2022
Bischoff-Ferrari, Heike A; Freystätter, Gregor; Vellas, Bruno; Dawson-Hughes, Bess; Kressig, Reto W; Kanis, John A; Willett, Walter C; Manson, JoAnn E; Rizzoli, René; Theiler, Robert; Hofbauer, Lorenz C; Armbrecht, Gabriele; da Silva, José A P; Blauth, Michael; de Godoi Rezende Costa Molino, Caroline; Lang, Wei; Siebert, Uwe; Egli, Andreas; Orav, Endel J; Wieczorek, Maud; Group, DO-HEALTH Research
In: Am J Clin Nutr, vol. 115, no. 5, pp. 1311-1321, 2022, ISSN: 1938-3207.
@article{pmid35136915,
title = {Effects of vitamin D, omega-3 fatty acids and a simple home strength exercise program on fall prevention: the DO-HEALTH randomized clinical trial},
author = {Heike A Bischoff-Ferrari and Gregor Freyst\"{a}tter and Bruno Vellas and Bess Dawson-Hughes and Reto W Kressig and John A Kanis and Walter C Willett and JoAnn E Manson and Ren\'{e} Rizzoli and Robert Theiler and Lorenz C Hofbauer and Gabriele Armbrecht and Jos\'{e} A P da Silva and Michael Blauth and Caroline de Godoi Rezende Costa Molino and Wei Lang and Uwe Siebert and Andreas Egli and Endel J Orav and Maud Wieczorek and DO-HEALTH Research Group},
doi = {10.1093/ajcn/nqac022},
issn = {1938-3207},
year = {2022},
date = {2022-05-01},
urldate = {2022-02-01},
journal = {Am J Clin Nutr},
volume = {115},
number = {5},
pages = {1311-1321},
abstract = {BACKGROUND: The role of vitamin D, omega-3 fatty acids and home exercise on fall prevention among generally healthy and active older adults is unclear.
OBJECTIVES: To test the effect of daily supplemental vitamin D, marine omega-3 s fatty acids and a simple home exercise program (SHEP), alone or in combination, on the incidence of total and injurious falls among generally healthy older adults.
METHODS: We performed a 2 × 2 × 2 factorial design randomized-controlled trial among 2157 community-dwelling adults age 70 years and older, who had no major health events in the five years prior to enrolment, recruited from Switzerland, Germany, Austria, France, and Portugal between December 2012 and November 2014. Participants were randomly assigned to 2000 international units/day of vitamin D3 and/or 1 g/day of marine omega-3 s, and/or a SHEP versus placebo and/or control exercise over three years. The primary endpoint for the present fall analysis was the incidence rate of total falls. Falls were recorded prospectively throughout the trial. Since there were no interactions between treatments, main effects are reported based on modified intent-to-treat.
RESULTS: Of 2157 randomized participants, 1900 (88%) completed the study. The mean age was 74.9 years, 61.7% were women, 40.7% had serum 25-hydroxyvitamin D concentration < 20 ng/ml, and 83% were at least moderately physically active. In total, 3333 falls were recorded over a median follow-up of 2.99 years. Overall, vitamin D and SHEP had no benefit on total falls, whilst omega-3 s compared to no omega-3 s reduced total falls by 10% (incidence rate ratio [IRR] = 0.90, 95% confidence interval [0.81, 1.00], P = 0.04).
CONCLUSION: Among generally healthy, active and vitamin D-replete older adults, supplemental omega-3 s may have a modest benefit on the incidence of total falls, whilst daily high-dose vitamin D or SHEP had no benefit. Trial registration number: NCT01745263 URL of registration: https://clinicaltrials.gov/ct2/show/NCT01745263.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: The role of vitamin D, omega-3 fatty acids and home exercise on fall prevention among generally healthy and active older adults is unclear.
OBJECTIVES: To test the effect of daily supplemental vitamin D, marine omega-3 s fatty acids and a simple home exercise program (SHEP), alone or in combination, on the incidence of total and injurious falls among generally healthy older adults.
METHODS: We performed a 2 × 2 × 2 factorial design randomized-controlled trial among 2157 community-dwelling adults age 70 years and older, who had no major health events in the five years prior to enrolment, recruited from Switzerland, Germany, Austria, France, and Portugal between December 2012 and November 2014. Participants were randomly assigned to 2000 international units/day of vitamin D3 and/or 1 g/day of marine omega-3 s, and/or a SHEP versus placebo and/or control exercise over three years. The primary endpoint for the present fall analysis was the incidence rate of total falls. Falls were recorded prospectively throughout the trial. Since there were no interactions between treatments, main effects are reported based on modified intent-to-treat.
RESULTS: Of 2157 randomized participants, 1900 (88%) completed the study. The mean age was 74.9 years, 61.7% were women, 40.7% had serum 25-hydroxyvitamin D concentration < 20 ng/ml, and 83% were at least moderately physically active. In total, 3333 falls were recorded over a median follow-up of 2.99 years. Overall, vitamin D and SHEP had no benefit on total falls, whilst omega-3 s compared to no omega-3 s reduced total falls by 10% (incidence rate ratio [IRR] = 0.90, 95% confidence interval [0.81, 1.00], P = 0.04).
CONCLUSION: Among generally healthy, active and vitamin D-replete older adults, supplemental omega-3 s may have a modest benefit on the incidence of total falls, whilst daily high-dose vitamin D or SHEP had no benefit. Trial registration number: NCT01745263 URL of registration: https://clinicaltrials.gov/ct2/show/NCT01745263.
OBJECTIVES: To test the effect of daily supplemental vitamin D, marine omega-3 s fatty acids and a simple home exercise program (SHEP), alone or in combination, on the incidence of total and injurious falls among generally healthy older adults.
METHODS: We performed a 2 × 2 × 2 factorial design randomized-controlled trial among 2157 community-dwelling adults age 70 years and older, who had no major health events in the five years prior to enrolment, recruited from Switzerland, Germany, Austria, France, and Portugal between December 2012 and November 2014. Participants were randomly assigned to 2000 international units/day of vitamin D3 and/or 1 g/day of marine omega-3 s, and/or a SHEP versus placebo and/or control exercise over three years. The primary endpoint for the present fall analysis was the incidence rate of total falls. Falls were recorded prospectively throughout the trial. Since there were no interactions between treatments, main effects are reported based on modified intent-to-treat.
RESULTS: Of 2157 randomized participants, 1900 (88%) completed the study. The mean age was 74.9 years, 61.7% were women, 40.7% had serum 25-hydroxyvitamin D concentration < 20 ng/ml, and 83% were at least moderately physically active. In total, 3333 falls were recorded over a median follow-up of 2.99 years. Overall, vitamin D and SHEP had no benefit on total falls, whilst omega-3 s compared to no omega-3 s reduced total falls by 10% (incidence rate ratio [IRR] = 0.90, 95% confidence interval [0.81, 1.00], P = 0.04).
CONCLUSION: Among generally healthy, active and vitamin D-replete older adults, supplemental omega-3 s may have a modest benefit on the incidence of total falls, whilst daily high-dose vitamin D or SHEP had no benefit. Trial registration number: NCT01745263 URL of registration: https://clinicaltrials.gov/ct2/show/NCT01745263.
Yildirim, Melike; Gaynes, Bradley N.; Keskinocak, Pinar; Pence, Brian W.; Swann, Julie
The Cost-Effectiveness Of Depression Screening For The General Adult Population. Journal Article
In: Journal of affective disorders, vol. 303, pp. 306-314, 2022, ISSN: 1573-2517.
@article{Yildirim2022,
title = {The Cost-Effectiveness Of Depression Screening For The General Adult Population.},
author = {Melike Yildirim and Bradley N. Gaynes and Pinar Keskinocak and Brian W. Pence and Julie Swann},
url = {https://pubmed.ncbi.nlm.nih.gov/35181387/},
doi = {10.1016/j.jad.2022.02.044},
issn = {1573-2517},
year = {2022},
date = {2022-04-15},
urldate = {2022-02-01},
journal = {Journal of affective disorders},
volume = {303},
pages = {306-314},
abstract = {Depression is a treatable disease, and untreated depression can lead to serious health complications and decrease the quality of life. Therefore, prevention, early identification, and treatment efforts are essential. Screening has an essential role in preventive medicine in the general population. Ideally, screening tools detect patients early enough to manage the disease and reduce symptoms. We aimed to determine the cost-effectiveness of routine screening schedules. We used a discrete-time nonstationary Markov model to simulate the progression of depression. We used Monte Carlo techniques to simulate the stochastic model for 20 years or during the lifetime of individuals. Baseline and screening scenario models with screening frequencies of annual, 2-year, and 5-year strategies were compared based on incremental cost-effectiveness ratios (ICER). Monte Carlo (MC) simulation and one-way sensitivity analysis were conducted to manage uncertainties. In the general population, all screening strategies were cost-effective compared to the baseline. However, male and female populations differed based on cost over quality-adjusted life years (QALY). Females had lower ICERs, and annual screening had the highest ICER for females, with 11,134$/QALY gained. In contrast, males had around three times higher ICER, with annual screening costs of 34,065$/QALY gained. We assumed that the screening frequency was not changing at any time during the screening scenario. In our calculations, false-positive cases were not taking into account. Considering the high lifetime prevalence and recurrence rates of depression, detection and prevention efforts can be one critical cornerstone to support required care. Our analysis combined the expected benefits and costs of screening and assessed the effectiveness of screening scenarios. We conclude that routine screening is cost-effective for all age groups of females and young, middle-aged males.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Depression is a treatable disease, and untreated depression can lead to serious health complications and decrease the quality of life. Therefore, prevention, early identification, and treatment efforts are essential. Screening has an essential role in preventive medicine in the general population. Ideally, screening tools detect patients early enough to manage the disease and reduce symptoms. We aimed to determine the cost-effectiveness of routine screening schedules. We used a discrete-time nonstationary Markov model to simulate the progression of depression. We used Monte Carlo techniques to simulate the stochastic model for 20 years or during the lifetime of individuals. Baseline and screening scenario models with screening frequencies of annual, 2-year, and 5-year strategies were compared based on incremental cost-effectiveness ratios (ICER). Monte Carlo (MC) simulation and one-way sensitivity analysis were conducted to manage uncertainties. In the general population, all screening strategies were cost-effective compared to the baseline. However, male and female populations differed based on cost over quality-adjusted life years (QALY). Females had lower ICERs, and annual screening had the highest ICER for females, with 11,134$/QALY gained. In contrast, males had around three times higher ICER, with annual screening costs of 34,065$/QALY gained. We assumed that the screening frequency was not changing at any time during the screening scenario. In our calculations, false-positive cases were not taking into account. Considering the high lifetime prevalence and recurrence rates of depression, detection and prevention efforts can be one critical cornerstone to support required care. Our analysis combined the expected benefits and costs of screening and assessed the effectiveness of screening scenarios. We conclude that routine screening is cost-effective for all age groups of females and young, middle-aged males.
Linas, Benjamin P; Xiao, Jade; Dalgic, Ozden O; Mueller, Peter P; Adee, Madeline; Aaron, Alec; Ayer, Turgay; Chhatwal, Jagpreet
Projecting COVID-19 Mortality as States Relax Nonpharmacologic Interventions Journal Article
In: JAMA Health Forum, vol. 3, no. 4, pp. e220760, 2022, ISSN: 2689-0186.
@article{pmid35977324,
title = {Projecting COVID-19 Mortality as States Relax Nonpharmacologic Interventions},
author = {Benjamin P Linas and Jade Xiao and Ozden O Dalgic and Peter P Mueller and Madeline Adee and Alec Aaron and Turgay Ayer and Jagpreet Chhatwal},
doi = {10.1001/jamahealthforum.2022.0760},
issn = {2689-0186},
year = {2022},
date = {2022-04-01},
journal = {JAMA Health Forum},
volume = {3},
number = {4},
pages = {e220760},
abstract = {Importance: A key question for policy makers and the public is what to expect from the COVID-19 pandemic going forward as states lift nonpharmacologic interventions (NPIs), such as indoor mask mandates, to prevent COVID-19 transmission.
Objective: To project COVID-19 deaths between March 1, 2022, and December 31, 2022, in each of the 50 US states, District of Columbia, and Puerto Rico assuming different dates of lifting of mask mandates and NPIs.
Design Setting and Participants: This simulation modeling study used the COVID-19 Policy Simulator compartmental model to project COVID-19 deaths from March 1, 2022, to December 31, 2022, using simulated populations in the 50 US states, District of Columbia, and Puerto Rico. Projected current epidemiologic trends for each state until December 31, 2022, assuming the current pace of vaccination is maintained into the future and modeling different dates of lifting NPIs.
Exposures: Date of lifting statewide NPI mandates as March 1, April 1, May 1, June 1, or July 1, 2022.
Main Outcomes and Measures: Projected COVID-19 incident deaths from March to December 2022.
Results: With the high transmissibility of current circulating SARS-CoV-2 variants, the simulated lifting of NPIs in March 2022 was associated with resurgences of COVID-19 deaths in nearly every state. In comparison, delaying by even 1 month to lift NPIs in April 2022 was estimated to mitigate the amplitude of the surge. For most states, however, no amount of delay was estimated to be sufficient to prevent a surge in deaths completely. The primary factor associated with recurrent epidemics in the simulation was the assumed high effective reproduction number of unmitigated viral transmission. With a lower level of transmissibility similar to those of the ancestral strains, the model estimated that most states could remove NPIs in March 2022 and likely not see recurrent surges.
Conclusions and Relevance: This simulation study estimated that the SARS-CoV-2 virus would likely continue to take a major toll in the US, even as cases continued to decrease. Because of the high transmissibility of the recent Delta and Omicron variants, premature lifting of NPIs could pose a substantial threat of rebounding surges in morbidity and mortality. At the same time, continued delay in lifting NPIs may not prevent future surges.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Importance: A key question for policy makers and the public is what to expect from the COVID-19 pandemic going forward as states lift nonpharmacologic interventions (NPIs), such as indoor mask mandates, to prevent COVID-19 transmission.
Objective: To project COVID-19 deaths between March 1, 2022, and December 31, 2022, in each of the 50 US states, District of Columbia, and Puerto Rico assuming different dates of lifting of mask mandates and NPIs.
Design Setting and Participants: This simulation modeling study used the COVID-19 Policy Simulator compartmental model to project COVID-19 deaths from March 1, 2022, to December 31, 2022, using simulated populations in the 50 US states, District of Columbia, and Puerto Rico. Projected current epidemiologic trends for each state until December 31, 2022, assuming the current pace of vaccination is maintained into the future and modeling different dates of lifting NPIs.
Exposures: Date of lifting statewide NPI mandates as March 1, April 1, May 1, June 1, or July 1, 2022.
Main Outcomes and Measures: Projected COVID-19 incident deaths from March to December 2022.
Results: With the high transmissibility of current circulating SARS-CoV-2 variants, the simulated lifting of NPIs in March 2022 was associated with resurgences of COVID-19 deaths in nearly every state. In comparison, delaying by even 1 month to lift NPIs in April 2022 was estimated to mitigate the amplitude of the surge. For most states, however, no amount of delay was estimated to be sufficient to prevent a surge in deaths completely. The primary factor associated with recurrent epidemics in the simulation was the assumed high effective reproduction number of unmitigated viral transmission. With a lower level of transmissibility similar to those of the ancestral strains, the model estimated that most states could remove NPIs in March 2022 and likely not see recurrent surges.
Conclusions and Relevance: This simulation study estimated that the SARS-CoV-2 virus would likely continue to take a major toll in the US, even as cases continued to decrease. Because of the high transmissibility of the recent Delta and Omicron variants, premature lifting of NPIs could pose a substantial threat of rebounding surges in morbidity and mortality. At the same time, continued delay in lifting NPIs may not prevent future surges.
Objective: To project COVID-19 deaths between March 1, 2022, and December 31, 2022, in each of the 50 US states, District of Columbia, and Puerto Rico assuming different dates of lifting of mask mandates and NPIs.
Design Setting and Participants: This simulation modeling study used the COVID-19 Policy Simulator compartmental model to project COVID-19 deaths from March 1, 2022, to December 31, 2022, using simulated populations in the 50 US states, District of Columbia, and Puerto Rico. Projected current epidemiologic trends for each state until December 31, 2022, assuming the current pace of vaccination is maintained into the future and modeling different dates of lifting NPIs.
Exposures: Date of lifting statewide NPI mandates as March 1, April 1, May 1, June 1, or July 1, 2022.
Main Outcomes and Measures: Projected COVID-19 incident deaths from March to December 2022.
Results: With the high transmissibility of current circulating SARS-CoV-2 variants, the simulated lifting of NPIs in March 2022 was associated with resurgences of COVID-19 deaths in nearly every state. In comparison, delaying by even 1 month to lift NPIs in April 2022 was estimated to mitigate the amplitude of the surge. For most states, however, no amount of delay was estimated to be sufficient to prevent a surge in deaths completely. The primary factor associated with recurrent epidemics in the simulation was the assumed high effective reproduction number of unmitigated viral transmission. With a lower level of transmissibility similar to those of the ancestral strains, the model estimated that most states could remove NPIs in March 2022 and likely not see recurrent surges.
Conclusions and Relevance: This simulation study estimated that the SARS-CoV-2 virus would likely continue to take a major toll in the US, even as cases continued to decrease. Because of the high transmissibility of the recent Delta and Omicron variants, premature lifting of NPIs could pose a substantial threat of rebounding surges in morbidity and mortality. At the same time, continued delay in lifting NPIs may not prevent future surges.
