0.87-1.98).
CONCLUSIONS: Naloxone prescribing after overdose in our system was suboptimal, with fewer than half of patients with an overdose diagnosis code receiving this lifesaving and evidence-based intervention. Patients who were Hispanic/Latinx were more likely to receive naloxone than other race and ethnicity groups, and patients who were older were less likely to receive it. Health systems need ongoing equity-informed implementation of programs to expand access to naloxone to all patients at risk.
Beaulieu, Elizabeth; Spanjaart, Anne; Roes, Ashley; Rachet, Bernard; Dalle, Stéphane; Kersten, Marie José; Maucort-Boulch, Delphine; Jalali, Mohammad S
Health-related quality of life in cancer immunotherapy: a systematic perspective, using causal loop diagrams Journal Article
In: Qual Life Res, vol. 31, iss. 8, pp. 2357-2366, 2022, ISSN: 1573-2649.
@article{pmid35298735,
title = {Health-related quality of life in cancer immunotherapy: a systematic perspective, using causal loop diagrams},
author = {Elizabeth Beaulieu and Anne Spanjaart and Ashley Roes and Bernard Rachet and St\'{e}phane Dalle and Marie Jos\'{e} Kersten and Delphine Maucort-Boulch and Mohammad S Jalali},
doi = {10.1007/s11136-022-03110-5},
issn = {1573-2649},
year = {2022},
date = {2022-08-01},
urldate = {2022-03-01},
journal = {Qual Life Res},
volume = {31},
issue = {8},
pages = {2357-2366},
abstract = {PURPOSE: System science offers a unique set of tools, including causal loop diagrams (CLDs), for stakeholders to better grasp the complexity of factors surrounding quality of life. Because the health-related quality of life (HRQoL) of cancer immunotherapy patients exists within an intricate system affected by and affecting many factors across multiple dimensions, the development of a systems-level model can provide a powerful framework to aid the understanding of this complexity. We developed a CLD for HRQoL of cancer immunotherapy patients.
METHODS: We first applied a literature-based approach to construct a CLD for patients following immunotherapy. We then iteratively reviewed and enhanced the CLD through interviews with subject matter experts.
RESULTS: Based on the reviewed literature and subject matter expert input, we produced a CLD representing the system surrounding cancer immunotherapy patients' HRQoL. Several feedback loops are identified that span clinical experiences, oncology teams' perceptions about immunotherapy, social support structures, and further research and development in cancer immunotherapy, in addition to other components. The CLD enables visualization of thought experiments regarding how a change anywhere in the system can ultimately worsen or improve patients' HRQoL.
CONCLUSION: The CLD illustrates the valuable contribution of a systems perspective to quality-of-life research. This systems-based qualitative representation gives insight on strategies to inhibit harmful effects, enhance beneficial effects, and inherent tradeoffs within the system. The CLD identifies gaps in the literature and offers a communication tool for diverse stakeholders. Our research method provides an example for studying the complexities of quality of life in other health domains.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: System science offers a unique set of tools, including causal loop diagrams (CLDs), for stakeholders to better grasp the complexity of factors surrounding quality of life. Because the health-related quality of life (HRQoL) of cancer immunotherapy patients exists within an intricate system affected by and affecting many factors across multiple dimensions, the development of a systems-level model can provide a powerful framework to aid the understanding of this complexity. We developed a CLD for HRQoL of cancer immunotherapy patients.
METHODS: We first applied a literature-based approach to construct a CLD for patients following immunotherapy. We then iteratively reviewed and enhanced the CLD through interviews with subject matter experts.
RESULTS: Based on the reviewed literature and subject matter expert input, we produced a CLD representing the system surrounding cancer immunotherapy patients' HRQoL. Several feedback loops are identified that span clinical experiences, oncology teams' perceptions about immunotherapy, social support structures, and further research and development in cancer immunotherapy, in addition to other components. The CLD enables visualization of thought experiments regarding how a change anywhere in the system can ultimately worsen or improve patients' HRQoL.
CONCLUSION: The CLD illustrates the valuable contribution of a systems perspective to quality-of-life research. This systems-based qualitative representation gives insight on strategies to inhibit harmful effects, enhance beneficial effects, and inherent tradeoffs within the system. The CLD identifies gaps in the literature and offers a communication tool for diverse stakeholders. Our research method provides an example for studying the complexities of quality of life in other health domains.
METHODS: We first applied a literature-based approach to construct a CLD for patients following immunotherapy. We then iteratively reviewed and enhanced the CLD through interviews with subject matter experts.
RESULTS: Based on the reviewed literature and subject matter expert input, we produced a CLD representing the system surrounding cancer immunotherapy patients' HRQoL. Several feedback loops are identified that span clinical experiences, oncology teams' perceptions about immunotherapy, social support structures, and further research and development in cancer immunotherapy, in addition to other components. The CLD enables visualization of thought experiments regarding how a change anywhere in the system can ultimately worsen or improve patients' HRQoL.