Cramer, Estee Y; Ray, Evan L; Lopez, Velma K; Bracher, Johannes; Brennen, Andrea; Rivadeneira, Alvaro J Castro; Gerding, Aaron; Gneiting, Tilmann; House, Katie H; Huang, Yuxin; Jayawardena, Dasuni; Kanji, Abdul H; Khandelwal, Ayush; Le, Khoa; Mühlemann, Anja; Niemi, Jarad; Shah, Apurv; Stark, Ariane; Wang, Yijin; Wattanachit, Nutcha; Zorn, Martha W; Gu, Youyang; Jain, Sansiddh; Bannur, Nayana; Deva, Ayush; Kulkarni, Mihir; Merugu, Srujana; Raval, Alpan; Shingi, Siddhant; Tiwari, Avtansh; White, Jerome; Abernethy, Neil F; Woody, Spencer; Dahan, Maytal; Fox, Spencer; Gaither, Kelly; Lachmann, Michael; Meyers, Lauren Ancel; Scott, James G; Tec, Mauricio; Srivastava, Ajitesh; George, Glover E; Cegan, Jeffrey C; Dettwiller, Ian D; England, William P; Farthing, Matthew W; Hunter, Robert H; Lafferty, Brandon; Linkov, Igor; Mayo, Michael L; Parno, Matthew D; Rowland, Michael A; Trump, Benjamin D; Zhang-James, Yanli; Chen, Samuel; Faraone, Stephen V; Hess, Jonathan; Morley, Christopher P; Salekin, Asif; Wang, Dongliang; Corsetti, Sabrina M; Baer, Thomas M; Eisenberg, Marisa C; Falb, Karl; Huang, Yitao; Martin, Emily T; McCauley, Ella; Myers, Robert L; Schwarz, Tom; Sheldon, Daniel; Gibson, Graham Casey; Yu, Rose; Gao, Liyao; Ma, Yian; Wu, Dongxia; Yan, Xifeng; Jin, Xiaoyong; Wang, Yu-Xiang; Chen, YangQuan; Guo, Lihong; Zhao, Yanting; Gu, Quanquan; Chen, Jinghui; Wang, Lingxiao; Xu, Pan; Zhang, Weitong; Zou, Difan; Biegel, Hannah; Lega, Joceline; McConnell, Steve; Nagraj, V P; Guertin, Stephanie L; Hulme-Lowe, Christopher; Turner, Stephen D; Shi, Yunfeng; Ban, Xuegang; Walraven, Robert; Hong, Qi-Jun; Kong, Stanley; van de Walle, Axel; Turtle, James A; Ben-Nun, Michal; Riley, Steven; Riley, Pete; Koyluoglu, Ugur; DesRoches, David; Forli, Pedro; Hamory, Bruce; Kyriakides, Christina; Leis, Helen; Milliken, John; Moloney, Michael; Morgan, James; Nirgudkar, Ninad; Ozcan, Gokce; Piwonka, Noah; Ravi, Matt; Schrader, Chris; Shakhnovich, Elizabeth; Siegel, Daniel; Spatz, Ryan; Stiefeling, Chris; Wilkinson, Barrie; Wong, Alexander; Cavany, Sean; España, Guido; Moore, Sean; Oidtman, Rachel; Perkins, Alex; Kraus, David; Kraus, Andrea; Gao, Zhifeng; Bian, Jiang; Cao, Wei; Ferres, Juan Lavista; Li, Chaozhuo; Liu, Tie-Yan; Xie, Xing; Zhang, Shun; Zheng, Shun; Vespignani, Alessandro; Chinazzi, Matteo; Davis, Jessica T; Mu, Kunpeng; Piontti, Ana Pastore Y; Xiong, Xinyue; Zheng, Andrew; Baek, Jackie; Farias, Vivek; Georgescu, Andreea; Levi, Retsef; Sinha, Deeksha; Wilde, Joshua; Perakis, Georgia; Bennouna, Mohammed Amine; Nze-Ndong, David; Singhvi, Divya; Spantidakis, Ioannis; Thayaparan, Leann; Tsiourvas, Asterios; Sarker, Arnab; Jadbabaie, Ali; Shah, Devavrat; Penna, Nicolas Della; Celi, Leo A; Sundar, Saketh; Wolfinger, Russ; Osthus, Dave; Castro, Lauren; Fairchild, Geoffrey; Michaud, Isaac; Karlen, Dean; Kinsey, Matt; Mullany, Luke C; Rainwater-Lovett, Kaitlin; Shin, Lauren; Tallaksen, Katharine; Wilson, Shelby; Lee, Elizabeth C; Dent, Juan; Grantz, Kyra H; Hill, Alison L; Kaminsky, Joshua; Kaminsky, Kathryn; Keegan, Lindsay T; Lauer, Stephen A; Lemaitre, Joseph C; Lessler, Justin; Meredith, Hannah R; Perez-Saez, Javier; Shah, Sam; Smith, Claire P; Truelove, Shaun A; Wills, Josh; Marshall, Maximilian; Gardner, Lauren; Nixon, Kristen; Burant, John C; Wang, Lily; Gao, Lei; Gu, Zhiling; Kim, Myungjin; Li, Xinyi; Wang, Guannan; Wang, Yueying; Yu, Shan; Reiner, Robert C; Barber, Ryan; Gakidou, Emmanuela; Hay, Simon I; Lim, Steve; Murray, Chris; Pigott, David; Gurung, Heidi L; Baccam, Prasith; Stage, Steven A; Suchoski, Bradley T; Prakash, B Aditya; Adhikari, Bijaya; Cui, Jiaming; Rodríguez, Alexander; Tabassum, Anika; Xie, Jiajia; Keskinocak, Pinar; Asplund, John; Baxter, Arden; Oruc, Buse Eylul; Serban, Nicoleta; Arik, Sercan O; Dusenberry, Mike; Epshteyn, Arkady; Kanal, Elli; Le, Long T; Li, Chun-Liang; Pfister, Tomas; Sava, Dario; Sinha, Rajarishi; Tsai, Thomas; Yoder, Nate; Yoon, Jinsung; Zhang, Leyou; Abbott, Sam; Bosse, Nikos I; Funk, Sebastian; Hellewell, Joel; Meakin, Sophie R; Sherratt, Katharine; Zhou, Mingyuan; Kalantari, Rahi; Yamana, Teresa K; Pei, Sen; Shaman, Jeffrey; Li, Michael L; Bertsimas, Dimitris; Lami, Omar Skali; Soni, Saksham; Bouardi, Hamza Tazi; Ayer, Turgay; Adee, Madeline; Chhatwal, Jagpreet; Dalgic, Ozden O; Ladd, Mary A; Linas, Benjamin P; Mueller, Peter; Xiao, Jade; Wang, Yuanjia; Wang, Qinxia; Xie, Shanghong; Zeng, Donglin; Green, Alden; Bien, Jacob; Brooks, Logan; Hu, Addison J; Jahja, Maria; McDonald, Daniel; Narasimhan, Balasubramanian; Politsch, Collin; Rajanala, Samyak; Rumack, Aaron; Simon, Noah; Tibshirani, Ryan J; Tibshirani, Rob; Ventura, Valerie; Wasserman, Larry; O'Dea, Eamon B; Drake, John M; Pagano, Robert; Tran, Quoc T; Ho, Lam Si Tung; Huynh, Huong; Walker, Jo W; Slayton, Rachel B; Johansson, Michael A; Biggerstaff, Matthew; Reich, Nicholas G
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States Journal Article
In: Proc Natl Acad Sci U S A, vol. 119, no. 15, pp. e2113561119, 2022, ISSN: 1091-6490.
@article{pmid35394862,
title = {Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States},
author = {Estee Y Cramer and Evan L Ray and Velma K Lopez and Johannes Bracher and Andrea Brennen and Alvaro J Castro Rivadeneira and Aaron Gerding and Tilmann Gneiting and Katie H House and Yuxin Huang and Dasuni Jayawardena and Abdul H Kanji and Ayush Khandelwal and Khoa Le and Anja M\"{u}hlemann and Jarad Niemi and Apurv Shah and Ariane Stark and Yijin Wang and Nutcha Wattanachit and Martha W Zorn and Youyang Gu and Sansiddh Jain and Nayana Bannur and Ayush Deva and Mihir Kulkarni and Srujana Merugu and Alpan Raval and Siddhant Shingi and Avtansh Tiwari and Jerome White and Neil F Abernethy and Spencer Woody and Maytal Dahan and Spencer Fox and Kelly Gaither and Michael Lachmann and Lauren Ancel Meyers and James G Scott and Mauricio Tec and Ajitesh Srivastava and Glover E George and Jeffrey C Cegan and Ian D Dettwiller and William P England and Matthew W Farthing and Robert H Hunter and Brandon Lafferty and Igor Linkov and Michael L Mayo and Matthew D Parno and Michael A Rowland and Benjamin D Trump and Yanli Zhang-James and Samuel Chen and Stephen V Faraone and Jonathan Hess and Christopher P Morley and Asif Salekin and Dongliang Wang and Sabrina M Corsetti and Thomas M Baer and Marisa C Eisenberg and Karl Falb and Yitao Huang and Emily T Martin and Ella McCauley and Robert L Myers and Tom Schwarz and Daniel Sheldon and Graham Casey Gibson and Rose Yu and Liyao Gao and Yian Ma and Dongxia Wu and Xifeng Yan and Xiaoyong Jin and Yu-Xiang Wang and YangQuan Chen and Lihong Guo and Yanting Zhao and Quanquan Gu and Jinghui Chen and Lingxiao Wang and Pan Xu and Weitong Zhang and Difan Zou and Hannah Biegel and Joceline Lega and Steve McConnell and V P Nagraj and Stephanie L Guertin and Christopher Hulme-Lowe and Stephen D Turner and Yunfeng Shi and Xuegang Ban and Robert Walraven and Qi-Jun Hong and Stanley Kong and Axel van de Walle and James A Turtle and Michal Ben-Nun and Steven Riley and Pete Riley and Ugur Koyluoglu and David DesRoches and Pedro Forli and Bruce Hamory and Christina Kyriakides and Helen Leis and John Milliken and Michael Moloney and James Morgan and Ninad Nirgudkar and Gokce Ozcan and Noah Piwonka and Matt Ravi and Chris Schrader and Elizabeth Shakhnovich and Daniel Siegel and Ryan Spatz and Chris Stiefeling and Barrie Wilkinson and Alexander Wong and Sean Cavany and Guido Espa\~{n}a and Sean Moore and Rachel Oidtman and Alex Perkins and David Kraus and Andrea Kraus and Zhifeng Gao and Jiang Bian and Wei Cao and Juan Lavista Ferres and Chaozhuo Li and Tie-Yan Liu and Xing Xie and Shun Zhang and Shun Zheng and Alessandro Vespignani and Matteo Chinazzi and Jessica T Davis and Kunpeng Mu and Ana Pastore Y Piontti and Xinyue Xiong and Andrew Zheng and Jackie Baek and Vivek Farias and Andreea Georgescu and Retsef Levi and Deeksha Sinha and Joshua Wilde and Georgia Perakis and Mohammed Amine Bennouna and David Nze-Ndong and Divya Singhvi and Ioannis Spantidakis and Leann Thayaparan and Asterios Tsiourvas and Arnab Sarker and Ali Jadbabaie and Devavrat Shah and Nicolas Della Penna and Leo A Celi and Saketh Sundar and Russ Wolfinger and Dave Osthus and Lauren Castro and Geoffrey Fairchild and Isaac Michaud and Dean Karlen and Matt Kinsey and Luke C Mullany and Kaitlin Rainwater-Lovett and Lauren Shin and Katharine Tallaksen and Shelby Wilson and Elizabeth C Lee and Juan Dent and Kyra H Grantz and Alison L Hill and Joshua Kaminsky and Kathryn Kaminsky and Lindsay T Keegan and Stephen A Lauer and Joseph C Lemaitre and Justin Lessler and Hannah R Meredith and Javier Perez-Saez and Sam Shah and Claire P Smith and Shaun A Truelove and Josh Wills and Maximilian Marshall and Lauren Gardner and Kristen Nixon and John C Burant and Lily Wang and Lei Gao and Zhiling Gu and Myungjin Kim and Xinyi Li and Guannan Wang and Yueying Wang and Shan Yu and Robert C Reiner and Ryan Barber and Emmanuela Gakidou and Simon I Hay and Steve Lim and Chris Murray and David Pigott and Heidi L Gurung and Prasith Baccam and Steven A Stage and Bradley T Suchoski and B Aditya Prakash and Bijaya Adhikari and Jiaming Cui and Alexander Rodr\'{i}guez and Anika Tabassum and Jiajia Xie and Pinar Keskinocak and John Asplund and Arden Baxter and Buse Eylul Oruc and Nicoleta Serban and Sercan O Arik and Mike Dusenberry and Arkady Epshteyn and Elli Kanal and Long T Le and Chun-Liang Li and Tomas Pfister and Dario Sava and Rajarishi Sinha and Thomas Tsai and Nate Yoder and Jinsung Yoon and Leyou Zhang and Sam Abbott and Nikos I Bosse and Sebastian Funk and Joel Hellewell and Sophie R Meakin and Katharine Sherratt and Mingyuan Zhou and Rahi Kalantari and Teresa K Yamana and Sen Pei and Jeffrey Shaman and Michael L Li and Dimitris Bertsimas and Omar Skali Lami and Saksham Soni and Hamza Tazi Bouardi and Turgay Ayer and Madeline Adee and Jagpreet Chhatwal and Ozden O Dalgic and Mary A Ladd and Benjamin P Linas and Peter Mueller and Jade Xiao and Yuanjia Wang and Qinxia Wang and Shanghong Xie and Donglin Zeng and Alden Green and Jacob Bien and Logan Brooks and Addison J Hu and Maria Jahja and Daniel McDonald and Balasubramanian Narasimhan and Collin Politsch and Samyak Rajanala and Aaron Rumack and Noah Simon and Ryan J Tibshirani and Rob Tibshirani and Valerie Ventura and Larry Wasserman and Eamon B O'Dea and John M Drake and Robert Pagano and Quoc T Tran and Lam Si Tung Ho and Huong Huynh and Jo W Walker and Rachel B Slayton and Michael A Johansson and Matthew Biggerstaff and Nicholas G Reich},
doi = {10.1073/pnas.2113561119},
issn = {1091-6490},
year = {2022},
date = {2022-04-01},
journal = {Proc Natl Acad Sci U S A},
volume = {119},
number = {15},
pages = {e2113561119},
abstract = {SignificanceThis paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the United States. Results show high variation in accuracy between and within stand-alone models and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public-health action.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
SignificanceThis paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the United States. Results show high variation in accuracy between and within stand-alone models and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public-health action.
Liao, Che-Yi; Garcia, Gian-Gabriel P; DiGennaro, Catherine; Jalali, Mohammad S
Racial Disparities in Opioid Overdose Deaths in Massachusetts Journal Article
In: JAMA Netw Open, vol. 5, no. 4, pp. e229081, 2022, ISSN: 2574-3805.
@article{pmid35482312,
title = {Racial Disparities in Opioid Overdose Deaths in Massachusetts},
author = {Che-Yi Liao and Gian-Gabriel P Garcia and Catherine DiGennaro and Mohammad S Jalali},
doi = {10.1001/jamanetworkopen.2022.9081},
issn = {2574-3805},
year = {2022},
date = {2022-04-01},
journal = {JAMA Netw Open},
volume = {5},
number = {4},
pages = {e229081},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Jahn, Beate; Friedrich, Sarah; Behnke, Joachim; Engel, Joachim; Garczarek, Ursula; Münnich, Ralf; Pauly, Markus; Wilhelm, Adalbert; Wolkenhauer, Olaf; Zwick, Markus; Siebert, Uwe; Friede, Tim
On the role of data, statistics and decisions in a pandemic Journal Article
In: Adv Stat Anal, pp. 1–34, 2022, ISSN: 1863-8171.
@article{pmid35432617,
title = {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/s10182-022-00439-7},
issn = {1863-8171},
year = {2022},
date = {2022-04-01},
journal = {Adv Stat Anal},
pages = {1--34},
abstract = {A pandemic poses particular challenges to decision-making because of the need to continuously adapt decisions to rapidly changing evidence and available data. For example, which countermeasures are appropriate at a particular stage of the pandemic? How can the severity of the pandemic be measured? What is the effect of vaccination in the population and which groups should be vaccinated first? The process of decision-making starts with data collection and modeling and continues to the dissemination of results and the subsequent decisions taken. The goal of this paper is to give an overview of this process and to provide recommendations for the different steps from a statistical perspective. In particular, we discuss a range of modeling techniques including mathematical, statistical and decision-analytic models along with their applications in the COVID-19 context. With this overview, we aim to foster the understanding of the goals of these modeling approaches and the specific data requirements that are essential for the interpretation of results and for successful interdisciplinary collaborations. A special focus is on the role played by data in these different models, and we incorporate into the discussion the importance of statistical literacy and of effective dissemination and communication of findings.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A pandemic poses particular challenges to decision-making because of the need to continuously adapt decisions to rapidly changing evidence and available data. For example, which countermeasures are appropriate at a particular stage of the pandemic? How can the severity of the pandemic be measured? What is the effect of vaccination in the population and which groups should be vaccinated first? The process of decision-making starts with data collection and modeling and continues to the dissemination of results and the subsequent decisions taken. The goal of this paper is to give an overview of this process and to provide recommendations for the different steps from a statistical perspective. In particular, we discuss a range of modeling techniques including mathematical, statistical and decision-analytic models along with their applications in the COVID-19 context. With this overview, we aim to foster the understanding of the goals of these modeling approaches and the specific data requirements that are essential for the interpretation of results and for successful interdisciplinary collaborations. A special focus is on the role played by data in these different models, and we incorporate into the discussion the importance of statistical literacy and of effective dissemination and communication of findings.
Krumeich, Lauren N; Roses, Robert E; Kuo, Lindsay E; Lindeman, Brenessa M; Nehs, Matthew A; Tavakkoli, Ali; Parangi, Sareh; Hodin, Richard A; Fraker, Douglas L; James, Benjamin C; Wang, Tracy S; Solórzano, Carmen C; Lubitz, Carrie C; Wachtel, Heather
ASO Visual Abstract: Survival After Adrenalectomy for Metastatic Lung Cancer Journal Article
In: Ann Surg Oncol, vol. 29, iss. 4, pp. 2580-2581, 2022, ISSN: 1534-4681.
@article{pmid35094187,
title = {ASO Visual Abstract: Survival After Adrenalectomy for Metastatic Lung Cancer},
author = {Lauren N Krumeich and Robert E Roses and Lindsay E Kuo and Brenessa M Lindeman and Matthew A Nehs and Ali Tavakkoli and Sareh Parangi and Richard A Hodin and Douglas L Fraker and Benjamin C James and Tracy S Wang and Carmen C Sol\'{o}rzano and Carrie C Lubitz and Heather Wachtel},
url = {https://pubmed.ncbi.nlm.nih.gov/35094187/},
doi = {10.1245/s10434-021-11282-6},
issn = {1534-4681},
year = {2022},
date = {2022-04-01},
urldate = {2022-01-01},
journal = {Ann Surg Oncol},
volume = {29},
issue = {4},
pages = {2580-2581},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Krumeich, Lauren N; Roses, Robert E; Kuo, Lindsay E; Lindeman, Brenessa M; Nehs, Matthew A; Tavakkoli, Ali; Parangi, Sareh; Hodin, Richard A; Fraker, Douglas L; James, Benjamin C; Wang, Tracy S; Solórzano, Carmen C; Lubitz, Carrie C; Wachtel, Heather
Survival After Adrenalectomy for Metastatic Lung Cancer Journal Article
In: Ann Surg Oncol, vol. 29, iss. 4, pp. 2571-2579, 2022, ISSN: 1534-4681.
@article{pmid34989938,
title = {Survival After Adrenalectomy for Metastatic Lung Cancer},
author = {Lauren N Krumeich and Robert E Roses and Lindsay E Kuo and Brenessa M Lindeman and Matthew A Nehs and Ali Tavakkoli and Sareh Parangi and Richard A Hodin and Douglas L Fraker and Benjamin C James and Tracy S Wang and Carmen C Sol\'{o}rzano and Carrie C Lubitz and Heather Wachtel},
doi = {10.1245/s10434-021-11192-7},
issn = {1534-4681},
year = {2022},
date = {2022-04-01},
urldate = {2022-01-01},
journal = {Ann Surg Oncol},
volume = {29},
issue = {4},
pages = {2571-2579},
abstract = {BACKGROUND: Adrenal metastasectomy is associated with increased survival in non-small cell lung cancer (NSCLC) with isolated adrenal metastases. Although clinical use of adrenal metastasectomy has expanded, indications remain poorly defined. The aim of this study was to evaluate the clinical benefit of adrenal metastasectomy for all lung cancer subtypes.
PATIENTS AND METHODS: We performed a retrospective cohort study of patients who underwent adrenal metastasectomy for metastatic lung cancer at six institutions between 2001 and 2015. The primary outcomes were disease-free survival (DFS) and overall survival (OS). Cox proportional hazards regressions and Kaplan-Meier survival analysis were performed.
RESULTS: For 122 patients, the mean age was 60.5 years and 49.2% were female. Median time to detection of the metastasis was 11 months, and 41.8% were ipsilateral to the primary lung cancer. Median DFS was 40 months (1 year: 64.8%; 5 year: 42.9%). Factors associated with longer DFS included primary tumor resection [hazard ratio (HR): 0.001; p = 0.005], longer time to adrenal metastasis (HR: 0.94; p = 0.005), and ipsilateral metastases (HR: 0.13; p = 0.004). Shorter DFS corresponded with older age (HR: 1.11; p = 0.01), R1 resection (HR: 8.94; p = 0.01), adjuvant radiation (HR: 9.45; p = 0.02), and open adrenal metastasectomy (HR: 10.0; p = 0.03). Median OS was 47 months (1 year: 80.2%; 5 year: 35.2%). Longer OS was associated with ipsilateral metastasis (HR: 0.55; p = 0.02) and adjuvant chemotherapy (HR: 0.35; p = 0.02). Shorter OS was associated with extra-adrenal metastases at adrenalectomy (HR: 3.52; p = 0.007), small cell histology (HR: 15.0; p = 0.04), and lung radiation (HR: 3.37; p = 0.002).
DISCUSSION: Durable survival was observed in patients undergoing adrenal metastasectomy and should be considered for isolated adrenal metastases of NSCLC. Small cell histology and extra-adrenal metastases are relative contraindications to adrenal metastasectomy.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: Adrenal metastasectomy is associated with increased survival in non-small cell lung cancer (NSCLC) with isolated adrenal metastases. Although clinical use of adrenal metastasectomy has expanded, indications remain poorly defined. The aim of this study was to evaluate the clinical benefit of adrenal metastasectomy for all lung cancer subtypes.
PATIENTS AND METHODS: We performed a retrospective cohort study of patients who underwent adrenal metastasectomy for metastatic lung cancer at six institutions between 2001 and 2015. The primary outcomes were disease-free survival (DFS) and overall survival (OS). Cox proportional hazards regressions and Kaplan-Meier survival analysis were performed.
RESULTS: For 122 patients, the mean age was 60.5 years and 49.2% were female. Median time to detection of the metastasis was 11 months, and 41.8% were ipsilateral to the primary lung cancer. Median DFS was 40 months (1 year: 64.8%; 5 year: 42.9%). Factors associated with longer DFS included primary tumor resection [hazard ratio (HR): 0.001; p = 0.005], longer time to adrenal metastasis (HR: 0.94; p = 0.005), and ipsilateral metastases (HR: 0.13; p = 0.004). Shorter DFS corresponded with older age (HR: 1.11; p = 0.01), R1 resection (HR: 8.94; p = 0.01), adjuvant radiation (HR: 9.45; p = 0.02), and open adrenal metastasectomy (HR: 10.0; p = 0.03). Median OS was 47 months (1 year: 80.2%; 5 year: 35.2%). Longer OS was associated with ipsilateral metastasis (HR: 0.55; p = 0.02) and adjuvant chemotherapy (HR: 0.35; p = 0.02). Shorter OS was associated with extra-adrenal metastases at adrenalectomy (HR: 3.52; p = 0.007), small cell histology (HR: 15.0; p = 0.04), and lung radiation (HR: 3.37; p = 0.002).
DISCUSSION: Durable survival was observed in patients undergoing adrenal metastasectomy and should be considered for isolated adrenal metastases of NSCLC. Small cell histology and extra-adrenal metastases are relative contraindications to adrenal metastasectomy.
PATIENTS AND METHODS: We performed a retrospective cohort study of patients who underwent adrenal metastasectomy for metastatic lung cancer at six institutions between 2001 and 2015. The primary outcomes were disease-free survival (DFS) and overall survival (OS). Cox proportional hazards regressions and Kaplan-Meier survival analysis were performed.
RESULTS: For 122 patients, the mean age was 60.5 years and 49.2% were female. Median time to detection of the metastasis was 11 months, and 41.8% were ipsilateral to the primary lung cancer. Median DFS was 40 months (1 year: 64.8%; 5 year: 42.9%). Factors associated with longer DFS included primary tumor resection [hazard ratio (HR): 0.001; p = 0.005], longer time to adrenal metastasis (HR: 0.94; p = 0.005), and ipsilateral metastases (HR: 0.13; p = 0.004). Shorter DFS corresponded with older age (HR: 1.11; p = 0.01), R1 resection (HR: 8.94; p = 0.01), adjuvant radiation (HR: 9.45; p = 0.02), and open adrenal metastasectomy (HR: 10.0; p = 0.03). Median OS was 47 months (1 year: 80.2%; 5 year: 35.2%). Longer OS was associated with ipsilateral metastasis (HR: 0.55; p = 0.02) and adjuvant chemotherapy (HR: 0.35; p = 0.02). Shorter OS was associated with extra-adrenal metastases at adrenalectomy (HR: 3.52; p = 0.007), small cell histology (HR: 15.0; p = 0.04), and lung radiation (HR: 3.37; p = 0.002).
DISCUSSION: Durable survival was observed in patients undergoing adrenal metastasectomy and should be considered for isolated adrenal metastases of NSCLC. Small cell histology and extra-adrenal metastases are relative contraindications to adrenal metastasectomy.
Tatar, Moosa; Jalali, Mohammad S.; Tak, Hyo Jung; Chen, Li-Wu; Araz, Ozgur M; Wilson, Fernando A
Impact of Florida's prescription drug monitoring program on drug- related fatal vehicle crashes: a difference-in-differences approach. Journal Article
In: Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention, vol. 28, iss. 2, pp. 105-107, 2022, ISSN: 1475-5785.
@article{Tatar2021,
title = {Impact of Florida's prescription drug monitoring program on drug- related fatal vehicle crashes: a difference-in-differences approach.},
author = {Moosa Tatar and Mohammad S. Jalali and Hyo Jung Tak and Li-Wu Chen and Ozgur M Araz and Fernando A Wilson},
url = {https://pubmed.ncbi.nlm.nih.gov/34162702/},
doi = {10.1136/injuryprev-2020-044113},
issn = {1475-5785},
year = {2022},
date = {2022-04-01},
urldate = {2021-06-01},
journal = {Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention},
volume = {28},
issue = {2},
pages = {105-107},
abstract = {Prescription drug use has soared in the USA within the last two decades. Prescription drugs can impair motor skills essential for the safe operation of a motor vehicle, and therefore can affect traffic safety. As one of the epicentres of the opioid epidemic, Florida has been struck by high opioid misuse and overdose rates, and has concurrently suffered major threats to traffic disruptions safety caused by driving under the influence of drugs. To prevent prescription opioid misuse in Florida, Prescription Drug Monitoring Programs (PDMPs) were implemented in September 2011. To examine the impact of Florida's implementation of a mandatory PDMP on drug-related MVCs occurring on public roads. We employed a difference-in-differences approach to estimate the difference in prescription drug-related fatal crashes in Florida associated with its 2011 PDMP implementation relative to those in Georgia, which did not use PDMPs during the same period (2009-2013). The analyses were conducted in 2020. In Florida, there was a significant decline in drug-related vehicle crashes during the 22 months post-PDMP. PDMP implementation was associated with approximately two (-2.21; 95% CI -4.04 to -0.37; p<0.05) fewer prescribed opioid-related fatal crashes every month, indicating 25% reduction in the number of monthly crashes. We conducted sensitivity analyses to investigate the impact of PDMP implementation on central nervous system depressants and stimulants as well as cocaine and marijuana-related fatal crashes but found no robust significant reductions. The implementation of PDMPs in Florida provided important benefits for traffic safety, reducing the rates of prescription opioid-related vehicle crashes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Prescription drug use has soared in the USA within the last two decades. Prescription drugs can impair motor skills essential for the safe operation of a motor vehicle, and therefore can affect traffic safety. As one of the epicentres of the opioid epidemic, Florida has been struck by high opioid misuse and overdose rates, and has concurrently suffered major threats to traffic disruptions safety caused by driving under the influence of drugs. To prevent prescription opioid misuse in Florida, Prescription Drug Monitoring Programs (PDMPs) were implemented in September 2011. To examine the impact of Florida's implementation of a mandatory PDMP on drug-related MVCs occurring on public roads. We employed a difference-in-differences approach to estimate the difference in prescription drug-related fatal crashes in Florida associated with its 2011 PDMP implementation relative to those in Georgia, which did not use PDMPs during the same period (2009-2013). The analyses were conducted in 2020. In Florida, there was a significant decline in drug-related vehicle crashes during the 22 months post-PDMP. PDMP implementation was associated with approximately two (-2.21; 95% CI -4.04 to -0.37; p<0.05) fewer prescribed opioid-related fatal crashes every month, indicating 25% reduction in the number of monthly crashes. We conducted sensitivity analyses to investigate the impact of PDMP implementation on central nervous system depressants and stimulants as well as cocaine and marijuana-related fatal crashes but found no robust significant reductions. The implementation of PDMPs in Florida provided important benefits for traffic safety, reducing the rates of prescription opioid-related vehicle crashes.
Rainer, L J; Granbichler, C A; Kobulashvili, T; Kuchukhidze, G; Rauscher, C; Renz, N; Langthaler, P B; Braun, M; Linehan, C; Christensen, J; Siebert, U; Trinka, E
Prevalence of comorbidities, and affective disorders in epilepsy: A latent class analysis approach Journal Article
In: Epilepsy Res, vol. 182, pp. 106917, 2022, ISSN: 1872-6844.
@article{pmid35390702,
title = {Prevalence of comorbidities, and affective disorders in epilepsy: A latent class analysis approach},
author = {L J Rainer and C A Granbichler and T Kobulashvili and G Kuchukhidze and C Rauscher and N Renz and P B Langthaler and M Braun and C Linehan and J Christensen and U Siebert and E Trinka},
doi = {10.1016/j.eplepsyres.2022.106917},
issn = {1872-6844},
year = {2022},
date = {2022-03-01},
journal = {Epilepsy Res},
volume = {182},
pages = {106917},
abstract = {OBJECTIVE: Epilepsies are severe chronic neurological diseases that impair several domains in life and are often accompanied by various somatic and psychiatric comorbidities. Associations between epilepsy and its comorbidities remain poorly understood. As epidemiological research mainly relies on cross-sectional designs and descriptive results, homogeneities regarding comorbidities in individuals suffering from epilepsy remain uncovered. Therefore, we aimed to identify clusters of individuals based on selected seizure-related variables and somatic comorbidities, and their respective risk of experiencing affective disorders, using a Latent Class Analysis (LCA).
METHODS: Latent class analysis, is a model-driven statistical approach, which aims at latent, unobservable clusters on selected disease features. LCA has therefore the potential for uncovering previously unobservable groups or classes with similar comorbidity patterns. It allows for comparisons between those classes regarding risk or promotive factors - such as affective disorders. Our data derives from the Austrian cohort of the European Study on Burden and Care of Epilepsy (ESBACE; http://www.esbace.eu/). In ESBACE, multiple factors were collected to get a detailed picture on prevalence, epilepsy-related variables and comorbidities in a population-based cohort from the region of Salzburg, Austria. We used LCA to identify epilepsy-somatic-comorbidity-clusters and further, compared them to the observed the risk of suffering from affective disorders.
RESULTS: The prevalence of epilepsy in the study region was 9.14/1000 inhabitants. LCA unveiled a three-cluster solution, of which one cluster, mainly consisting of individuals with mixed seizure types, higher age, and discrete somatic comorbidities (stroke, cardiovascular - and respiratory/pulmonary diseases) had a higher risk of experiencing affective disorders.
SIGNIFICANCE: To our knowledge, this is the first large scale study that uses LCA to identify epilepsy-related comorbidity phenotypes, and therefore it might open a new way for epidemiological research.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
OBJECTIVE: Epilepsies are severe chronic neurological diseases that impair several domains in life and are often accompanied by various somatic and psychiatric comorbidities. Associations between epilepsy and its comorbidities remain poorly understood. As epidemiological research mainly relies on cross-sectional designs and descriptive results, homogeneities regarding comorbidities in individuals suffering from epilepsy remain uncovered. Therefore, we aimed to identify clusters of individuals based on selected seizure-related variables and somatic comorbidities, and their respective risk of experiencing affective disorders, using a Latent Class Analysis (LCA).
METHODS: Latent class analysis, is a model-driven statistical approach, which aims at latent, unobservable clusters on selected disease features. LCA has therefore the potential for uncovering previously unobservable groups or classes with similar comorbidity patterns. It allows for comparisons between those classes regarding risk or promotive factors - such as affective disorders. Our data derives from the Austrian cohort of the European Study on Burden and Care of Epilepsy (ESBACE; http://www.esbace.eu/). In ESBACE, multiple factors were collected to get a detailed picture on prevalence, epilepsy-related variables and comorbidities in a population-based cohort from the region of Salzburg, Austria. We used LCA to identify epilepsy-somatic-comorbidity-clusters and further, compared them to the observed the risk of suffering from affective disorders.
RESULTS: The prevalence of epilepsy in the study region was 9.14/1000 inhabitants. LCA unveiled a three-cluster solution, of which one cluster, mainly consisting of individuals with mixed seizure types, higher age, and discrete somatic comorbidities (stroke, cardiovascular - and respiratory/pulmonary diseases) had a higher risk of experiencing affective disorders.
SIGNIFICANCE: To our knowledge, this is the first large scale study that uses LCA to identify epilepsy-related comorbidity phenotypes, and therefore it might open a new way for epidemiological research.
METHODS: Latent class analysis, is a model-driven statistical approach, which aims at latent, unobservable clusters on selected disease features. LCA has therefore the potential for uncovering previously unobservable groups or classes with similar comorbidity patterns. It allows for comparisons between those classes regarding risk or promotive factors - such as affective disorders. Our data derives from the Austrian cohort of the European Study on Burden and Care of Epilepsy (ESBACE; http://www.esbace.eu/). In ESBACE, multiple factors were collected to get a detailed picture on prevalence, epilepsy-related variables and comorbidities in a population-based cohort from the region of Salzburg, Austria. We used LCA to identify epilepsy-somatic-comorbidity-clusters and further, compared them to the observed the risk of suffering from affective disorders.
RESULTS: The prevalence of epilepsy in the study region was 9.14/1000 inhabitants. LCA unveiled a three-cluster solution, of which one cluster, mainly consisting of individuals with mixed seizure types, higher age, and discrete somatic comorbidities (stroke, cardiovascular - and respiratory/pulmonary diseases) had a higher risk of experiencing affective disorders.
SIGNIFICANCE: To our knowledge, this is the first large scale study that uses LCA to identify epilepsy-related comorbidity phenotypes, and therefore it might open a new way for epidemiological research.
Rajakumar, Timothy; Horos, Rastislav; Jehn, Julia; Schenz, Judith; Muley, Thomas; Pelea, Oana; Hofmann, Sarah; Kittner, Paul; Kahraman, Mustafa; Heuvelman, Marco; Sikosek, Tobias; Feufel, Jennifer; Skottke, Jasmin; Nötzel, Dennis; Hinkfoth, Franziska; Tikk, Kaja; Daniel-Moreno, Alberto; Ceiler, Jessika; Mercaldo, Nathaniel; Uhle, Florian; Uhle, Sandra; Weigand, Markus A; Elshiaty, Mariam; Lusky, Fabienne; Schindler, Hannah; Ferry, Quentin; Sauka-Spengler, Tatjana; Wu, Qianxin; Rabe, Klaus F; Reck, Martin; Thomas, Michael; Christopoulos, Petros; Steinkraus, Bruno R
A blood-based miRNA signature with prognostic value for overall survival in advanced stage non-small cell lung cancer treated with immunotherapy Journal Article
In: NPJ Precis Oncol, vol. 6, no. 1, pp. 19, 2022, ISSN: 2397-768X.