CONCLUSION: The CLD illustrates the valuable contribution of a systems perspective to quality-of-life research. This systems-based qualitative representation gives insight on strategies to inhibit harmful effects, enhance beneficial effects, and inherent tradeoffs within the system. The CLD identifies gaps in the literature and offers a communication tool for diverse stakeholders. Our research method provides an example for studying the complexities of quality of life in other health domains.
Jahn, Beate; Friedrich, Sarah; Behnke, Joachim; Engel, Joachim; Garczarek, Ursula; Münnich, Ralf; Pauly, Markus; Wilhelm, Adalbert; Wolkenhauer, Olaf; Zwick, Markus; Siebert, Uwe; Friede, Tim
Authors' response: on the role of data, statistics and decisions in a pandemic Journal Article
In: Adv Stat Anal, pp. 1–3, 2022, ISSN: 1863-8171.
@article{pmid35967605,
title = {Authors' response: on the role of data, statistics and decisions in a pandemic},
author = {Beate Jahn and Sarah Friedrich and Joachim Behnke and Joachim Engel and Ursula Garczarek and Ralf M\"{u}nnich and Markus Pauly and Adalbert Wilhelm and Olaf Wolkenhauer and Markus Zwick and Uwe Siebert and Tim Friede},
doi = {10.1007/s10182-022-00460-w},
issn = {1863-8171},
year = {2022},
date = {2022-07-01},
journal = {Adv Stat Anal},
pages = {1--3},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Deutsch, Arielle R; Jalali, Mohammad S; Stout, Sarah; Frerichs, Leah
Equitable Policies Need Equitable Practices: Alcohol- and Substance-Exposed Pregnancy as a Case Study Journal Article
In: Health Promot Pract, pp. 15248399221107605, 2022, ISSN: 1524-8399.
@article{pmid35778898,
title = {Equitable Policies Need Equitable Practices: Alcohol- and Substance-Exposed Pregnancy as a Case Study},
author = {Arielle R Deutsch and Mohammad S Jalali and Sarah Stout and Leah Frerichs},
doi = {10.1177/15248399221107605},
issn = {1524-8399},
year = {2022},
date = {2022-07-01},
journal = {Health Promot Pract},
pages = {15248399221107605},
abstract = {There is clear need for more effective public health policies. Coupled with calls for more effective policies, increasing demand to address public health disparities experienced by systemically marginalized and historically oppressed groups emphasizes the long-standing need for policies that improve public health equity. Such need is highlighted when examining public health issues such as alcohol- and substance-exposed pregnancy (ASEP): Current policies are ineffective at reducing ASEP, and marginalized groups experience disproportionately lower benefits and higher negative consequences as a result of such policies. Powerful strategies to develop more effective policies that can account for the complexity of such issues, such as systems science methods (SSMs), are becoming popular. However, current best practices for such methods often do not emphasize the additional efforts that will be required to develop equitable, not just effective policies. Using ASEP as an example of a crucial complex issue requiring new policy, we suggest additional steps to include in SSM projects for developing more effective policies that will also help stakeholders determine high-equity policies to reduce health disparities. These steps include modeling structural differences experienced by marginalized groups via systemic racism and oppression, incorporating existing cultural and community sources of strength and resilience as key areas for policy development, and evaluating the sustainability of policies as a dimension of efficacy. We also discuss using community-based participatory approaches as a framework for all SSM processes to ensure that policy development itself is grounded in equitable shared decision-making for marginalized individuals.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
There is clear need for more effective public health policies. Coupled with calls for more effective policies, increasing demand to address public health disparities experienced by systemically marginalized and historically oppressed groups emphasizes the long-standing need for policies that improve public health equity. Such need is highlighted when examining public health issues such as alcohol- and substance-exposed pregnancy (ASEP): Current policies are ineffective at reducing ASEP, and marginalized groups experience disproportionately lower benefits and higher negative consequences as a result of such policies. Powerful strategies to develop more effective policies that can account for the complexity of such issues, such as systems science methods (SSMs), are becoming popular. However, current best practices for such methods often do not emphasize the additional efforts that will be required to develop equitable, not just effective policies. Using ASEP as an example of a crucial complex issue requiring new policy, we suggest additional steps to include in SSM projects for developing more effective policies that will also help stakeholders determine high-equity policies to reduce health disparities. These steps include modeling structural differences experienced by marginalized groups via systemic racism and oppression, incorporating existing cultural and community sources of strength and resilience as key areas for policy development, and evaluating the sustainability of policies as a dimension of efficacy. We also discuss using community-based participatory approaches as a framework for all SSM processes to ensure that policy development itself is grounded in equitable shared decision-making for marginalized individuals.
Mueller, Peter P.; Chen, Qiushi; Ayer, Turgay; Nemutlu, Gizem; Hajjar, Ali; Bethea, Emily D.; Peters, Mary Linton B.; Lee, Brian P.; Janjua, Naveed Z.; Kanwal, Fasiha; Chhatwal, Jagpreet
Duration and cost-effectiveness of hepatocellular carcinoma surveillance in hepatitis C patients after viral eradication. Journal Article
In: Journal of hepatology, vol. 77, iss. 1, pp. 55-62, 2022, ISSN: 1600-0641.
@article{Mueller2022,
title = {Duration and cost-effectiveness of hepatocellular carcinoma surveillance in hepatitis C patients after viral eradication.},
author = {Peter P. Mueller and Qiushi Chen and Turgay Ayer and Gizem Nemutlu and Ali Hajjar and Emily D. Bethea and Mary Linton B. Peters and Brian P. Lee and Naveed Z. Janjua and Fasiha Kanwal and Jagpreet Chhatwal},
url = {https://pubmed.ncbi.nlm.nih.gov/35157959/},
doi = {10.1016/j.jhep.2022.01.027},
issn = {1600-0641},
year = {2022},
date = {2022-07-01},
urldate = {2022-02-01},
journal = {Journal of hepatology},
volume = {77},
issue = {1},
pages = {55-62},
abstract = {Successful treatment of chronic hepatitis C with oral direct-acting antiviral (DAA) leads to virological cure, however, the subsequent risk of hepatocellular carcinoma (HCC) persists. Our objective was to evaluate the cost-effectiveness of biannual surveillance for HCC in patients cured of hepatitis C and the optimal age to stop surveillance. We developed a microsimulation model of the natural history of HCC in hepatitis C individuals with advanced fibrosis or cirrhosis who achieved virological cure with oral DAAs. We used published data on HCC incidence, tumor progression, real-world HCC surveillance adherence, and costs and utilities of different health states. We compared biannual HCC surveillance using ultrasound and alpha-fetoprotein for varying durations of surveillance (from 5 years to lifetime) versus no surveillance. In virologically-cured patients with cirrhosis, the ICER of biannual surveillance remained below $150,000 per additional quality-adjusted life year (QALY) (range: $79,500-$94,800) when surveillance was stopped at age 70, irrespective of the start age (40-65). Compared with no surveillance, surveillance per 1000 cirrhosis patients detected 130 additional HCCs in 'very early'/early stage and yielded 51 additional QALYs. In virologically-cured patients with advanced fibrosis, the ICER of biannual surveillance remained below $150,000/QALY (range: $124,600-$129,800) when surveillance was stopped at age 60, irrespective of the start age (40-50). Compared with no surveillance, surveillance per 1000 advanced fibrosis patients detected 24 additional HCCs in 'very early'/early stage and yielded 12 additional QALYs. Biannual surveillance for HCC in virologically-cured hepatitis C patients is cost-effective until the age of 70 for cirrhosis patients, and until the age of 60 for patients with stable advanced fibrosis. Individuals who are cured of hepatitis C using oral antiviral drugs remain at risk of developing liver cancer. The value of lifelong screening for liver cancer in these individuals is not known. By simulating the life course of hepatitis C cured individuals, we found that ultrasound-based bi-annual screening for liver cancer is cost-effective up to age 70 in those having cirrhosis and up to age 60 in those having stable advanced fibrosis.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Successful treatment of chronic hepatitis C with oral direct-acting antiviral (DAA) leads to virological cure, however, the subsequent risk of hepatocellular carcinoma (HCC) persists. Our objective was to evaluate the cost-effectiveness of biannual surveillance for HCC in patients cured of hepatitis C and the optimal age to stop surveillance. We developed a microsimulation model of the natural history of HCC in hepatitis C individuals with advanced fibrosis or cirrhosis who achieved virological cure with oral DAAs. We used published data on HCC incidence, tumor progression, real-world HCC surveillance adherence, and costs and utilities of different health states. We compared biannual HCC surveillance using ultrasound and alpha-fetoprotein for varying durations of surveillance (from 5 years to lifetime) versus no surveillance. In virologically-cured patients with cirrhosis, the ICER of biannual surveillance remained below $150,000 per additional quality-adjusted life year (QALY) (range: $79,500-$94,800) when surveillance was stopped at age 70, irrespective of the start age (40-65). Compared with no surveillance, surveillance per 1000 cirrhosis patients detected 130 additional HCCs in 'very early'/early stage and yielded 51 additional QALYs. In virologically-cured patients with advanced fibrosis, the ICER of biannual surveillance remained below $150,000/QALY (range: $124,600-$129,800) when surveillance was stopped at age 60, irrespective of the start age (40-50). Compared with no surveillance, surveillance per 1000 advanced fibrosis patients detected 24 additional HCCs in 'very early'/early stage and yielded 12 additional QALYs. Biannual surveillance for HCC in virologically-cured hepatitis C patients is cost-effective until the age of 70 for cirrhosis patients, and until the age of 60 for patients with stable advanced fibrosis. Individuals who are cured of hepatitis C using oral antiviral drugs remain at risk of developing liver cancer. The value of lifelong screening for liver cancer in these individuals is not known. By simulating the life course of hepatitis C cured individuals, we found that ultrasound-based bi-annual screening for liver cancer is cost-effective up to age 70 in those having cirrhosis and up to age 60 in those having stable advanced fibrosis.