@article{pmid35361874,
title = {A blood-based miRNA signature with prognostic value for overall survival in advanced stage non-small cell lung cancer treated with immunotherapy},
author = {Timothy Rajakumar and Rastislav Horos and Julia Jehn and Judith Schenz and Thomas Muley and Oana Pelea and Sarah Hofmann and Paul Kittner and Mustafa Kahraman and Marco Heuvelman and Tobias Sikosek and Jennifer Feufel and Jasmin Skottke and Dennis N\"{o}tzel and Franziska Hinkfoth and Kaja Tikk and Alberto Daniel-Moreno and Jessika Ceiler and Nathaniel Mercaldo and Florian Uhle and Sandra Uhle and Markus A Weigand and Mariam Elshiaty and Fabienne Lusky and Hannah Schindler and Quentin Ferry and Tatjana Sauka-Spengler and Qianxin Wu and Klaus F Rabe and Martin Reck and Michael Thomas and Petros Christopoulos and Bruno R Steinkraus},
doi = {10.1038/s41698-022-00262-y},
issn = {2397-768X},
year = {2022},
date = {2022-03-01},
journal = {NPJ Precis Oncol},
volume = {6},
number = {1},
pages = {19},
abstract = {Immunotherapies have recently gained traction as highly effective therapies in a subset of late-stage cancers. Unfortunately, only a minority of patients experience the remarkable benefits of immunotherapies, whilst others fail to respond or even come to harm through immune-related adverse events. For immunotherapies within the PD-1/PD-L1 inhibitor class, patient stratification is currently performed using tumor (tissue-based) PD-L1 expression. However, PD-L1 is an accurate predictor of response in only ~30% of cases. There is pressing need for more accurate biomarkers for immunotherapy response prediction. We sought to identify peripheral blood biomarkers, predictive of response to immunotherapies against lung cancer, based on whole blood microRNA profiling. Using three well-characterized cohorts consisting of a total of 334 stage IV NSCLC patients, we have defined a 5 microRNA risk score (miRisk) that is predictive of overall survival following immunotherapy in training and independent validation (HR 2.40, 95% CI 1.37-4.19; P < 0.01) cohorts. We have traced the signature to a myeloid origin and performed miRNA target prediction to make a direct mechanistic link to the PD-L1 signaling pathway and PD-L1 itself. The miRisk score offers a potential blood-based companion diagnostic for immunotherapy that outperforms tissue-based PD-L1 staining.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Immunotherapies have recently gained traction as highly effective therapies in a subset of late-stage cancers. Unfortunately, only a minority of patients experience the remarkable benefits of immunotherapies, whilst others fail to respond or even come to harm through immune-related adverse events. For immunotherapies within the PD-1/PD-L1 inhibitor class, patient stratification is currently performed using tumor (tissue-based) PD-L1 expression. However, PD-L1 is an accurate predictor of response in only ~30% of cases. There is pressing need for more accurate biomarkers for immunotherapy response prediction. We sought to identify peripheral blood biomarkers, predictive of response to immunotherapies against lung cancer, based on whole blood microRNA profiling. Using three well-characterized cohorts consisting of a total of 334 stage IV NSCLC patients, we have defined a 5 microRNA risk score (miRisk) that is predictive of overall survival following immunotherapy in training and independent validation (HR 2.40, 95% CI 1.37-4.19; P < 0.01) cohorts. We have traced the signature to a myeloid origin and performed miRNA target prediction to make a direct mechanistic link to the PD-L1 signaling pathway and PD-L1 itself. The miRisk score offers a potential blood-based companion diagnostic for immunotherapy that outperforms tissue-based PD-L1 staining.
Adee, Madeline; Zhong, Huaiyang; Reipold, Elena Ivanova; Zhuo, Yueran; Shilton, Sonjelle; Chhatwal, Jagpreet
Cost-Effectiveness of a Core Antigen-Based Rapid Diagnostic Test for Hepatitis C Journal Article
In: Value Health, 2022, ISSN: 1524-4733.
@article{pmid35272954,
title = {Cost-Effectiveness of a Core Antigen-Based Rapid Diagnostic Test for Hepatitis C},
author = {Madeline Adee and Huaiyang Zhong and Elena Ivanova Reipold and Yueran Zhuo and Sonjelle Shilton and Jagpreet Chhatwal},
doi = {10.1016/j.jval.2022.01.004},
issn = {1524-4733},
year = {2022},
date = {2022-03-01},
journal = {Value Health},
abstract = {OBJECTIVES: Hepatitis C virus (HCV) affects 58 million worldwide and > 79% of people remain undiagnosed. Rapid diagnostic tests (RDTs) for HCV can help improve diagnosis and treatment rates. Nevertheless, the high price and infrastructure needed to use current molecular HCV RDT options present a barrier to widespread use-particularly in low- and middle-income countries. We evaluated the performance and cost-effectiveness of a theoretical core antigen (cAg) RDT for HCV viremia confirmation, which requires fewer resources.
METHODS: We adapted a previously validated microsimulation model to simulate HCV disease progression and outcomes under different HCV testing algorithms in Georgia and Malaysia. We compared standard of care testing with laboratory-based ribonucleic acid HCV to a cAg-based RDT for HCV confirmation. We simulated a cohort of 10 000 adults in each country, with an HCV-ribonucleic acid prevalence of 5.40% in Georgia and 1.54% in Malaysia. We projected the cumulative healthcare costs, quality-adjusted life-years, and diagnosis coverage rates over a lifetime horizon.
RESULTS: Compared with the standard of care testing, the cAg-based RDT would increase quality-adjusted life-years by 270 in Georgia and 259 in Malaysia per 10 000 people. The high diagnosis rate and treatment rate of the cAg-based RDT result in substantial cost savings because of averted HCV sequelae management costs. Cost savings are $281 000 for Georgia and $781 000 for Malaysia.
CONCLUSIONS: We found that a cAg-based RDT for HCV could improve the diagnosis rate and result in cost savings. Such a test could have a substantial impact on the feasibility and cost of HCV elimination.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
OBJECTIVES: Hepatitis C virus (HCV) affects 58 million worldwide and > 79% of people remain undiagnosed. Rapid diagnostic tests (RDTs) for HCV can help improve diagnosis and treatment rates. Nevertheless, the high price and infrastructure needed to use current molecular HCV RDT options present a barrier to widespread use-particularly in low- and middle-income countries. We evaluated the performance and cost-effectiveness of a theoretical core antigen (cAg) RDT for HCV viremia confirmation, which requires fewer resources.
METHODS: We adapted a previously validated microsimulation model to simulate HCV disease progression and outcomes under different HCV testing algorithms in Georgia and Malaysia. We compared standard of care testing with laboratory-based ribonucleic acid HCV to a cAg-based RDT for HCV confirmation. We simulated a cohort of 10 000 adults in each country, with an HCV-ribonucleic acid prevalence of 5.40% in Georgia and 1.54% in Malaysia. We projected the cumulative healthcare costs, quality-adjusted life-years, and diagnosis coverage rates over a lifetime horizon.
RESULTS: Compared with the standard of care testing, the cAg-based RDT would increase quality-adjusted life-years by 270 in Georgia and 259 in Malaysia per 10 000 people. The high diagnosis rate and treatment rate of the cAg-based RDT result in substantial cost savings because of averted HCV sequelae management costs. Cost savings are $281 000 for Georgia and $781 000 for Malaysia.
CONCLUSIONS: We found that a cAg-based RDT for HCV could improve the diagnosis rate and result in cost savings. Such a test could have a substantial impact on the feasibility and cost of HCV elimination.
METHODS: We adapted a previously validated microsimulation model to simulate HCV disease progression and outcomes under different HCV testing algorithms in Georgia and Malaysia. We compared standard of care testing with laboratory-based ribonucleic acid HCV to a cAg-based RDT for HCV confirmation. We simulated a cohort of 10 000 adults in each country, with an HCV-ribonucleic acid prevalence of 5.40% in Georgia and 1.54% in Malaysia. We projected the cumulative healthcare costs, quality-adjusted life-years, and diagnosis coverage rates over a lifetime horizon.
RESULTS: Compared with the standard of care testing, the cAg-based RDT would increase quality-adjusted life-years by 270 in Georgia and 259 in Malaysia per 10 000 people. The high diagnosis rate and treatment rate of the cAg-based RDT result in substantial cost savings because of averted HCV sequelae management costs. Cost savings are $281 000 for Georgia and $781 000 for Malaysia.
CONCLUSIONS: We found that a cAg-based RDT for HCV could improve the diagnosis rate and result in cost savings. Such a test could have a substantial impact on the feasibility and cost of HCV elimination.
Markby, Jessica; Gupta, Ekta; Soni, Divya; Sarin, Sanjay; Murya, Mugil; Katapur, Preetishirin; Tewatia, Navneet; Ramachandran, Babu Entoor; Ruiz, Ryan Jose; Geddart, Mary; Tyshkovskiy, Alex; Adee, Madeline; Chhatwal, Jagpreet; Miglani, Sundeep; Easterbrook, Philippa; Sarin, Shiv K.; Shilton, Sonjelle
Feasibility, effectiveness and cost of a decentralized HCV care model among the general population in Delhi, India. Journal Article
In: Liver international : official journal of the International Association for the Study of the Liver, vol. 42, iss. 3, pp. 532-540, 2022, ISSN: 1478-3231.
@article{Markby2021,
title = {Feasibility, effectiveness and cost of a decentralized HCV care model among the general population in Delhi, India.},
author = {Jessica Markby and Ekta Gupta and Divya Soni and Sanjay Sarin and Mugil Murya and Preetishirin Katapur and Navneet Tewatia and Babu Entoor Ramachandran and Ryan Jose Ruiz and Mary Geddart and Alex Tyshkovskiy and Madeline Adee and Jagpreet Chhatwal and Sundeep Miglani and Philippa Easterbrook and Shiv K. Sarin and Sonjelle Shilton},
url = {https://pubmed.ncbi.nlm.nih.gov/34817928/},
doi = {10.1111/liv.15112},
issn = {1478-3231},
year = {2022},
date = {2022-03-01},
urldate = {2021-11-01},
journal = {Liver international : official journal of the International Association for the Study of the Liver},
volume = {42},
issue = {3},
pages = {532-540},
abstract = {India has a significant burden of hepatitis C virus (HCV) infection and has committed to achieving national elimination by 2030. This will require a substantial scale-up in testing and treatment. The "HEAD-Start Project Delhi" aimed to enhance HCV diagnosis and treatment pathways among the general population. A prospective study was conducted at 5 district hospitals (Arm 1: one-stop shop), 15 polyclinics (Arm 2: referral for viral load (VL) testing and treatment), and 62 screening camps (Arm 3: referral for treatment). HCV prevalence, retention in the HCV care cascade, and turn-around time were measured. Between January and September 2019, 37,425 participants were screened for HCV. The median (IQR) age of participants was 35 (26-48) years, with 50.4% male and 49.6% female. A significantly higher proportion of participants in Arm 1 (93.7%) and Arm 3 (90.3%) received a VL test compared with Arm 2 (52.5%, P < 0.001). Of those confirmed positive, treatment was initiated at significantly higher rates for participants in both Arms 1 (85.6%) and 2 (73.7%) compared to Arm 3 (41.8%, P < 0.001). Arm 1 was found to be a cost-saving strategy compared to Arm 2, Arm 3, and no action. Delivery of all services at a single site (district hospitals) resulted in a higher yield of HCV seropositive cases and retention compared with sites where participants were referred elsewhere for VL testing and/or treatment. The highest level of retention in the care cascade was also associated with the shortest turn-around times.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
India has a significant burden of hepatitis C virus (HCV) infection and has committed to achieving national elimination by 2030. This will require a substantial scale-up in testing and treatment. The "HEAD-Start Project Delhi" aimed to enhance HCV diagnosis and treatment pathways among the general population. A prospective study was conducted at 5 district hospitals (Arm 1: one-stop shop), 15 polyclinics (Arm 2: referral for viral load (VL) testing and treatment), and 62 screening camps (Arm 3: referral for treatment). HCV prevalence, retention in the HCV care cascade, and turn-around time were measured. Between January and September 2019, 37,425 participants were screened for HCV. The median (IQR) age of participants was 35 (26-48) years, with 50.4% male and 49.6% female. A significantly higher proportion of participants in Arm 1 (93.7%) and Arm 3 (90.3%) received a VL test compared with Arm 2 (52.5%, P < 0.001). Of those confirmed positive, treatment was initiated at significantly higher rates for participants in both Arms 1 (85.6%) and 2 (73.7%) compared to Arm 3 (41.8%, P < 0.001). Arm 1 was found to be a cost-saving strategy compared to Arm 2, Arm 3, and no action. Delivery of all services at a single site (district hospitals) resulted in a higher yield of HCV seropositive cases and retention compared with sites where participants were referred elsewhere for VL testing and/or treatment. The highest level of retention in the care cascade was also associated with the shortest turn-around times.
Li, Peiyi; Luo, Yunmei; Yu, Xuexin; Mason, Elizabeth; Zeng, Zhi; Wen, Jin; Li, Weimin; Jalali, Mohammad S.
Readiness of healthcare providers for e-hospitals: a cross-sectional analysis in China before the COVID-19 period. Journal Article
In: BMJ open, vol. 12, iss. 2, pp. e054169, 2022, ISSN: 2044-6055.
@article{Li2022,
title = {Readiness of healthcare providers for e-hospitals: a cross-sectional analysis in China before the COVID-19 period.},
author = {Peiyi Li and Yunmei Luo and Xuexin Yu and Elizabeth Mason and Zhi Zeng and Jin Wen and Weimin Li and Mohammad S. Jalali},
url = {https://pubmed.ncbi.nlm.nih.gov/35190431/},
doi = {10.1136/bmjopen-2021-054169},
issn = {2044-6055},
year = {2022},
date = {2022-02-01},
journal = {BMJ open},
volume = {12},
issue = {2},
pages = {e054169},
abstract = {The growth and development of smartphones and eHealth technologies have enabled the potential for extended care hospitals (e-hospitals) in China in order to facilitate the success of a primary healthcare centre (PHC)-based integrated delivery model. Although the adoption of e-hospitals is essential, few studies have directed their research towards understanding the perspectives of healthcare providers. This study aims to identify the current readiness of healthcare providers to adopt e-hospital technologies, determine the factors influencing this adoption and describe the perceived facilitators and barriers in regard to working at e-hospitals. A cross-sectional study conducted in Sichuan, China, between June and September 2019. Information was collected from healthcare providers who have more than 3 years of work experience from a tertiary hospital, secondary hospital, PHCs and private hospital. 2298 medical professionals were included in this study. This study included a self-administered questionnaire that was used to assess participants' sociodemographic characteristics, online medical practices, willingness to use e-hospitals and perceived facilitators/barriers to working at e-hospitals. Multivariate regression analysis was performed in order to evaluate the independent factors associated with e-hospital work. Overall, 86.3% had a positive response towards working at e-hospitals. Age (p<0.05), familiarity with e-hospitals (p<0.001) and prior work practices in online healthcare settings (p<0.001) were associated with participants' readiness to work at e-hospitals. Gender, education level, professional level, the tier of their affiliated hospital and workload were not statistically associated. Healthcare providers who had positive attitudes towards e-hospitals considered improved efficiency, patient satisfaction, communication among physicians, increased reputation and income, and alleviated workload to be advantages of adoption. The participants who were unwilling to work at e-hospitals perceived lack of time, insufficient authenticity/reliability and underdeveloped policies as potential barriers. Improving operative proficiency in electronic devices, accommodating to work schedules, increasing familiarity with e-hospitals and regulating practices will improve the readiness of healthcare providers to work at e-hospitals.},
keywords = {},
pubstate = {epublish},
tppubtype = {article}
}
The growth and development of smartphones and eHealth technologies have enabled the potential for extended care hospitals (e-hospitals) in China in order to facilitate the success of a primary healthcare centre (PHC)-based integrated delivery model. Although the adoption of e-hospitals is essential, few studies have directed their research towards understanding the perspectives of healthcare providers. This study aims to identify the current readiness of healthcare providers to adopt e-hospital technologies, determine the factors influencing this adoption and describe the perceived facilitators and barriers in regard to working at e-hospitals. A cross-sectional study conducted in Sichuan, China, between June and September 2019. Information was collected from healthcare providers who have more than 3 years of work experience from a tertiary hospital, secondary hospital, PHCs and private hospital. 2298 medical professionals were included in this study. This study included a self-administered questionnaire that was used to assess participants' sociodemographic characteristics, online medical practices, willingness to use e-hospitals and perceived facilitators/barriers to working at e-hospitals. Multivariate regression analysis was performed in order to evaluate the independent factors associated with e-hospital work. Overall, 86.3% had a positive response towards working at e-hospitals. Age (p<0.05), familiarity with e-hospitals (p<0.001) and prior work practices in online healthcare settings (p<0.001) were associated with participants' readiness to work at e-hospitals. Gender, education level, professional level, the tier of their affiliated hospital and workload were not statistically associated. Healthcare providers who had positive attitudes towards e-hospitals considered improved efficiency, patient satisfaction, communication among physicians, increased reputation and income, and alleviated workload to be advantages of adoption. The participants who were unwilling to work at e-hospitals perceived lack of time, insufficient authenticity/reliability and underdeveloped policies as potential barriers. Improving operative proficiency in electronic devices, accommodating to work schedules, increasing familiarity with e-hospitals and regulating practices will improve the readiness of healthcare providers to work at e-hospitals.
Adee, Madeline; Zhuo, Yueran; Zhong, Huaiyang; Zhan, Tiannan; Aggarwal, Rakesh; Shilton, Sonjelle; Chhatwal, Jagpreet
Author Correction: Assessing cost-effectiveness of hepatitis C testing pathways in Georgia using the Hep C Testing Calculator. Journal Article
In: Scientific reports, vol. 12, iss. 1, pp. 3101, 2022, ISSN: 2045-2322.
@article{Adee2022,
title = {Author Correction: Assessing cost-effectiveness of hepatitis C testing pathways in Georgia using the Hep C Testing Calculator.},
author = {Madeline Adee and Yueran Zhuo and Huaiyang Zhong and Tiannan Zhan and Rakesh Aggarwal and Sonjelle Shilton and Jagpreet Chhatwal},
url = {https://pubmed.ncbi.nlm.nih.gov/35177757/},
doi = {10.1038/s41598-022-07001-0},
issn = {2045-2322},
year = {2022},
date = {2022-02-01},
journal = {Scientific reports},
volume = {12},
issue = {1},
pages = {3101},
keywords = {},
pubstate = {epublish},
tppubtype = {article}
}
Petranovic, Milena; Raoof, Sana; Digumarthy, Subba R.; Sharma, Amita; Shepard, Jo-Anne O.; Gainor, Justin F.; Pandharipande, Pari V.
Liquid Biopsy, Diagnostic Imaging, and Future Synergies. Journal Article
In: Journal of the American College of Radiology : JACR, vol. 19, iss. 2 Pt B, pp. 336–343, 2022, ISSN: 1558-349X.