Panda, Nikhil; Solsky, Ian; Cauley, Christy; Lipsitz, Stuart; Desai, Eesha V.; Huang, Emily J.; Benjamin, Evan M.; Lubitz, Carrie C.; Onnela, Jukka-Pekka; Haynes, Alex B.
In: Annals of surgery, vol. 276, iss. 1, pp. 193-199, 2022, ISSN: 1528-1140.
@article{Panda2020b,
title = {Smartphone-Based Assessment of Preoperative Decision Conflict and Postoperative Physical Activity Among Patients Undergoing Cancer Surgery: A Prospective Cohort Study.},
author = {Nikhil Panda and Ian Solsky and Christy Cauley and Stuart Lipsitz and Eesha V. Desai and Emily J. Huang and Evan M. Benjamin and Carrie C. Lubitz and Jukka-Pekka Onnela and Alex B. Haynes},
doi = {10.1097/SLA.0000000000004487},
issn = {1528-1140},
year = {2022},
date = {2022-07-01},
urldate = {2022-07-01},
journal = {Annals of surgery},
volume = {276},
issue = {1},
pages = {193-199},
abstract = {To determine the prevalence of clinically significant decision conflict (CSDC) among patients undergoing cancer surgery and associations with postoperative physical activity, as measured through smartphone accelerometer data. Patients with cancer face challenging treatment decisions, which may lead to CSDC. CSDC negatively affects patient-provider relationships, psychosocial functioning, and health-related quality of life; however, physical manifestations of CSDC remain poorly characterized. Adult smartphone-owners undergoing surgery for breast, skin-soft-tissue, head-and-neck, or abdominal cancer (July 2017-2019) were approached. Patients downloaded the Beiwe application that delivered the Decision Conflict Scale (DCS) preoperatively and collected smartphone accelerometer data continuously from enrollment through 6 months postoperatively. Restricted-cubic-spline regression, adjusting for a priori potential confounders (age, type of surgery, support status, and postoperative complications) was used to determine trends in postoperative daily physical activity among patients with and without CSDC (DCS score≥25/100). Among 99 patients who downloaded the application, 85 completed the DCS (86% participation rate). Twenty-three (27%) reported CSDC. These patients were younger (mean age 48.3 [standard deviation 14.2]-vs.-55.0 [13.3},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
To determine the prevalence of clinically significant decision conflict (CSDC) among patients undergoing cancer surgery and associations with postoperative physical activity, as measured through smartphone accelerometer data. Patients with cancer face challenging treatment decisions, which may lead to CSDC. CSDC negatively affects patient-provider relationships, psychosocial functioning, and health-related quality of life; however, physical manifestations of CSDC remain poorly characterized. Adult smartphone-owners undergoing surgery for breast, skin-soft-tissue, head-and-neck, or abdominal cancer (July 2017-2019) were approached. Patients downloaded the Beiwe application that delivered the Decision Conflict Scale (DCS) preoperatively and collected smartphone accelerometer data continuously from enrollment through 6 months postoperatively. Restricted-cubic-spline regression, adjusting for a priori potential confounders (age, type of surgery, support status, and postoperative complications) was used to determine trends in postoperative daily physical activity among patients with and without CSDC (DCS score≥25/100). Among 99 patients who downloaded the application, 85 completed the DCS (86% participation rate). Twenty-three (27%) reported CSDC. These patients were younger (mean age 48.3 [standard deviation 14.2]-vs.-55.0 [13.3
Keyes, Katherine M; Rutherford, Caroline; Hamilton, Ava; Barocas, Joshua A; Gelberg, Kitty H; Mueller, Peter P; Feaster, Daniel J; El-Bassel, Nabila; Cerdá, Magdalena
In: Drug Alcohol Depend Rep, vol. 3, 2022, ISSN: 2772-7246.
@article{pmid35783994,
title = {What is the prevalence of and trend in opioid use disorder in the United States from 2010 to 2019? Using multiplier approaches to estimate prevalence for an unknown population size},
author = {Katherine M Keyes and Caroline Rutherford and Ava Hamilton and Joshua A Barocas and Kitty H Gelberg and Peter P Mueller and Daniel J Feaster and Nabila El-Bassel and Magdalena Cerd\'{a}},
doi = {10.1016/j.dadr.2022.100052},
issn = {2772-7246},
year = {2022},
date = {2022-06-01},
journal = {Drug Alcohol Depend Rep},
volume = {3},
abstract = {Opioid-related overdose deaths have increased since 2010 in the U.S., but information on trends in opioid use disorder (OUD) prevalence is limited due to unreliable data. Multiplier methods are a classical epidemiological technique to estimate prevalence when direct estimation is infeasible or unreliable. We used two different multiplier approaches to estimate OUD prevalence from 2010 to 2019. First, we estimated OUD in National Survey on Drug Use and Health (NSDUH), and based on existing capture-recapture studies, multiplied prevalence by 4.5x. Second, we estimated the probability of drug poisoning death among people with OUD (Meta-analysis indicates 0.52/100,000), and divided the number of drug poisoning deaths in the US by this probability. Estimates were weighted to account for increase in drug-related mortality in recent years due to fentanyl. Estimated OUD prevalence was lowest when estimated in NSDUH with no multiplier, and highest when estimated from vital statistics data without adjustment. Consistent findings emerged with two methods: NSDUH data with multiplier correction, and vital statistics data with multiplier and adjustment. From these two methods, OUD prevalence increased from 2010 to 2014; then stabilized and slightly declined annually (survey data with multiplier, highest prevalence of 4.0% in 2015; death data with a multiplier and correction, highest prevalence of 2.35% in 2016). The number of US adolescent and adult individuals with OUD in 2019 was estimated between 6.7-7.6 million. When multipliers and corrections are used, OUD may have stabilized or slightly declined after 2015. Nevertheless, it remains highly prevalent, affecting 6-7 million US adolescents and adults.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Opioid-related overdose deaths have increased since 2010 in the U.S., but information on trends in opioid use disorder (OUD) prevalence is limited due to unreliable data. Multiplier methods are a classical epidemiological technique to estimate prevalence when direct estimation is infeasible or unreliable. We used two different multiplier approaches to estimate OUD prevalence from 2010 to 2019. First, we estimated OUD in National Survey on Drug Use and Health (NSDUH), and based on existing capture-recapture studies, multiplied prevalence by 4.5x. Second, we estimated the probability of drug poisoning death among people with OUD (Meta-analysis indicates 0.52/100,000), and divided the number of drug poisoning deaths in the US by this probability. Estimates were weighted to account for increase in drug-related mortality in recent years due to fentanyl. Estimated OUD prevalence was lowest when estimated in NSDUH with no multiplier, and highest when estimated from vital statistics data without adjustment. Consistent findings emerged with two methods: NSDUH data with multiplier correction, and vital statistics data with multiplier and adjustment. From these two methods, OUD prevalence increased from 2010 to 2014; then stabilized and slightly declined annually (survey data with multiplier, highest prevalence of 4.0% in 2015; death data with a multiplier and correction, highest prevalence of 2.35% in 2016). The number of US adolescent and adult individuals with OUD in 2019 was estimated between 6.7-7.6 million. When multipliers and corrections are used, OUD may have stabilized or slightly declined after 2015. Nevertheless, it remains highly prevalent, affecting 6-7 million US adolescents and adults.
Micieli, Andrew; Singh, Nishita; Jahn, Beate; Siebert, Uwe; Menon, Bijoy K; Demchuk, Andrew M
Cost effectiveness of testing for CYP2C19 loss-of-function carriers following transient ischemic attack/minor stroke: A Canadian perspective Journal Article
In: Int J Stroke, pp. 17474930221111898, 2022, ISSN: 1747-4949.
@article{pmid35739635,
title = {Cost effectiveness of testing for CYP2C19 loss-of-function carriers following transient ischemic attack/minor stroke: A Canadian perspective},
author = {Andrew Micieli and Nishita Singh and Beate Jahn and Uwe Siebert and Bijoy K Menon and Andrew M Demchuk},
doi = {10.1177/17474930221111898},
issn = {1747-4949},
year = {2022},
date = {2022-06-01},
journal = {Int J Stroke},
pages = {17474930221111898},
abstract = {Background- The CHANCE-2 study compared three weeks of aspirin-ticagrelor to aspirin-clopidogrel in CYP2C19 loss-of-function (LOF) allele carriers following a TIA/minor stroke and demonstrated a modestly lower risk of stroke recurrence with aspirin-ticagrelor. This stroke protection was largely for minor stroke and came at an increased risk of bleeding. The cost effectiveness of implementing testing for LOF allele status to personalize antiplatelet regimen for secondary stroke prevention after a TIA/minor stroke in the Canadian health care context is unknown.Methods- Cost effectiveness analysis using a decision-analytic Markov cohort model with a lifetime horizon was performed to determine the costs and health benefits of testing for LOF allele status compared with no testing (current standard of care). The population of interest was patients living in Canada who suffered a TIA/minor stroke. Outcomes of interest were life-years gained (LYG), quality-adjusted life years (QALY) gained, costs (reported in 2022 Canadian dollars) and the incremental cost-effectiveness ratio (ICER). We adopted the perspective of the Federal, Provincial and Territorial Ministries of Health, and used a 1.5% annual discount rate. Sensitivity analyses were performed to assess uncertainty.Results- Compared to standard of care, LOF allele testing leads to 0.14 LYG (undiscounted), 0.12 QALYs gained (undiscounted) and additional lifetime costs of $432 (discounted) per patient. The ICER of the LOF allele testing strategy is $4310 per QALY gained compared with standard of care. The probabilistic sensitivity analyses demonstrated that LOF allele testing was cost-effective in more than 99.99% of simulations using a willingness-to-pay threshold of $50,000 per QALY.Conclusions-Based on available evidence, testing for LOF allele followed by short duration three weeks of aspirin-ticagrelor compared to standard of care aspirin-clopidogrel can lead to prolonged life and improved quality of life, and can be considered very cost effective when compared with other well-accepted technologies in health and medicine.