@article{Petranovic2022,
title = {Liquid Biopsy, Diagnostic Imaging, and Future Synergies.},
author = {Milena Petranovic and Sana Raoof and Subba R. Digumarthy and Amita Sharma and Jo-Anne O. Shepard and Justin F. Gainor and Pari V. Pandharipande},
url = {https://pubmed.ncbi.nlm.nih.gov/35152958/},
doi = {10.1016/j.jacr.2021.11.001},
issn = {1558-349X},
year = {2022},
date = {2022-02-01},
journal = {Journal of the American College of Radiology : JACR},
volume = {19},
issue = {2 Pt B},
pages = {336--343},
abstract = {Imaging plays an integral role in the initial diagnosis and longitudinal care of patients with cancer. Liquid biopsies, which most commonly involve genetic analysis of circulating free DNA, have emerged as important complementary tools in cancer care with the potential to interface with imaging at each step of the cancer care continuum. Here, the authors use non-small-cell lung cancer as a paradigm to elucidate factors driving the need for liquid biopsy in the spectrum of lung cancer care, demonstrate ways in which liquid biopsy has already changed standard clinical practice, and discuss anticipated synergies of liquid biopsy and imaging in screening and early detection and in monitoring of disease.},
keywords = {},
pubstate = {ppublish},
tppubtype = {article}
}
Imaging plays an integral role in the initial diagnosis and longitudinal care of patients with cancer. Liquid biopsies, which most commonly involve genetic analysis of circulating free DNA, have emerged as important complementary tools in cancer care with the potential to interface with imaging at each step of the cancer care continuum. Here, the authors use non-small-cell lung cancer as a paradigm to elucidate factors driving the need for liquid biopsy in the spectrum of lung cancer care, demonstrate ways in which liquid biopsy has already changed standard clinical practice, and discuss anticipated synergies of liquid biopsy and imaging in screening and early detection and in monitoring of disease.
Chhatwal, Jagpreet; Tapper, Elliot B
Nonalcoholic Fatty Liver Disease Natural History: Role of Mathematical Modeling Bachelor Thesis
2022, ISSN: 1542-7714.
@bachelorthesis{pmid35123079,
title = {Nonalcoholic Fatty Liver Disease Natural History: Role of Mathematical Modeling},
author = {Jagpreet Chhatwal and Elliot B Tapper},
doi = {10.1016/j.cgh.2022.01.041},
issn = {1542-7714},
year = {2022},
date = {2022-02-01},
urldate = {2022-02-01},
journal = {Clin Gastroenterol Hepatol},
volume = {21},
issue = {2},
pages = {280-282},
keywords = {},
pubstate = {published},
tppubtype = {bachelorthesis}
}
Harvey, H Benjamin; Gowda, Vrushab
Clinical applications of AI in MSK imaging: a liability perspective
2022, ().
@{pmid33835241,
title = {Clinical applications of AI in MSK imaging: a liability perspective},
author = {H Benjamin Harvey and Vrushab Gowda},
doi = {10.1007/s00256-021-03782-z},
issn = {1432-2161},
year = {2022},
date = {2022-02-01},
journal = {Skeletal Radiol},
volume = {51},
number = {2},
pages = {235--238},
abstract = {Artificial intelligence (AI) applications have been gaining traction across the radiology space, promising to redefine its workflow and delivery. However, they enter into an uncertain legal environment. This piece examines the nature, exposure, and theories of liability relevant to musculoskeletal radiologist practice. More specifically, it explores the negligence, vicarious liability, and product liability frameworks by way of illustrative vignettes.},
keywords = {},
pubstate = {published},
tppubtype = {}
}
Artificial intelligence (AI) applications have been gaining traction across the radiology space, promising to redefine its workflow and delivery. However, they enter into an uncertain legal environment. This piece examines the nature, exposure, and theories of liability relevant to musculoskeletal radiologist practice. More specifically, it explores the negligence, vicarious liability, and product liability frameworks by way of illustrative vignettes.
Jalali, Mohammad S.; DiGennaro, Catherine; Guitar, Abby; Lew, Karen; Rahmandad, Hazhir
Evolution and Reproducibility of Simulation Modeling in Epidemiology and Health Policy over Half a Century. Journal Article
In: Epidemiologic reviews, vol. 43, iss. 1, pp. 166-175, 2022, ISSN: 1478-6729.
@article{Jalali2021f,
title = {Evolution and Reproducibility of Simulation Modeling in Epidemiology and Health Policy over Half a Century.},
author = {Mohammad S. Jalali and Catherine DiGennaro and Abby Guitar and Karen Lew and Hazhir Rahmandad},
url = {https://pubmed.ncbi.nlm.nih.gov/34505122/},
doi = {10.1093/epirev/mxab006},
issn = {1478-6729},
year = {2022},
date = {2022-01-14},
urldate = {2021-09-01},
journal = {Epidemiologic reviews},
volume = {43},
issue = {1},
pages = {166-175},
abstract = {Simulation models are increasingly used to inform epidemiological studies and health policy, yet there is great variation in their transparency and reproducibility. This review provides an overview of applications of simulation models in health policy and epidemiology, analyzes the use of best reporting practices, and assesses the reproducibility of the models using predefined, categorical criteria. 1,613 studies were identified and analyzed. We found an exponential growth in the number of studies over the past half century, with the highest growth in dynamic modeling approaches. The largest subset of studies is focused on disease policy models (70%), within which pathological conditions, viral diseases, neoplasms, and cardiovascular diseases account for one-third of the articles. Nearly half of the studies do not report the details of their models. We also provide in depth analysis of modeling best practices, reporting quality and reproducibility for a subset of 100 articles (50 highly cited and 50 random). Only seven of 26 in-depth evaluation criteria were satisfied by more than 80% of samples. We identify areas for increased application of simulation modeling and opportunities to enhance the rigor and documentation in the conduct and reporting of simulation modeling in epidemiology and health policy.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Simulation models are increasingly used to inform epidemiological studies and health policy, yet there is great variation in their transparency and reproducibility. This review provides an overview of applications of simulation models in health policy and epidemiology, analyzes the use of best reporting practices, and assesses the reproducibility of the models using predefined, categorical criteria. 1,613 studies were identified and analyzed. We found an exponential growth in the number of studies over the past half century, with the highest growth in dynamic modeling approaches. The largest subset of studies is focused on disease policy models (70%), within which pathological conditions, viral diseases, neoplasms, and cardiovascular diseases account for one-third of the articles. Nearly half of the studies do not report the details of their models. We also provide in depth analysis of modeling best practices, reporting quality and reproducibility for a subset of 100 articles (50 highly cited and 50 random). Only seven of 26 in-depth evaluation criteria were satisfied by more than 80% of samples. We identify areas for increased application of simulation modeling and opportunities to enhance the rigor and documentation in the conduct and reporting of simulation modeling in epidemiology and health policy.
Cerdá, Magdalena; Jalali, Mohammad S.; Hamilton, Ava D.; DiGennaro, Catherine; Hyder, Ayaz; Santaella-Tenorio, Julian; Kaur, Navdep; Wang, Christina; Keyes, Katherine M.
A Systematic Review of Simulation Models to Track and Address the Opioid Crisis. Journal Article
In: Epidemiologic reviews, vol. 43, iss. 1, pp. 147-165, 2022, ISSN: 1478-6729.
@article{Cerda2021,
title = {A Systematic Review of Simulation Models to Track and Address the Opioid Crisis.},
author = {Magdalena Cerd\'{a} and Mohammad S. Jalali and Ava D. Hamilton and Catherine DiGennaro and Ayaz Hyder and Julian Santaella-Tenorio and Navdep Kaur and Christina Wang and Katherine M. Keyes},
url = {https://pubmed.ncbi.nlm.nih.gov/34791110/},
doi = {10.1093/epirev/mxab013},
issn = {1478-6729},
year = {2022},
date = {2022-01-14},
urldate = {2021-11-01},
journal = {Epidemiologic reviews},
volume = {43},
issue = {1},
pages = {147-165},
abstract = {The opioid overdose crisis is driven by an intersecting set of social, structural, and economic forces. Simulation models offer a tool to help us understand and address this complex, dynamic, and nonlinear social phenomenon. We conducted a systematic review of the literature on simulation models of opioid use and overdose up to September 2019. We extracted modeling types, target populations, interventions, and findings. Further, we created a database of model parameters used for model calibration, and evaluated study transparency and reproducibility. Of the 1,398 articles screened, we identified 88 eligible articles. The most frequent types of models were compartmental (36%), Markov (20%), system dynamics (16%), and Agent-Based models (16%). Over a third evaluated intervention cost-effectiveness (40%), and another third (39%) focused on treatment and harm reduction services for people with opioid use disorder (OUD). More than half (61%) discussed calibrating their models to empirical data, and 31% discussed validation approaches used in their modeling process. From the 63 studies that provided model parameters, we extracted the data sources on opioid use, OUD, OUD treatment, cessation/relapse, emergency medical services, and mortality parameters. This database offers a tool that future modelers can use to identify potential model inputs and evaluate comparability of their models to prior work. Future applications of simulation models to this field should actively tackle key methodological challenges, including the potential for bias in the choice of parameter inputs, investment in model calibration and validation, and transparency in the assumptions and mechanics of simulation models to facilitate reproducibility.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The opioid overdose crisis is driven by an intersecting set of social, structural, and economic forces. Simulation models offer a tool to help us understand and address this complex, dynamic, and nonlinear social phenomenon. We conducted a systematic review of the literature on simulation models of opioid use and overdose up to September 2019. We extracted modeling types, target populations, interventions, and findings. Further, we created a database of model parameters used for model calibration, and evaluated study transparency and reproducibility. Of the 1,398 articles screened, we identified 88 eligible articles. The most frequent types of models were compartmental (36%), Markov (20%), system dynamics (16%), and Agent-Based models (16%). Over a third evaluated intervention cost-effectiveness (40%), and another third (39%) focused on treatment and harm reduction services for people with opioid use disorder (OUD). More than half (61%) discussed calibrating their models to empirical data, and 31% discussed validation approaches used in their modeling process. From the 63 studies that provided model parameters, we extracted the data sources on opioid use, OUD, OUD treatment, cessation/relapse, emergency medical services, and mortality parameters. This database offers a tool that future modelers can use to identify potential model inputs and evaluate comparability of their models to prior work. Future applications of simulation models to this field should actively tackle key methodological challenges, including the potential for bias in the choice of parameter inputs, investment in model calibration and validation, and transparency in the assumptions and mechanics of simulation models to facilitate reproducibility.
Conrads-Frank, Annette; Schnell-Inderst, Petra; Neusser, Silke; Hallsson, Lára R; Stojkov, Igor; Siebert, Silke; Kühne, Felicitas; Jahn, Beate; Siebert, Uwe; Sroczynski, Gabi
Decision-analytic modeling for early health technology assessment of medical devices - a scoping review Journal Article
In: Ger Med Sci, vol. 20, pp. Doc11, 2022, ISSN: 1612-3174.
@article{pmid36742459,
title = {Decision-analytic modeling for early health technology assessment of medical devices - a scoping review},
author = {Annette Conrads-Frank and Petra Schnell-Inderst and Silke Neusser and L\'{a}ra R Hallsson and Igor Stojkov and Silke Siebert and Felicitas K\"{u}hne and Beate Jahn and Uwe Siebert and Gabi Sroczynski},
doi = {10.3205/000313},
issn = {1612-3174},
year = {2022},
date = {2022-01-01},
journal = {Ger Med Sci},
volume = {20},
pages = {Doc11},
abstract = {OBJECTIVE: The goal of this review was to identify decision-analytic modeling studies in early health technology assessments (HTA) of high-risk medical devices, published over the last three years, and to provide a systematic overview of model purposes and characteristics. Additionally, the aim was to describe recent developments in modeling techniques.
METHODS: For this scoping review, we performed a systematic literature search in PubMed and Embase including studies published in English or German. The search code consisted of terms describing early health technology assessment and terms for decision-analytic models. In abstract and full-text screening, studies were excluded that were not modeling studies for a high-risk medical device or an in-vitro diagnostic test. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram was used to report on the search and exclusion of studies. For all included studies, study purpose, framework and model characteristics were extracted and reported in systematic evidence tables and a narrative summary.
RESULTS: Out of 206 identified studies, 19 studies were included in the review. Studies were either conducted for hypothetical devices or for existing devices after they were already available on the market. No study extrapolated technical data from early development stages to estimate potential value of devices in development. All studies except one included cost as an outcome. Two studies were budget impact analyses. Most studies aimed at adoption and reimbursement decisions. The majority of studies were on in-vitro diagnostic tests for personalized and targeted medicine. A timed automata model, to our knowledge a model type new to HTA, was tested by one study. It describes the agents in a clinical pathway in separate models and, by allowing for interaction between the models, can reflect complex individual clinical pathways and dynamic system interactions. Not all sources of uncertainty for in-vitro tests were explicitly modeled. Elicitation of expert knowledge and judgement was used for substitution of missing empirical data. Analysis of uncertainty was the most valuable strength of decision-analytic models in early HTA, but no model applied sensitivity analysis to optimize the test positivity cutoff with regard to the benefit-harm balance or cost-effectiveness. Value-of-information analysis was rarely performed. No information was found on the use of causal inference methods for estimation of effect parameters from observational data.
CONCLUSION: Our review provides an overview of the purposes and model characteristics of nineteen recent early evaluation studies on medical devices. The review shows the growing importance of personalized interventions and confirms previously published recommendations for careful modeling of uncertainties surrounding diagnostic devices and for increased use of value-of-information analysis. Timed automata may be a model type worth exploring further in HTA. In addition, we recommend to extend the application of sensitivity analysis to optimize positivity criteria for in-vitro tests with regard to benefit-harm or cost-effectiveness. We emphasize the importance of causal inference methods when estimating effect parameters from observational data.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
OBJECTIVE: The goal of this review was to identify decision-analytic modeling studies in early health technology assessments (HTA) of high-risk medical devices, published over the last three years, and to provide a systematic overview of model purposes and characteristics. Additionally, the aim was to describe recent developments in modeling techniques.
METHODS: For this scoping review, we performed a systematic literature search in PubMed and Embase including studies published in English or German. The search code consisted of terms describing early health technology assessment and terms for decision-analytic models. In abstract and full-text screening, studies were excluded that were not modeling studies for a high-risk medical device or an in-vitro diagnostic test. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram was used to report on the search and exclusion of studies. For all included studies, study purpose, framework and model characteristics were extracted and reported in systematic evidence tables and a narrative summary.
RESULTS: Out of 206 identified studies, 19 studies were included in the review. Studies were either conducted for hypothetical devices or for existing devices after they were already available on the market. No study extrapolated technical data from early development stages to estimate potential value of devices in development. All studies except one included cost as an outcome. Two studies were budget impact analyses. Most studies aimed at adoption and reimbursement decisions. The majority of studies were on in-vitro diagnostic tests for personalized and targeted medicine. A timed automata model, to our knowledge a model type new to HTA, was tested by one study. It describes the agents in a clinical pathway in separate models and, by allowing for interaction between the models, can reflect complex individual clinical pathways and dynamic system interactions. Not all sources of uncertainty for in-vitro tests were explicitly modeled. Elicitation of expert knowledge and judgement was used for substitution of missing empirical data. Analysis of uncertainty was the most valuable strength of decision-analytic models in early HTA, but no model applied sensitivity analysis to optimize the test positivity cutoff with regard to the benefit-harm balance or cost-effectiveness. Value-of-information analysis was rarely performed. No information was found on the use of causal inference methods for estimation of effect parameters from observational data.
CONCLUSION: Our review provides an overview of the purposes and model characteristics of nineteen recent early evaluation studies on medical devices. The review shows the growing importance of personalized interventions and confirms previously published recommendations for careful modeling of uncertainties surrounding diagnostic devices and for increased use of value-of-information analysis. Timed automata may be a model type worth exploring further in HTA. In addition, we recommend to extend the application of sensitivity analysis to optimize positivity criteria for in-vitro tests with regard to benefit-harm or cost-effectiveness. We emphasize the importance of causal inference methods when estimating effect parameters from observational data.
METHODS: For this scoping review, we performed a systematic literature search in PubMed and Embase including studies published in English or German. The search code consisted of terms describing early health technology assessment and terms for decision-analytic models. In abstract and full-text screening, studies were excluded that were not modeling studies for a high-risk medical device or an in-vitro diagnostic test. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram was used to report on the search and exclusion of studies. For all included studies, study purpose, framework and model characteristics were extracted and reported in systematic evidence tables and a narrative summary.
RESULTS: Out of 206 identified studies, 19 studies were included in the review. Studies were either conducted for hypothetical devices or for existing devices after they were already available on the market. No study extrapolated technical data from early development stages to estimate potential value of devices in development. All studies except one included cost as an outcome. Two studies were budget impact analyses. Most studies aimed at adoption and reimbursement decisions. The majority of studies were on in-vitro diagnostic tests for personalized and targeted medicine. A timed automata model, to our knowledge a model type new to HTA, was tested by one study. It describes the agents in a clinical pathway in separate models and, by allowing for interaction between the models, can reflect complex individual clinical pathways and dynamic system interactions. Not all sources of uncertainty for in-vitro tests were explicitly modeled. Elicitation of expert knowledge and judgement was used for substitution of missing empirical data. Analysis of uncertainty was the most valuable strength of decision-analytic models in early HTA, but no model applied sensitivity analysis to optimize the test positivity cutoff with regard to the benefit-harm balance or cost-effectiveness. Value-of-information analysis was rarely performed. No information was found on the use of causal inference methods for estimation of effect parameters from observational data.
CONCLUSION: Our review provides an overview of the purposes and model characteristics of nineteen recent early evaluation studies on medical devices. The review shows the growing importance of personalized interventions and confirms previously published recommendations for careful modeling of uncertainties surrounding diagnostic devices and for increased use of value-of-information analysis. Timed automata may be a model type worth exploring further in HTA. In addition, we recommend to extend the application of sensitivity analysis to optimize positivity criteria for in-vitro tests with regard to benefit-harm or cost-effectiveness. We emphasize the importance of causal inference methods when estimating effect parameters from observational data.
Kühne, Felicitas; Schomaker, Michael; Stojkov, Igor; Jahn, Beate; Conrads-Frank, Annette; Siebert, Silke; Sroczynski, Gaby; Puntscher, Sibylle; Schmid, Daniela; Schnell-Inderst, Petra; Siebert, Uwe
Causal evidence in health decision making: methodological approaches of causal inference and health decision science Journal Article
In: Ger Med Sci, vol. 20, pp. Doc12, 2022, ISSN: 1612-3174.
@article{pmid36742460,
title = {Causal evidence in health decision making: methodological approaches of causal inference and health decision science},
author = {Felicitas K\"{u}hne and Michael Schomaker and Igor Stojkov and Beate Jahn and Annette Conrads-Frank and Silke Siebert and Gaby Sroczynski and Sibylle Puntscher and Daniela Schmid and Petra Schnell-Inderst and Uwe Siebert},
doi = {10.3205/000314},
issn = {1612-3174},
year = {2022},
date = {2022-01-01},
journal = {Ger Med Sci},
volume = {20},
pages = {Doc12},
abstract = {OBJECTIVES: Public health decision making is a complex process based on thorough and comprehensive health technology assessments involving the comparison of different strategies, values and tradeoffs under uncertainty. This process must be based on best available evidence and plausible assumptions. Causal inference and health decision science are two methodological approaches providing information to help guide decision making in health care. Both approaches are quantitative methods that use statistical and modeling techniques and simplifying assumptions to mimic the complexity of the real world. We intend to review and lay out both disciplines with their aims, strengths and limitations based on a combination of textbook knowledge and expert experience.
METHODS: To help understanding and differentiating the methodological approaches of causal inference and health decision science, we reviewed both methods with the focus on aims, research questions, methods, assumptions, limitations and challenges, and software. For each methodological approach, we established a group of four experts from our own working group to carefully review and summarize each method, followed by structured discussion rounds and written reviews, in which the experts from all disciplines including HTA and medicine were involved. The entire expert group discussed objectives, strengths and limitations of both methodological areas, and potential synergies. Finally, we derived recommendations for further research and provide a brief outlook on future trends.
RESULTS: Causal inference methods aim for drawing causal conclusions from empirical data on the relationship of pre-specified interventions on a specific target outcome and apply a counterfactual framework and statistical techniques to derive causal effects of exposures or interventions from these data. Causal inference is based on a causal diagram, more specifically, a directed acyclic graph (DAG), which encodes the assumptions regarding the causal relations between variables. Depending on the type of confounding and selection bias, traditional statistical methods or more complex g-methods are needed to derive valid causal effects. Besides the correct specification of the DAG and the statistical model, assumptions such as consistency, positivity, and exchangeability must be checked when aiming at causal inference. Health decision science aims for guiding policy decision making regarding health interventions considering and balancing multiple competing objectives of a decision based on data from multiple sources and studies, for example prevalence studies, clinical trials and long-term observational routine effectiveness studies, and studies on preferences and costs. It involves decision analysis, a systematic, explicit and quantitative framework to guide decisions under uncertainty. Decision analyses are based on decision-analytic models to mimic the course of disease as well as aspects and consequences of the intervention in order to quantitatively optimize the decision. Depending on the type of decision problem, decision trees, state-transition models, discrete event simulation models, dynamic transmission models, or other model types are applied. Models must be validated against observed data, and comprehensive sensitivity analyses must be performed to assess uncertainty. Besides the appropriate choice of the model type and the valid specification of the model structure, it must be checked if input parameters of effects can be interpreted as causal parameters in the model. Otherwise results will be biased.
CONCLUSIONS: Both causal inference and health decision science aim for providing best causal evidence for informed health decision making. The strengths and limitations of both methods differ and a good understanding of both methods is essential for correct application but also for correct interpretation of findings from the described methods. Importantly, decision-analytic modeling should be combined with causal inference when developing guidance and recommendations regarding decisions on health care interventions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
OBJECTIVES: Public health decision making is a complex process based on thorough and comprehensive health technology assessments involving the comparison of different strategies, values and tradeoffs under uncertainty. This process must be based on best available evidence and plausible assumptions. Causal inference and health decision science are two methodological approaches providing information to help guide decision making in health care. Both approaches are quantitative methods that use statistical and modeling techniques and simplifying assumptions to mimic the complexity of the real world. We intend to review and lay out both disciplines with their aims, strengths and limitations based on a combination of textbook knowledge and expert experience.
METHODS: To help understanding and differentiating the methodological approaches of causal inference and health decision science, we reviewed both methods with the focus on aims, research questions, methods, assumptions, limitations and challenges, and software. For each methodological approach, we established a group of four experts from our own working group to carefully review and summarize each method, followed by structured discussion rounds and written reviews, in which the experts from all disciplines including HTA and medicine were involved. The entire expert group discussed objectives, strengths and limitations of both methodological areas, and potential synergies. Finally, we derived recommendations for further research and provide a brief outlook on future trends.
RESULTS: Causal inference methods aim for drawing causal conclusions from empirical data on the relationship of pre-specified interventions on a specific target outcome and apply a counterfactual framework and statistical techniques to derive causal effects of exposures or interventions from these data. Causal inference is based on a causal diagram, more specifically, a directed acyclic graph (DAG), which encodes the assumptions regarding the causal relations between variables. Depending on the type of confounding and selection bias, traditional statistical methods or more complex g-methods are needed to derive valid causal effects. Besides the correct specification of the DAG and the statistical model, assumptions such as consistency, positivity, and exchangeability must be checked when aiming at causal inference. Health decision science aims for guiding policy decision making regarding health interventions considering and balancing multiple competing objectives of a decision based on data from multiple sources and studies, for example prevalence studies, clinical trials and long-term observational routine effectiveness studies, and studies on preferences and costs. It involves decision analysis, a systematic, explicit and quantitative framework to guide decisions under uncertainty. Decision analyses are based on decision-analytic models to mimic the course of disease as well as aspects and consequences of the intervention in order to quantitatively optimize the decision. Depending on the type of decision problem, decision trees, state-transition models, discrete event simulation models, dynamic transmission models, or other model types are applied. Models must be validated against observed data, and comprehensive sensitivity analyses must be performed to assess uncertainty. Besides the appropriate choice of the model type and the valid specification of the model structure, it must be checked if input parameters of effects can be interpreted as causal parameters in the model. Otherwise results will be biased.
CONCLUSIONS: Both causal inference and health decision science aim for providing best causal evidence for informed health decision making. The strengths and limitations of both methods differ and a good understanding of both methods is essential for correct application but also for correct interpretation of findings from the described methods. Importantly, decision-analytic modeling should be combined with causal inference when developing guidance and recommendations regarding decisions on health care interventions.
METHODS: To help understanding and differentiating the methodological approaches of causal inference and health decision science, we reviewed both methods with the focus on aims, research questions, methods, assumptions, limitations and challenges, and software. For each methodological approach, we established a group of four experts from our own working group to carefully review and summarize each method, followed by structured discussion rounds and written reviews, in which the experts from all disciplines including HTA and medicine were involved. The entire expert group discussed objectives, strengths and limitations of both methodological areas, and potential synergies. Finally, we derived recommendations for further research and provide a brief outlook on future trends.
RESULTS: Causal inference methods aim for drawing causal conclusions from empirical data on the relationship of pre-specified interventions on a specific target outcome and apply a counterfactual framework and statistical techniques to derive causal effects of exposures or interventions from these data. Causal inference is based on a causal diagram, more specifically, a directed acyclic graph (DAG), which encodes the assumptions regarding the causal relations between variables. Depending on the type of confounding and selection bias, traditional statistical methods or more complex g-methods are needed to derive valid causal effects. Besides the correct specification of the DAG and the statistical model, assumptions such as consistency, positivity, and exchangeability must be checked when aiming at causal inference. Health decision science aims for guiding policy decision making regarding health interventions considering and balancing multiple competing objectives of a decision based on data from multiple sources and studies, for example prevalence studies, clinical trials and long-term observational routine effectiveness studies, and studies on preferences and costs. It involves decision analysis, a systematic, explicit and quantitative framework to guide decisions under uncertainty. Decision analyses are based on decision-analytic models to mimic the course of disease as well as aspects and consequences of the intervention in order to quantitatively optimize the decision. Depending on the type of decision problem, decision trees, state-transition models, discrete event simulation models, dynamic transmission models, or other model types are applied. Models must be validated against observed data, and comprehensive sensitivity analyses must be performed to assess uncertainty. Besides the appropriate choice of the model type and the valid specification of the model structure, it must be checked if input parameters of effects can be interpreted as causal parameters in the model. Otherwise results will be biased.
CONCLUSIONS: Both causal inference and health decision science aim for providing best causal evidence for informed health decision making. The strengths and limitations of both methods differ and a good understanding of both methods is essential for correct application but also for correct interpretation of findings from the described methods. Importantly, decision-analytic modeling should be combined with causal inference when developing guidance and recommendations regarding decisions on health care interventions.
Schnell-Inderst, Petra; Steigenberger, Caroline; Mertz, Marcel; Otto, Ilvie; Flatscher-Thöni, Magdalena; Siebert, Uwe
In: Ger Med Sci, vol. 20, pp. Doc10, 2022, ISSN: 1612-3174.
@article{pmid36160875,
title = {Additional treatment with mistletoe extracts for patients with breast cancer compared to conventional cancer therapy alone - efficacy and safety, costs and cost-effectiveness, patients and social aspects, and ethical assessment},
author = {Petra Schnell-Inderst and Caroline Steigenberger and Marcel Mertz and Ilvie Otto and Magdalena Flatscher-Th\"{o}ni and Uwe Siebert},
doi = {10.3205/000312},
issn = {1612-3174},
year = {2022},
date = {2022-01-01},
journal = {Ger Med Sci},
volume = {20},
pages = {Doc10},
abstract = {Background: Chemotherapy is often used in the treatment of breast cancer in women. Side effects such as diarrhea, fatigue, hair loss, fever or disturbances in blood formation impair the women's quality of life. An essential treatment goal of the accompanying mistletoe therapy (MT) used in complementary medicine is to improve the health-related quality of life during cancer therapy.
Aim and methods: The HTA report on which this article is based examines the medical efficacy and safety, costs and cost-effectiveness, patient and social aspects, and ethical aspects of MT in women with breast cancer. Systematic reviews were conducted for this purpose. The search period of the literature search ranged from 2004 to October 2020.
Results: A total of 2 evidence-based medical guidelines, 3 randomized trials assessing efficacy and 1 additional non-randomized intervention trial, as well as 3 observational studies assessing safety, a cost analysis, 12 cross-sectional studies on patient aspects and 17 articles on ethical evaluation were included. Improvements in health-related quality of life compared to the control group were small to moderate. Due to the high risk of bias in the studies, it is possible that the difference is not caused by MT. One study with a small sample size showed no effect on progression-free survival after 5 years. Studies on the effect of MT on overall survival are lacking. In seven studies, local skin reactions of low and moderate severity were reported in a median of 25% (range 5 to 94%) of patients, and mild to moderate systemic reactions in a median of 2% (range 0 to 8%) of patients. A comparative cost analysis from Germany reported significantly lower medical costs within 5 years after surgery for patients with MT than for patients without MT, but the underlying observational study did not control for systematic bias. With regard to patient aspects, the frequency of use and the reasons for use from the patient's or practitioner's point of view were mainly investigated. A median of 25% (range 7 to 46%) of patients with breast cancer and 29% (range 29 to 79%) of treatment providers use MT. The main motivations of patients for use were to reduce side effects, strengthen the immune system and take an active role in the treatment process. Patients felt insufficiently advised. Studies on other aspects are lacking. The ethical evaluation was able to identify 6 overarching themes; the central challenge is the insufficient evidence on efficacy and safety.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Background: Chemotherapy is often used in the treatment of breast cancer in women. Side effects such as diarrhea, fatigue, hair loss, fever or disturbances in blood formation impair the women's quality of life. An essential treatment goal of the accompanying mistletoe therapy (MT) used in complementary medicine is to improve the health-related quality of life during cancer therapy.
Aim and methods: The HTA report on which this article is based examines the medical efficacy and safety, costs and cost-effectiveness, patient and social aspects, and ethical aspects of MT in women with breast cancer. Systematic reviews were conducted for this purpose. The search period of the literature search ranged from 2004 to October 2020.
Results: A total of 2 evidence-based medical guidelines, 3 randomized trials assessing efficacy and 1 additional non-randomized intervention trial, as well as 3 observational studies assessing safety, a cost analysis, 12 cross-sectional studies on patient aspects and 17 articles on ethical evaluation were included. Improvements in health-related quality of life compared to the control group were small to moderate. Due to the high risk of bias in the studies, it is possible that the difference is not caused by MT. One study with a small sample size showed no effect on progression-free survival after 5 years. Studies on the effect of MT on overall survival are lacking. In seven studies, local skin reactions of low and moderate severity were reported in a median of 25% (range 5 to 94%) of patients, and mild to moderate systemic reactions in a median of 2% (range 0 to 8%) of patients. A comparative cost analysis from Germany reported significantly lower medical costs within 5 years after surgery for patients with MT than for patients without MT, but the underlying observational study did not control for systematic bias. With regard to patient aspects, the frequency of use and the reasons for use from the patient's or practitioner's point of view were mainly investigated. A median of 25% (range 7 to 46%) of patients with breast cancer and 29% (range 29 to 79%) of treatment providers use MT. The main motivations of patients for use were to reduce side effects, strengthen the immune system and take an active role in the treatment process. Patients felt insufficiently advised. Studies on other aspects are lacking. The ethical evaluation was able to identify 6 overarching themes; the central challenge is the insufficient evidence on efficacy and safety.
Aim and methods: The HTA report on which this article is based examines the medical efficacy and safety, costs and cost-effectiveness, patient and social aspects, and ethical aspects of MT in women with breast cancer. Systematic reviews were conducted for this purpose. The search period of the literature search ranged from 2004 to October 2020.
Results: A total of 2 evidence-based medical guidelines, 3 randomized trials assessing efficacy and 1 additional non-randomized intervention trial, as well as 3 observational studies assessing safety, a cost analysis, 12 cross-sectional studies on patient aspects and 17 articles on ethical evaluation were included. Improvements in health-related quality of life compared to the control group were small to moderate. Due to the high risk of bias in the studies, it is possible that the difference is not caused by MT. One study with a small sample size showed no effect on progression-free survival after 5 years. Studies on the effect of MT on overall survival are lacking. In seven studies, local skin reactions of low and moderate severity were reported in a median of 25% (range 5 to 94%) of patients, and mild to moderate systemic reactions in a median of 2% (range 0 to 8%) of patients. A comparative cost analysis from Germany reported significantly lower medical costs within 5 years after surgery for patients with MT than for patients without MT, but the underlying observational study did not control for systematic bias. With regard to patient aspects, the frequency of use and the reasons for use from the patient's or practitioner's point of view were mainly investigated. A median of 25% (range 7 to 46%) of patients with breast cancer and 29% (range 29 to 79%) of treatment providers use MT. The main motivations of patients for use were to reduce side effects, strengthen the immune system and take an active role in the treatment process. Patients felt insufficiently advised. Studies on other aspects are lacking. The ethical evaluation was able to identify 6 overarching themes; the central challenge is the insufficient evidence on efficacy and safety.
Chhatwal, Jagpreet; Dalgic, Ozden O; Chen, Wanyi; Samur, Sumeyye; Bethea, Emily D; Xiao, Jade; Hur, Chin; Corey, Kathleen E; Loomba, Rohit
Analysis of a Simulation Model to Estimate Long-term Outcomes in Patients with Nonalcoholic Fatty Liver Disease Journal Article
In: JAMA Netw Open, vol. 5, no. 9, pp. e2230426, 2022, ISSN: 2574-3805.
@article{pmid36098969,
title = {Analysis of a Simulation Model to Estimate Long-term Outcomes in Patients with Nonalcoholic Fatty Liver Disease},
author = {Jagpreet Chhatwal and Ozden O Dalgic and Wanyi Chen and Sumeyye Samur and Emily D Bethea and Jade Xiao and Chin Hur and Kathleen E Corey and Rohit Loomba},
doi = {10.1001/jamanetworkopen.2022.30426},
issn = {2574-3805},
year = {2022},
date = {2022-01-01},
journal = {JAMA Netw Open},
volume = {5},
number = {9},
pages = {e2230426},
abstract = {Importance: Quantitative assessment of disease progression in patients with nonalcoholic fatty liver disease (NAFLD) has not been systematically examined using competing liver-related and non-liver-related mortality.
Objective: To estimate long-term outcomes in NAFLD, accounting for competing liver-related and non-liver-related mortality associated with the different fibrosis stages of NAFLD using a simulated patient population.
Design, Setting, and Participants: This decision analytical modeling study used individual-level state-transition simulation analysis and was conducted from September 1, 2017, to September 1, 2021. A publicly available interactive tool, dubbed NAFLD Simulator, was developed that simulates the natural history of NAFLD by age and fibrosis stage at the time of (hypothetical) diagnosis defined by liver biopsy. Model health states were defined by fibrosis states F0 to F4, decompensated cirrhosis, hepatocellular carcinoma (HCC), and liver transplant. Simulated patients could experience nonalcoholic steatohepatitis resolution, and their fibrosis stage could progress or regress. Transition probabilities between states were estimated from the literature as well as calibration, and the model reproduced the outcomes of a large observational study.
Exposure: Simulated natural history of NAFLD.
Main Outcomes and Measures: Main outcomes were life expectancy; all cause, liver-related, and non-liver-related mortality; and cumulative incidence of decompensated cirrhosis and/or HCC.
Results: The model included 1 000 000 simulated patients with a mean (range) age of 49 (18-75) years at baseline, including 66% women. The life expectancy of patients aged 49 years was 25.3 (95% CI, 20.1-29.8) years for those with F0, 25.1 (95% CI, 20.1-29.4) years for those with F1, 23.6 (95% CI, 18.3-28.2) years for those with F2, 21.1 (95% CI, 15.6-26.3) years for those with F3, and 13.8 (95% CI, 10.3-17.6) years for those with F4 at the time of diagnosis. The estimated 10-year liver-related mortality was 0.1% (95% uncertainty interval [UI], <0.1%-0.2%) in F0, 0.2% (95% UI, 0.1%-0.4%) in F1, 1.0% (95% UI, 0.6%-1.7%) in F2, 4.0% (95% UI, 2.5%-5.9%) in F3, and 29.3% (95% UI, 21.8%-35.9%) in F4. The corresponding 10-year non-liver-related mortality was 1.8% (95% UI, 0.6%-5.0%) in F0, 2.4% (95% UI, 0.8%-6.3%) in F1, 5.2% (95% UI, 2.0%-11.9%) in F2, 9.7% (95% UI, 4.3%-18.1%) in F3, and 15.6% (95% UI, 10.1%-21.7%) in F4. Among patients aged 65 years, estimated 10-year non-liver-related mortality was higher than liver-related mortality in all fibrosis stages (eg, F2: 16.7% vs 0.8%; F3: 28.8% vs 3.0%; F4: 40.8% vs 21.9%).
Conclusions and Relevance: This decision analytic model study simulated stage-specific long-term outcomes, including liver- and non-liver-related mortality in patients with NAFLD. Depending on age and fibrosis stage, non-liver-related mortality was higher than liver-related mortality in patients with NAFLD. By translating surrogate markers into clinical outcomes, the NAFLD Simulator could be used as an educational tool among patients and clinicians to increase awareness of the health consequences of NAFLD.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Importance: Quantitative assessment of disease progression in patients with nonalcoholic fatty liver disease (NAFLD) has not been systematically examined using competing liver-related and non-liver-related mortality.
Objective: To estimate long-term outcomes in NAFLD, accounting for competing liver-related and non-liver-related mortality associated with the different fibrosis stages of NAFLD using a simulated patient population.