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Background- The CHANCE-2 study compared three weeks of aspirin-ticagrelor to aspirin-clopidogrel in CYP2C19 loss-of-function (LOF) allele carriers following a TIA/minor stroke and demonstrated a modestly lower risk of stroke recurrence with aspirin-ticagrelor. This stroke protection was largely for minor stroke and came at an increased risk of bleeding. The cost effectiveness of implementing testing for LOF allele status to personalize antiplatelet regimen for secondary stroke prevention after a TIA/minor stroke in the Canadian health care context is unknown.Methods- Cost effectiveness analysis using a decision-analytic Markov cohort model with a lifetime horizon was performed to determine the costs and health benefits of testing for LOF allele status compared with no testing (current standard of care). The population of interest was patients living in Canada who suffered a TIA/minor stroke. Outcomes of interest were life-years gained (LYG), quality-adjusted life years (QALY) gained, costs (reported in 2022 Canadian dollars) and the incremental cost-effectiveness ratio (ICER). We adopted the perspective of the Federal, Provincial and Territorial Ministries of Health, and used a 1.5% annual discount rate. Sensitivity analyses were performed to assess uncertainty.Results- Compared to standard of care, LOF allele testing leads to 0.14 LYG (undiscounted), 0.12 QALYs gained (undiscounted) and additional lifetime costs of $432 (discounted) per patient. The ICER of the LOF allele testing strategy is $4310 per QALY gained compared with standard of care. The probabilistic sensitivity analyses demonstrated that LOF allele testing was cost-effective in more than 99.99% of simulations using a willingness-to-pay threshold of $50,000 per QALY.Conclusions-Based on available evidence, testing for LOF allele followed by short duration three weeks of aspirin-ticagrelor compared to standard of care aspirin-clopidogrel can lead to prolonged life and improved quality of life, and can be considered very cost effective when compared with other well-accepted technologies in health and medicine.
Stringfellow, Erin J; Lim, Tse Yang; Humphreys, Keith; DiGennaro, Catherine; Stafford, Celia; Beaulieu, Elizabeth; Homer, Jack; Wakeland, Wayne; Bearnot, Benjamin; McHugh, R Kathryn; Kelly, John; Glos, Lukas; Eggers, Sara L; Kazemi, Reza; Jalali, Mohammad S
Reducing opioid use disorder and overdose deaths in the United States: A dynamic modeling analysis Journal Article
In: Sci Adv, vol. 8, no. 25, pp. eabm8147, 2022, ISSN: 2375-2548.
@article{pmid35749492,
title = {Reducing opioid use disorder and overdose deaths in the United States: A dynamic modeling analysis},
author = {Erin J Stringfellow and Tse Yang Lim and Keith Humphreys and Catherine DiGennaro and Celia Stafford and Elizabeth Beaulieu and Jack Homer and Wayne Wakeland and Benjamin Bearnot and R Kathryn McHugh and John Kelly and Lukas Glos and Sara L Eggers and Reza Kazemi and Mohammad S Jalali},
doi = {10.1126/sciadv.abm8147},
issn = {2375-2548},
year = {2022},
date = {2022-06-01},
journal = {Sci Adv},
volume = {8},
number = {25},
pages = {eabm8147},
abstract = {Opioid overdose deaths remain a major public health crisis. We used a system dynamics simulation model of the U.S. opioid-using population age 12 and older to explore the impacts of 11 strategies on the prevalence of opioid use disorder (OUD) and fatal opioid overdoses from 2022 to 2032. These strategies spanned opioid misuse and OUD prevention, buprenorphine capacity, recovery support, and overdose harm reduction. By 2032, three strategies saved the most lives: (i) reducing the risk of opioid overdose involving fentanyl use, which may be achieved through fentanyl-focused harm reduction services; (ii) increasing naloxone distribution to people who use opioids; and (iii) recovery support for people in remission, which reduced deaths by reducing OUD. Increasing buprenorphine providers' capacity to treat more people decreased fatal overdose, but only in the short term. Our analysis provides insight into the kinds of multifaceted approaches needed to save lives.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Opioid overdose deaths remain a major public health crisis. We used a system dynamics simulation model of the U.S. opioid-using population age 12 and older to explore the impacts of 11 strategies on the prevalence of opioid use disorder (OUD) and fatal opioid overdoses from 2022 to 2032. These strategies spanned opioid misuse and OUD prevention, buprenorphine capacity, recovery support, and overdose harm reduction. By 2032, three strategies saved the most lives: (i) reducing the risk of opioid overdose involving fentanyl use, which may be achieved through fentanyl-focused harm reduction services; (ii) increasing naloxone distribution to people who use opioids; and (iii) recovery support for people in remission, which reduced deaths by reducing OUD. Increasing buprenorphine providers' capacity to treat more people decreased fatal overdose, but only in the short term. Our analysis provides insight into the kinds of multifaceted approaches needed to save lives.
Ergun, Mehmet A; Hajjar, Ali; Alagoz, Oguzhan; Rampurwala, Murtuza
Optimal breast cancer risk reduction policies tailored to personal risk level Journal Article
In: Health Care Manag Sci, 2022, ISSN: 1386-9620.
@article{pmid35687269,
title = {Optimal breast cancer risk reduction policies tailored to personal risk level},
author = {Mehmet A Ergun and Ali Hajjar and Oguzhan Alagoz and Murtuza Rampurwala},
doi = {10.1007/s10729-022-09596-2},
issn = {1386-9620},
year = {2022},
date = {2022-06-01},
journal = {Health Care Manag Sci},
abstract = {Depending on personal and hereditary factors, each woman has a different risk of developing breast cancer, one of the leading causes of death for women. For women with a high-risk of breast cancer, their risk can be reduced by two main therapeutic approaches: 1) preventive treatments such as hormonal therapies (i.e., tamoxifen, raloxifene, exemestane); or 2) a risk reduction surgery (i.e., mastectomy). Existing national clinical guidelines either fail to incorporate or have limited use of the personal risk of developing breast cancer in their proposed risk reduction strategies. As a result, they do not provide enough resolution on the benefit-risk trade-off of an intervention policy as personal risk changes. In addressing this problem, we develop a discrete-time, finite-horizon Markov decision process (MDP) model with the objective of maximizing the patient's total expected quality-adjusted life years. We find several useful insights some of which contradict the existing national breast cancer risk reduction recommendations. For example, we find that mastectomy is the optimal choice for the border-line high-risk women who are between ages 22 and 38. Additionally, in contrast to the National Comprehensive Cancer Network recommendations, we find that exemestane is a plausible, in fact, the best, option for high-risk postmenopausal women.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Depending on personal and hereditary factors, each woman has a different risk of developing breast cancer, one of the leading causes of death for women. For women with a high-risk of breast cancer, their risk can be reduced by two main therapeutic approaches: 1) preventive treatments such as hormonal therapies (i.e., tamoxifen, raloxifene, exemestane); or 2) a risk reduction surgery (i.e., mastectomy). Existing national clinical guidelines either fail to incorporate or have limited use of the personal risk of developing breast cancer in their proposed risk reduction strategies. As a result, they do not provide enough resolution on the benefit-risk trade-off of an intervention policy as personal risk changes. In addressing this problem, we develop a discrete-time, finite-horizon Markov decision process (MDP) model with the objective of maximizing the patient's total expected quality-adjusted life years. We find several useful insights some of which contradict the existing national breast cancer risk reduction recommendations. For example, we find that mastectomy is the optimal choice for the border-line high-risk women who are between ages 22 and 38. Additionally, in contrast to the National Comprehensive Cancer Network recommendations, we find that exemestane is a plausible, in fact, the best, option for high-risk postmenopausal women.
Lim, Tse Yang; Stringfellow, Erin J; Stafford, Celia A; DiGennaro, Catherine; Homer, Jack B; Wakeland, Wayne; Eggers, Sara L; Kazemi, Reza; Glos, Lukas; Ewing, Emily G; Bannister, Calvin B; Humphreys, Keith; Throckmorton, Douglas C; Jalali, Mohammad S
Modeling the evolution of the US opioid crisis for national policy development Journal Article
In: Proc Natl Acad Sci U S A, vol. 119, no. 23, pp. e2115714119, 2022, ISSN: 1091-6490.
@article{pmid35639699,
title = {Modeling the evolution of the US opioid crisis for national policy development},
author = {Tse Yang Lim and Erin J Stringfellow and Celia A Stafford and Catherine DiGennaro and Jack B Homer and Wayne Wakeland and Sara L Eggers and Reza Kazemi and Lukas Glos and Emily G Ewing and Calvin B Bannister and Keith Humphreys and Douglas C Throckmorton and Mohammad S Jalali},
doi = {10.1073/pnas.2115714119},
issn = {1091-6490},
year = {2022},
date = {2022-06-01},
urldate = {2022-06-01},
journal = {Proc Natl Acad Sci U S A},
volume = {119},
number = {23},
pages = {e2115714119},
abstract = {Significance: The opioid crisis remains one of the greatest public health challenges in the United States. The crisis is complex, with long delays and feedbacks between policy actions and their effects, which creates a risk of unintended consequences and complicates policy decision-making. We present SOURCE (Simulation of Opioid Use, Response, Consequences, and Effects), an operationally detailed national-level model of the opioid crisis, intended to enhance understanding of the crisis and guide policy decisions. Drawing on multiple data sources, SOURCE replicates how risks of opioid misuse initiation and overdose have evolved over time in response to behavioral and other changes and suggests how those risks may evolve in the future, providing a basis for projecting and analyzing potential policy impacts and solutions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Significance: The opioid crisis remains one of the greatest public health challenges in the United States. The crisis is complex, with long delays and feedbacks between policy actions and their effects, which creates a risk of unintended consequences and complicates policy decision-making. We present SOURCE (Simulation of Opioid Use, Response, Consequences, and Effects), an operationally detailed national-level model of the opioid crisis, intended to enhance understanding of the crisis and guide policy decisions. Drawing on multiple data sources, SOURCE replicates how risks of opioid misuse initiation and overdose have evolved over time in response to behavioral and other changes and suggests how those risks may evolve in the future, providing a basis for projecting and analyzing potential policy impacts and solutions.