Design, Setting, and Participants: This decision analytical modeling study used individual-level state-transition simulation analysis and was conducted from September 1, 2017, to September 1, 2021. A publicly available interactive tool, dubbed NAFLD Simulator, was developed that simulates the natural history of NAFLD by age and fibrosis stage at the time of (hypothetical) diagnosis defined by liver biopsy. Model health states were defined by fibrosis states F0 to F4, decompensated cirrhosis, hepatocellular carcinoma (HCC), and liver transplant. Simulated patients could experience nonalcoholic steatohepatitis resolution, and their fibrosis stage could progress or regress. Transition probabilities between states were estimated from the literature as well as calibration, and the model reproduced the outcomes of a large observational study.
Exposure: Simulated natural history of NAFLD.
Main Outcomes and Measures: Main outcomes were life expectancy; all cause, liver-related, and non-liver-related mortality; and cumulative incidence of decompensated cirrhosis and/or HCC.
Results: The model included 1 000 000 simulated patients with a mean (range) age of 49 (18-75) years at baseline, including 66% women. The life expectancy of patients aged 49 years was 25.3 (95% CI, 20.1-29.8) years for those with F0, 25.1 (95% CI, 20.1-29.4) years for those with F1, 23.6 (95% CI, 18.3-28.2) years for those with F2, 21.1 (95% CI, 15.6-26.3) years for those with F3, and 13.8 (95% CI, 10.3-17.6) years for those with F4 at the time of diagnosis. The estimated 10-year liver-related mortality was 0.1% (95% uncertainty interval [UI], <0.1%-0.2%) in F0, 0.2% (95% UI, 0.1%-0.4%) in F1, 1.0% (95% UI, 0.6%-1.7%) in F2, 4.0% (95% UI, 2.5%-5.9%) in F3, and 29.3% (95% UI, 21.8%-35.9%) in F4. The corresponding 10-year non-liver-related mortality was 1.8% (95% UI, 0.6%-5.0%) in F0, 2.4% (95% UI, 0.8%-6.3%) in F1, 5.2% (95% UI, 2.0%-11.9%) in F2, 9.7% (95% UI, 4.3%-18.1%) in F3, and 15.6% (95% UI, 10.1%-21.7%) in F4. Among patients aged 65 years, estimated 10-year non-liver-related mortality was higher than liver-related mortality in all fibrosis stages (eg, F2: 16.7% vs 0.8%; F3: 28.8% vs 3.0%; F4: 40.8% vs 21.9%).
Conclusions and Relevance: This decision analytic model study simulated stage-specific long-term outcomes, including liver- and non-liver-related mortality in patients with NAFLD. Depending on age and fibrosis stage, non-liver-related mortality was higher than liver-related mortality in patients with NAFLD. By translating surrogate markers into clinical outcomes, the NAFLD Simulator could be used as an educational tool among patients and clinicians to increase awareness of the health consequences of NAFLD.
Objective: To estimate long-term outcomes in NAFLD, accounting for competing liver-related and non-liver-related mortality associated with the different fibrosis stages of NAFLD using a simulated patient population.
Design, Setting, and Participants: This decision analytical modeling study used individual-level state-transition simulation analysis and was conducted from September 1, 2017, to September 1, 2021. A publicly available interactive tool, dubbed NAFLD Simulator, was developed that simulates the natural history of NAFLD by age and fibrosis stage at the time of (hypothetical) diagnosis defined by liver biopsy. Model health states were defined by fibrosis states F0 to F4, decompensated cirrhosis, hepatocellular carcinoma (HCC), and liver transplant. Simulated patients could experience nonalcoholic steatohepatitis resolution, and their fibrosis stage could progress or regress. Transition probabilities between states were estimated from the literature as well as calibration, and the model reproduced the outcomes of a large observational study.
Exposure: Simulated natural history of NAFLD.
Main Outcomes and Measures: Main outcomes were life expectancy; all cause, liver-related, and non-liver-related mortality; and cumulative incidence of decompensated cirrhosis and/or HCC.
Results: The model included 1 000 000 simulated patients with a mean (range) age of 49 (18-75) years at baseline, including 66% women. The life expectancy of patients aged 49 years was 25.3 (95% CI, 20.1-29.8) years for those with F0, 25.1 (95% CI, 20.1-29.4) years for those with F1, 23.6 (95% CI, 18.3-28.2) years for those with F2, 21.1 (95% CI, 15.6-26.3) years for those with F3, and 13.8 (95% CI, 10.3-17.6) years for those with F4 at the time of diagnosis. The estimated 10-year liver-related mortality was 0.1% (95% uncertainty interval [UI], <0.1%-0.2%) in F0, 0.2% (95% UI, 0.1%-0.4%) in F1, 1.0% (95% UI, 0.6%-1.7%) in F2, 4.0% (95% UI, 2.5%-5.9%) in F3, and 29.3% (95% UI, 21.8%-35.9%) in F4. The corresponding 10-year non-liver-related mortality was 1.8% (95% UI, 0.6%-5.0%) in F0, 2.4% (95% UI, 0.8%-6.3%) in F1, 5.2% (95% UI, 2.0%-11.9%) in F2, 9.7% (95% UI, 4.3%-18.1%) in F3, and 15.6% (95% UI, 10.1%-21.7%) in F4. Among patients aged 65 years, estimated 10-year non-liver-related mortality was higher than liver-related mortality in all fibrosis stages (eg, F2: 16.7% vs 0.8%; F3: 28.8% vs 3.0%; F4: 40.8% vs 21.9%).
Conclusions and Relevance: This decision analytic model study simulated stage-specific long-term outcomes, including liver- and non-liver-related mortality in patients with NAFLD. Depending on age and fibrosis stage, non-liver-related mortality was higher than liver-related mortality in patients with NAFLD. By translating surrogate markers into clinical outcomes, the NAFLD Simulator could be used as an educational tool among patients and clinicians to increase awareness of the health consequences of NAFLD.
Alarid-Escudero, Fernando; Knudsen, Amy B; Ozik, Jonathan; Collier, Nicholson; Kuntz, Karen M
Characterization and Valuation of the Uncertainty of Calibrated Parameters in Microsimulation Decision Models Journal Article
In: Front Physiol, vol. 13, pp. 780917, 2022, ISSN: 1664-042X.
@article{pmid35615677,
title = {Characterization and Valuation of the Uncertainty of Calibrated Parameters in Microsimulation Decision Models},
author = {Fernando Alarid-Escudero and Amy B Knudsen and Jonathan Ozik and Nicholson Collier and Karen M Kuntz},
doi = {10.3389/fphys.2022.780917},
issn = {1664-042X},
year = {2022},
date = {2022-01-01},
journal = {Front Physiol},
volume = {13},
pages = {780917},
abstract = { We evaluated the implications of different approaches to characterize the uncertainty of calibrated parameters of microsimulation decision models (DMs) and quantified the value of such uncertainty in decision making. We calibrated the natural history model of CRC to simulated epidemiological data with different degrees of uncertainty and obtained the joint posterior distribution of the parameters using a Bayesian approach. We conducted a probabilistic sensitivity analysis (PSA) on all the model parameters with different characterizations of the uncertainty of the calibrated parameters. We estimated the value of uncertainty of the various characterizations with a value of information analysis. We conducted all analyses using high-performance computing resources running the Extreme-scale Model Exploration with Swift (EMEWS) framework. The posterior distribution had a high correlation among some parameters. The parameters of the Weibull hazard function for the age of onset of adenomas had the highest posterior correlation of -0.958. When comparing full posterior distributions and the maximum-a-posteriori estimate of the calibrated parameters, there is little difference in the spread of the distribution of the CEA outcomes with a similar expected value of perfect information (EVPI) of $653 and $685, respectively, at a willingness-to-pay (WTP) threshold of $66,000 per quality-adjusted life year (QALY). Ignoring correlation on the calibrated parameters' posterior distribution produced the broadest distribution of CEA outcomes and the highest EVPI of $809 at the same WTP threshold. Different characterizations of the uncertainty of calibrated parameters affect the expected value of eliminating parametric uncertainty on the CEA. Ignoring inherent correlation among calibrated parameters on a PSA overestimates the value of uncertainty.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We evaluated the implications of different approaches to characterize the uncertainty of calibrated parameters of microsimulation decision models (DMs) and quantified the value of such uncertainty in decision making. We calibrated the natural history model of CRC to simulated epidemiological data with different degrees of uncertainty and obtained the joint posterior distribution of the parameters using a Bayesian approach. We conducted a probabilistic sensitivity analysis (PSA) on all the model parameters with different characterizations of the uncertainty of the calibrated parameters. We estimated the value of uncertainty of the various characterizations with a value of information analysis. We conducted all analyses using high-performance computing resources running the Extreme-scale Model Exploration with Swift (EMEWS) framework. The posterior distribution had a high correlation among some parameters. The parameters of the Weibull hazard function for the age of onset of adenomas had the highest posterior correlation of -0.958. When comparing full posterior distributions and the maximum-a-posteriori estimate of the calibrated parameters, there is little difference in the spread of the distribution of the CEA outcomes with a similar expected value of perfect information (EVPI) of $653 and $685, respectively, at a willingness-to-pay (WTP) threshold of $66,000 per quality-adjusted life year (QALY). Ignoring correlation on the calibrated parameters' posterior distribution produced the broadest distribution of CEA outcomes and the highest EVPI of $809 at the same WTP threshold. Different characterizations of the uncertainty of calibrated parameters affect the expected value of eliminating parametric uncertainty on the CEA. Ignoring inherent correlation among calibrated parameters on a PSA overestimates the value of uncertainty.
Bicher, Martin; Rippinger, Claire; Zechmeister, Melanie; Jahn, Beate; Sroczynski, Gaby; Mühlberger, Nikolai; Santamaria-Navarro, Julia; Urach, Christoph; Brunmeir, Dominik; Siebert, Uwe; Popper, Niki
An iterative algorithm for optimizing COVID-19 vaccination strategies considering unknown supply Journal Article
In: PLoS One, vol. 17, no. 5, pp. e0265957, 2022, ISSN: 1932-6203.
@article{pmid35499997,
title = {An iterative algorithm for optimizing COVID-19 vaccination strategies considering unknown supply},
author = {Martin Bicher and Claire Rippinger and Melanie Zechmeister and Beate Jahn and Gaby Sroczynski and Nikolai M\"{u}hlberger and Julia Santamaria-Navarro and Christoph Urach and Dominik Brunmeir and Uwe Siebert and Niki Popper},
doi = {10.1371/journal.pone.0265957},
issn = {1932-6203},
year = {2022},
date = {2022-01-01},
journal = {PLoS One},
volume = {17},
number = {5},
pages = {e0265957},
abstract = {BACKGROUND AND OBJECTIVE: The distribution of the newly developed vaccines presents a great challenge in the ongoing SARS-CoV-2 pandemic. Policy makers must decide which subgroups should be vaccinated first to minimize the negative consequences of the pandemic. These decisions must be made upfront and under uncertainty regarding the amount of vaccine doses available at a given time. The objective of the present work was to develop an iterative optimization algorithm, which provides a prioritization order of predefined subgroups. The results of this algorithm should be optimal but also robust with respect to potentially limited vaccine supply.
METHODS: We present an optimization meta-heuristic which can be used in a classic simulation-optimization setting with a simulation model in a feedback loop. The meta-heuristic can be applied in combination with any epidemiological simulation model capable of depicting the effects of vaccine distribution to the modeled population, accepts a vaccine prioritization plan in a certain notation as input, and generates decision making relevant variables such as COVID-19 caused deaths or hospitalizations as output. We finally demonstrate the mechanics of the algorithm presenting the results of a case study performed with an epidemiological agent-based model.
RESULTS: We show that the developed method generates a highly robust vaccination prioritization plan which is proven to fulfill an elegant supremacy criterion: the plan is equally optimal for any quantity of vaccine doses available. The algorithm was tested on a case study in the Austrian context and it generated a vaccination plan prioritization favoring individuals age 65+, followed by vulnerable groups, to minimize COVID-19 related burden.
DISCUSSION: The results of the case study coincide with the international policy recommendations which strengthen the applicability of the approach. We conclude that the path-dependent optimum optimum provided by the algorithm is well suited for real world applications, in which decision makers need to develop strategies upfront under high levels of uncertainty.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND AND OBJECTIVE: The distribution of the newly developed vaccines presents a great challenge in the ongoing SARS-CoV-2 pandemic. Policy makers must decide which subgroups should be vaccinated first to minimize the negative consequences of the pandemic. These decisions must be made upfront and under uncertainty regarding the amount of vaccine doses available at a given time. The objective of the present work was to develop an iterative optimization algorithm, which provides a prioritization order of predefined subgroups. The results of this algorithm should be optimal but also robust with respect to potentially limited vaccine supply.
METHODS: We present an optimization meta-heuristic which can be used in a classic simulation-optimization setting with a simulation model in a feedback loop. The meta-heuristic can be applied in combination with any epidemiological simulation model capable of depicting the effects of vaccine distribution to the modeled population, accepts a vaccine prioritization plan in a certain notation as input, and generates decision making relevant variables such as COVID-19 caused deaths or hospitalizations as output. We finally demonstrate the mechanics of the algorithm presenting the results of a case study performed with an epidemiological agent-based model.
RESULTS: We show that the developed method generates a highly robust vaccination prioritization plan which is proven to fulfill an elegant supremacy criterion: the plan is equally optimal for any quantity of vaccine doses available. The algorithm was tested on a case study in the Austrian context and it generated a vaccination plan prioritization favoring individuals age 65+, followed by vulnerable groups, to minimize COVID-19 related burden.
DISCUSSION: The results of the case study coincide with the international policy recommendations which strengthen the applicability of the approach. We conclude that the path-dependent optimum optimum provided by the algorithm is well suited for real world applications, in which decision makers need to develop strategies upfront under high levels of uncertainty.
METHODS: We present an optimization meta-heuristic which can be used in a classic simulation-optimization setting with a simulation model in a feedback loop. The meta-heuristic can be applied in combination with any epidemiological simulation model capable of depicting the effects of vaccine distribution to the modeled population, accepts a vaccine prioritization plan in a certain notation as input, and generates decision making relevant variables such as COVID-19 caused deaths or hospitalizations as output. We finally demonstrate the mechanics of the algorithm presenting the results of a case study performed with an epidemiological agent-based model.
RESULTS: We show that the developed method generates a highly robust vaccination prioritization plan which is proven to fulfill an elegant supremacy criterion: the plan is equally optimal for any quantity of vaccine doses available. The algorithm was tested on a case study in the Austrian context and it generated a vaccination plan prioritization favoring individuals age 65+, followed by vulnerable groups, to minimize COVID-19 related burden.
DISCUSSION: The results of the case study coincide with the international policy recommendations which strengthen the applicability of the approach. We conclude that the path-dependent optimum optimum provided by the algorithm is well suited for real world applications, in which decision makers need to develop strategies upfront under high levels of uncertainty.
Suhaimi, Nurul M; Ghatnekar, Shilpa; Vahdat, Vahab; Griffin, Jacqueline; Rosmarin, David; Yang, F Clarissa
2022.
@{pmid33631214,
title = {Operationally balancing resident education and patient waiting time in an outpatient academic setting},
author = {Nurul M Suhaimi and Shilpa Ghatnekar and Vahab Vahdat and Jacqueline Griffin and David Rosmarin and F Clarissa Yang},
doi = {10.1016/j.jaad.2021.02.049},
issn = {1097-6787},
year = {2022},
date = {2022-01-01},
journal = {J Am Acad Dermatol},
volume = {86},
number = {3},
pages = {669--672},
keywords = {},
pubstate = {published},
tppubtype = {}
}
Stojkov, Igor; Conrads-Frank, Annette; Rochau, Ursula; Koinig, Karin A; Arvandi, Marjan; Puntscher, Sibylle; van Marrewijk, Corine; Fenaux, Pierre; Symeonidis, Argiris; Chermat, Fatiha; Garelius, Hege; Bowen, David; Mittelman, Moshe; Mora, Elvira; de Witte, Theo; Efficace, Fabio; Siebert, Uwe; Stauder, Reinhard
Core set of patient-reported outcomes for myelodysplastic syndromes: an EUMDS Delphi study involving patients and hematologists Journal Article
In: Blood Adv, vol. 6, no. 1, pp. 1–12, 2022, ISSN: 2473-9537.
@article{pmid34492684,
title = {Core set of patient-reported outcomes for myelodysplastic syndromes: an EUMDS Delphi study involving patients and hematologists},
author = {Igor Stojkov and Annette Conrads-Frank and Ursula Rochau and Karin A Koinig and Marjan Arvandi and Sibylle Puntscher and Corine van Marrewijk and Pierre Fenaux and Argiris Symeonidis and Fatiha Chermat and Hege Garelius and David Bowen and Moshe Mittelman and Elvira Mora and Theo de Witte and Fabio Efficace and Uwe Siebert and Reinhard Stauder},
doi = {10.1182/bloodadvances.2021004568},
issn = {2473-9537},
year = {2022},
date = {2022-01-01},
journal = {Blood Adv},
volume = {6},
number = {1},
pages = {1--12},
abstract = {Patient-reported outcomes (PROs) are relevant and valuable end points in the care of patients with myelodysplastic syndromes (MDS). However, a consensus-based selection of PROs for MDS, derived by both patients and hematologists, is lacking. We aimed to develop a core set of PROs for patients with MDS as part of the prospective European LeukemiaNet MDS (EUMDS) Registry. According to international guidelines, candidate PROs were identified from a comprehensive literature search of MDS studies. Overall, 40 PROs were selected and evaluated in a two-round Delphi survey by 40 patients with MDS and 38 hematologists in the first round and 38 patients and 32 hematologists in the second round. Based on an agreement scale and predefined inclusion criteria, both patients and hematologists selected "general quality of life" as a core PRO. Hematologists also selected "transfusion-dependency burden" and "ability to work/activities of daily living" as core PROs. The second Delphi round increased PRO rating agreements. Statistically significant rating differences between patients and hematologists were observed for 28 PROs (Mann-Whitney U test; P < .05) in the first round and for 19 PROs in the second round, with "disease knowledge" and "confidence in health care services" rated notably higher by patients. The overall mean PRO ratings correlation between the 2 groups was moderate (Spearman's rank correlation coefficient = 0.5; P < .05). This first consensus on a core set of PROs jointly developed by patients and hematologists forms the basis for patient-centered care in daily practice and clinical research.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Patient-reported outcomes (PROs) are relevant and valuable end points in the care of patients with myelodysplastic syndromes (MDS). However, a consensus-based selection of PROs for MDS, derived by both patients and hematologists, is lacking. We aimed to develop a core set of PROs for patients with MDS as part of the prospective European LeukemiaNet MDS (EUMDS) Registry. According to international guidelines, candidate PROs were identified from a comprehensive literature search of MDS studies. Overall, 40 PROs were selected and evaluated in a two-round Delphi survey by 40 patients with MDS and 38 hematologists in the first round and 38 patients and 32 hematologists in the second round. Based on an agreement scale and predefined inclusion criteria, both patients and hematologists selected "general quality of life" as a core PRO. Hematologists also selected "transfusion-dependency burden" and "ability to work/activities of daily living" as core PROs. The second Delphi round increased PRO rating agreements. Statistically significant rating differences between patients and hematologists were observed for 28 PROs (Mann-Whitney U test; P < .05) in the first round and for 19 PROs in the second round, with "disease knowledge" and "confidence in health care services" rated notably higher by patients. The overall mean PRO ratings correlation between the 2 groups was moderate (Spearman's rank correlation coefficient = 0.5; P < .05). This first consensus on a core set of PROs jointly developed by patients and hematologists forms the basis for patient-centered care in daily practice and clinical research.