Julien, Jovan; Ayer, Turgay; Tapper, Elliot B.; Barbosa, Carolina; Dowd, William; Chhatwal, Jagpreet
Effect of Increased Alcohol Consumption During COVID-19 Pandemic on Alcohol-related Liver Disease: A Modeling Study. Journal Article
In: Hepatology (Baltimore, Md.), vol. 75, iss. 6, pp. 1480-1490, 2022, ISSN: 1527-3350.
@article{Julien2021,
title = {Effect of Increased Alcohol Consumption During COVID-19 Pandemic on Alcohol-related Liver Disease: A Modeling Study.},
author = {Jovan Julien and Turgay Ayer and Elliot B. Tapper and Carolina Barbosa and William Dowd and Jagpreet Chhatwal},
url = {https://pubmed.ncbi.nlm.nih.gov/34878683/},
doi = {10.1002/hep.32272},
issn = {1527-3350},
year = {2022},
date = {2022-06-01},
urldate = {2021-12-01},
journal = {Hepatology (Baltimore, Md.)},
volume = {75},
issue = {6},
pages = {1480-1490},
abstract = {Alcohol consumption increased during the coronavirus disease-2019 (COVID-19) pandemic in 2020 in the U.S. We projected the effect of increased alcohol consumption on alcohol-related liver disease (ALD) and mortality. We extended a previously validated microsimulation model that estimated the short- and long-term effect of increased drinking during the COVID-19 pandemic in individuals in the US born between 1920-2012. We modeled short- and long-term outcomes of current drinking patterns during COVID-19 (status quo) using survey data of changes in alcohol consumption in a nationally representative sample between February and November 2020. We compared these outcomes with a counter-factual scenario wherein no COVID-19 occurs and drinking patterns do not change. One-year increase in alcohol consumption during the COVID-19 pandemic is estimated to result in 8,000 [95% UI 7,500-8,600] additional ALD-related deaths, 18,700 [95% UI 17,600-19,900] cases of decompensated cirrhosis, and 1,000 [95% UI 1,000-1,100] cases of HCC, and 8.9 million disability-adjusted life-years between 2020 and 2040. Between 2020 and 2023, alcohol consumption changes due to COVID-19 will lead to 100 [100-200] additional deaths and 2,800 [2,700-2,900] additional decompensated cirrhosis cases. A sustained increase in alcohol consumption for more than 1 year could result in additional morbidity and mortality. A short-term increase in alcohol consumption during the COVID-19 pandemic can substantially increase long-term ALD-related morbidity and mortality. Our findings highlight the need for individuals and policymakers to make informed decisions to mitigate the impact of high-risk alcohol drinking in the US.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Alcohol consumption increased during the coronavirus disease-2019 (COVID-19) pandemic in 2020 in the U.S. We projected the effect of increased alcohol consumption on alcohol-related liver disease (ALD) and mortality. We extended a previously validated microsimulation model that estimated the short- and long-term effect of increased drinking during the COVID-19 pandemic in individuals in the US born between 1920-2012. We modeled short- and long-term outcomes of current drinking patterns during COVID-19 (status quo) using survey data of changes in alcohol consumption in a nationally representative sample between February and November 2020. We compared these outcomes with a counter-factual scenario wherein no COVID-19 occurs and drinking patterns do not change. One-year increase in alcohol consumption during the COVID-19 pandemic is estimated to result in 8,000 [95% UI 7,500-8,600] additional ALD-related deaths, 18,700 [95% UI 17,600-19,900] cases of decompensated cirrhosis, and 1,000 [95% UI 1,000-1,100] cases of HCC, and 8.9 million disability-adjusted life-years between 2020 and 2040. Between 2020 and 2023, alcohol consumption changes due to COVID-19 will lead to 100 [100-200] additional deaths and 2,800 [2,700-2,900] additional decompensated cirrhosis cases. A sustained increase in alcohol consumption for more than 1 year could result in additional morbidity and mortality. A short-term increase in alcohol consumption during the COVID-19 pandemic can substantially increase long-term ALD-related morbidity and mortality. Our findings highlight the need for individuals and policymakers to make informed decisions to mitigate the impact of high-risk alcohol drinking in the US.