Kuehne, Felicitas; Rochau, Ursula; Paracha, Noman; Yeh, Jennifer M; Sabate, Eduardo; Siebert, Uwe
In: Med Decis Making, vol. 42, no. 2, pp. 194–207, 2022, ISSN: 1552-681X.
@article{pmid34666553,
title = {Estimating Treatment-Switching Bias in a Randomized Clinical Trial of Ovarian Cancer Treatment: Combining Causal Inference with Decision-Analytic Modeling},
author = {Felicitas Kuehne and Ursula Rochau and Noman Paracha and Jennifer M Yeh and Eduardo Sabate and Uwe Siebert},
url = {https://pubmed.ncbi.nlm.nih.gov/34666553/},
doi = {10.1177/0272989X211026288},
issn = {1552-681X},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
journal = {Med Decis Making},
volume = {42},
number = {2},
pages = {194--207},
abstract = {BACKGROUND: Bevacizumab is efficacious in delaying ovarian cancer progression and controlling ascites. The ICON7 trial showed a significant benefit in overall survival for bevacizumab, whereas the GOG-218 trial did not. GOG-218 allowed control group patients to switch to bevacizumab upon progression, which may have biased the results. Lack of data on switching behavior prevented the application of g-methods to adjust for switching. The objective of this study was to apply decision-analytic modeling to estimate the impact of switching bias on causal treatment-effect estimates.
METHODS: We developed a causal decision-analytic Markov model (CDAMM) to emulate the GOG-218 trial and estimate overall survival. CDAMM input parameters were based on data from randomized clinical trials and the published literature. Overall switching proportion was based on GOG-218 trial information, whereas the proportion switching with and without ascites was estimated using calibration. We estimated the counterfactual treatment effect that would have been observed had no switching occurred by denying switching in the CDAMM.
RESULTS: The survival curves generated by the CDAMM matched well with the ones reported in the GOG-218 trial. The survival curve correcting for switching showed an estimated bias such that 79% of the true treatment effect could not be observed in the GOG-218 trial. Results were most sensitive to changes in the proportion progressing with severe ascites and mortality.
LIMITATIONS: We used a simplified model structure and based model parameters on published data and assumptions. Robustness of the CDAMM was tested and model assumptions transparently reported.
CONCLUSIONS: Medical-decision science methods may be merged with empirical methods of causal inference to integrate data from other sources where empirical data are not sufficient. We recommend collecting sufficient information on switching behavior when switching cannot be avoided.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: Bevacizumab is efficacious in delaying ovarian cancer progression and controlling ascites. The ICON7 trial showed a significant benefit in overall survival for bevacizumab, whereas the GOG-218 trial did not. GOG-218 allowed control group patients to switch to bevacizumab upon progression, which may have biased the results. Lack of data on switching behavior prevented the application of g-methods to adjust for switching. The objective of this study was to apply decision-analytic modeling to estimate the impact of switching bias on causal treatment-effect estimates.
METHODS: We developed a causal decision-analytic Markov model (CDAMM) to emulate the GOG-218 trial and estimate overall survival. CDAMM input parameters were based on data from randomized clinical trials and the published literature. Overall switching proportion was based on GOG-218 trial information, whereas the proportion switching with and without ascites was estimated using calibration. We estimated the counterfactual treatment effect that would have been observed had no switching occurred by denying switching in the CDAMM.
RESULTS: The survival curves generated by the CDAMM matched well with the ones reported in the GOG-218 trial. The survival curve correcting for switching showed an estimated bias such that 79% of the true treatment effect could not be observed in the GOG-218 trial. Results were most sensitive to changes in the proportion progressing with severe ascites and mortality.
LIMITATIONS: We used a simplified model structure and based model parameters on published data and assumptions. Robustness of the CDAMM was tested and model assumptions transparently reported.
CONCLUSIONS: Medical-decision science methods may be merged with empirical methods of causal inference to integrate data from other sources where empirical data are not sufficient. We recommend collecting sufficient information on switching behavior when switching cannot be avoided.
METHODS: We developed a causal decision-analytic Markov model (CDAMM) to emulate the GOG-218 trial and estimate overall survival. CDAMM input parameters were based on data from randomized clinical trials and the published literature. Overall switching proportion was based on GOG-218 trial information, whereas the proportion switching with and without ascites was estimated using calibration. We estimated the counterfactual treatment effect that would have been observed had no switching occurred by denying switching in the CDAMM.
RESULTS: The survival curves generated by the CDAMM matched well with the ones reported in the GOG-218 trial. The survival curve correcting for switching showed an estimated bias such that 79% of the true treatment effect could not be observed in the GOG-218 trial. Results were most sensitive to changes in the proportion progressing with severe ascites and mortality.
LIMITATIONS: We used a simplified model structure and based model parameters on published data and assumptions. Robustness of the CDAMM was tested and model assumptions transparently reported.
CONCLUSIONS: Medical-decision science methods may be merged with empirical methods of causal inference to integrate data from other sources where empirical data are not sufficient. We recommend collecting sufficient information on switching behavior when switching cannot be avoided.
Garcia, Gian-Gabriel; Schumb, Caroline; Lavieri, Mariel S; Koffijberg, Hendrik; McAllister, Thomas; McCrea, Michael; Broglio, Steven P
Developing Insights for Possible and Probable Acute Concussions Using Cluster Analysis. Journal Article
In: Journal of neurotrauma, vol. 39, iss. 1-2, pp. 102-113, 2022, ISSN: 1557-9042.
@article{Garcia2021,
title = {Developing Insights for Possible and Probable Acute Concussions Using Cluster Analysis.},
author = {Gian-Gabriel Garcia and Caroline Schumb and Mariel S Lavieri and Hendrik Koffijberg and Thomas McAllister and Michael McCrea and Steven P Broglio},
url = {https://pubmed.ncbi.nlm.nih.gov/33674923/},
doi = {10.1089/neu.2020.7399},
issn = {1557-9042},
year = {2022},
date = {2022-01-01},
urldate = {2021-03-01},
journal = {Journal of neurotrauma},
volume = {39},
issue = {1-2},
pages = {102-113},
abstract = {Few studies have analyzed the Sport Concussion Assessment Tool's (SCAT) utility among athletes whose concussion assessment is challenging. Using a previously published algorithm, we identified Possible and Probable concussions at <6h (n=393 male},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Few studies have analyzed the Sport Concussion Assessment Tool's (SCAT) utility among athletes whose concussion assessment is challenging. Using a previously published algorithm, we identified Possible and Probable concussions at <6h (n=393 male
2021
Markby, Jessica; Shilton, Sonjelle; Sem, Xiaohui; Chan, Huan Keat; Said, Rosaida Md; Siva, Sasikala; Zainuddin, Zalwani; Bakar, Norasiah Abu; Omar, Haniza; Ruiz, Ryan Jose Iii; Gaeddert, Mary; Tyshkovskiy, Alexander; Adee, Madeline; Chhatwal, Jagpreet; Kumar, Suresh; Piedagnel, Jean-Michel; Zain, Rozainanee Mohd; Menétrey, Caroline; Yuswan, Fazidah; Nasir, Nazrila Hairizan; Andrieux-Meyer, Isabelle; Ismail, Fatanah; Zakaria, Rozita; Hasim, Ruziaton; Murad, Shahnaz; Easterbrook, Philippa; Hassan, Muhammad Radzi Abu
In: BMJ Open, vol. 11, no. 12, pp. e055142, 2021, ISSN: 2044-6055, ().
@article{pmid34952885,
title = {Assessing the impact of simplified HCV care on linkage to care amongst high-risk patients at primary healthcare clinics in Malaysia: a prospective observational study},
author = {Jessica Markby and Sonjelle Shilton and Xiaohui Sem and Huan Keat Chan and Rosaida Md Said and Sasikala Siva and Zalwani Zainuddin and Norasiah Abu Bakar and Haniza Omar and Ryan Jose Iii Ruiz and Mary Gaeddert and Alexander Tyshkovskiy and Madeline Adee and Jagpreet Chhatwal and Suresh Kumar and Jean-Michel Piedagnel and Rozainanee Mohd Zain and Caroline Men\'{e}trey and Fazidah Yuswan and Nazrila Hairizan Nasir and Isabelle Andrieux-Meyer and Fatanah Ismail and Rozita Zakaria and Ruziaton Hasim and Shahnaz Murad and Philippa Easterbrook and Muhammad Radzi Abu Hassan},
doi = {10.1136/bmjopen-2021-055142},
issn = {2044-6055},
year = {2021},
date = {2021-12-01},
journal = {BMJ Open},
volume = {11},
number = {12},
pages = {e055142},
abstract = {INTRODUCTION: To achieve the elimination of hepatitis C virus (HCV), substantial scale-up in access to testing and treatment is needed. This will require innovation and simplification of the care pathway, through decentralisation of testing and treatment to primary care settings and task-shifting to non-specialists. The objective of this study was to evaluate the feasibility and effectiveness of decentralisation of HCV testing and treatment using rapid diagnostic tests (RDTs) in primary healthcare clinics (PHCs) among high-risk populations, with referral of seropositive patients for confirmatory viral load testing and treatment.
METHODS: This observational study was conducted between December 2018 and October 2019 at 25 PHCs in three regions in Malaysia. Each PHC was linked to one or more hospitals, for referral of seropositive participants for confirmatory testing and pretreatment evaluation. Treatment was provided in PHCs for non-cirrhotic patients and at hospitals for cirrhotic patients.
RESULTS: During the study period, a total of 15 366 adults were screened at the 25 PHCs, using RDTs for HCV antibodies. Of the 2020 (13.2%) HCV antibody-positive participants, 1481/2020 (73.3%) had a confirmatory viral load test, 1241/1481 (83.8%) were HCV RNA-positive, 991/1241 (79.9%) completed pretreatment assessment, 632/991 (63.8%) initiated treatment, 518/632 (82.0%) completed treatment, 352/518 (68.0%) were eligible for a sustained virological response (SVR) cure assessment, 209/352 (59.4%) had an SVR cure assessment, and SVR was achieved in 202/209 (96.7%) patients. A significantly higher proportion of patients referred to PHCs initiated treatment compared with those who had treatment initiated at hospitals (71.0% vs 48.8%, p<0.001).
CONCLUSIONS: This study demonstrated the effectiveness and feasibility of a simplified decentralised HCV testing and treatment model in primary healthcare settings, targeting high-risk groups in Malaysia. There were good outcomes across most steps of the cascade of care when treatment was provided at PHCs compared with hospitals.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
INTRODUCTION: To achieve the elimination of hepatitis C virus (HCV), substantial scale-up in access to testing and treatment is needed. This will require innovation and simplification of the care pathway, through decentralisation of testing and treatment to primary care settings and task-shifting to non-specialists. The objective of this study was to evaluate the feasibility and effectiveness of decentralisation of HCV testing and treatment using rapid diagnostic tests (RDTs) in primary healthcare clinics (PHCs) among high-risk populations, with referral of seropositive patients for confirmatory viral load testing and treatment.
METHODS: This observational study was conducted between December 2018 and October 2019 at 25 PHCs in three regions in Malaysia. Each PHC was linked to one or more hospitals, for referral of seropositive participants for confirmatory testing and pretreatment evaluation. Treatment was provided in PHCs for non-cirrhotic patients and at hospitals for cirrhotic patients.
RESULTS: During the study period, a total of 15 366 adults were screened at the 25 PHCs, using RDTs for HCV antibodies. Of the 2020 (13.2%) HCV antibody-positive participants, 1481/2020 (73.3%) had a confirmatory viral load test, 1241/1481 (83.8%) were HCV RNA-positive, 991/1241 (79.9%) completed pretreatment assessment, 632/991 (63.8%) initiated treatment, 518/632 (82.0%) completed treatment, 352/518 (68.0%) were eligible for a sustained virological response (SVR) cure assessment, 209/352 (59.4%) had an SVR cure assessment, and SVR was achieved in 202/209 (96.7%) patients. A significantly higher proportion of patients referred to PHCs initiated treatment compared with those who had treatment initiated at hospitals (71.0% vs 48.8%, p<0.001).
CONCLUSIONS: This study demonstrated the effectiveness and feasibility of a simplified decentralised HCV testing and treatment model in primary healthcare settings, targeting high-risk groups in Malaysia. There were good outcomes across most steps of the cascade of care when treatment was provided at PHCs compared with hospitals.
METHODS: This observational study was conducted between December 2018 and October 2019 at 25 PHCs in three regions in Malaysia. Each PHC was linked to one or more hospitals, for referral of seropositive participants for confirmatory testing and pretreatment evaluation. Treatment was provided in PHCs for non-cirrhotic patients and at hospitals for cirrhotic patients.
RESULTS: During the study period, a total of 15 366 adults were screened at the 25 PHCs, using RDTs for HCV antibodies. Of the 2020 (13.2%) HCV antibody-positive participants, 1481/2020 (73.3%) had a confirmatory viral load test, 1241/1481 (83.8%) were HCV RNA-positive, 991/1241 (79.9%) completed pretreatment assessment, 632/991 (63.8%) initiated treatment, 518/632 (82.0%) completed treatment, 352/518 (68.0%) were eligible for a sustained virological response (SVR) cure assessment, 209/352 (59.4%) had an SVR cure assessment, and SVR was achieved in 202/209 (96.7%) patients. A significantly higher proportion of patients referred to PHCs initiated treatment compared with those who had treatment initiated at hospitals (71.0% vs 48.8%, p<0.001).
CONCLUSIONS: This study demonstrated the effectiveness and feasibility of a simplified decentralised HCV testing and treatment model in primary healthcare settings, targeting high-risk groups in Malaysia. There were good outcomes across most steps of the cascade of care when treatment was provided at PHCs compared with hospitals.
Claypool, Anneke L; Brandeau, Margaret L; Goldhaber-Fiebert, Jeremy D
Prevention and control of dengue and Chikungunya in Colombia: A cost-effectiveness analysis Journal Article
In: PLoS Negl Trop Dis, vol. 15, no. 12, pp. e0010086, 2021, ISSN: 1935-2735, ().
@article{pmid34965277,
title = {Prevention and control of dengue and Chikungunya in Colombia: A cost-effectiveness analysis},
author = {Anneke L Claypool and Margaret L Brandeau and Jeremy D Goldhaber-Fiebert},
doi = {10.1371/journal.pntd.0010086},
issn = {1935-2735},
year = {2021},
date = {2021-12-01},
journal = {PLoS Negl Trop Dis},
volume = {15},
number = {12},
pages = {e0010086},
abstract = {BACKGROUND: Chikungunya and dengue are emerging diseases that have caused large outbreaks in various regions of the world. Both are both spread by Aedes aegypti and Aedes albopictus mosquitos. We developed a dynamic transmission model of chikungunya and dengue, calibrated to data from Colombia (June 2014 -December 2017).
METHODOLOGY/PRINCIPAL FINDINGS: We evaluated the health benefits and cost-effectiveness of residual insecticide treatment, long-lasting insecticide-treated nets, routine dengue vaccination for children aged 9, catchup vaccination for individuals aged 10-19 or 10-29, and portfolios of these interventions. Model calibration resulted in 300 realistic transmission parameters sets that produced close matches to disease-specific incidence and deaths. Insecticide was the preferred intervention and was cost-effective. Insecticide averted an estimated 95 chikungunya cases and 114 dengue cases per 100,000 people, 61 deaths, and 4,523 disability-adjusted life years (DALYs). In sensitivity analysis, strategies that included dengue vaccination were cost-effective only when the vaccine cost was 14% of the current price.
CONCLUSIONS/SIGNIFICANCE: Insecticide to prevent chikungunya and dengue in Columbia could generate significant health benefits and be cost-effective. Because of limits on diagnostic accuracy and vaccine efficacy, the cost of dengue testing and vaccination must decrease dramatically for such vaccination to be cost-effective in Colombia. The vectors for chikungunya and dengue have recently spread to new regions, highlighting the importance of understanding the effectiveness and cost-effectiveness of policies aimed at preventing these diseases.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: Chikungunya and dengue are emerging diseases that have caused large outbreaks in various regions of the world. Both are both spread by Aedes aegypti and Aedes albopictus mosquitos. We developed a dynamic transmission model of chikungunya and dengue, calibrated to data from Colombia (June 2014 -December 2017).
METHODOLOGY/PRINCIPAL FINDINGS: We evaluated the health benefits and cost-effectiveness of residual insecticide treatment, long-lasting insecticide-treated nets, routine dengue vaccination for children aged 9, catchup vaccination for individuals aged 10-19 or 10-29, and portfolios of these interventions. Model calibration resulted in 300 realistic transmission parameters sets that produced close matches to disease-specific incidence and deaths. Insecticide was the preferred intervention and was cost-effective. Insecticide averted an estimated 95 chikungunya cases and 114 dengue cases per 100,000 people, 61 deaths, and 4,523 disability-adjusted life years (DALYs). In sensitivity analysis, strategies that included dengue vaccination were cost-effective only when the vaccine cost was 14% of the current price.
CONCLUSIONS/SIGNIFICANCE: Insecticide to prevent chikungunya and dengue in Columbia could generate significant health benefits and be cost-effective. Because of limits on diagnostic accuracy and vaccine efficacy, the cost of dengue testing and vaccination must decrease dramatically for such vaccination to be cost-effective in Colombia. The vectors for chikungunya and dengue have recently spread to new regions, highlighting the importance of understanding the effectiveness and cost-effectiveness of policies aimed at preventing these diseases.
METHODOLOGY/PRINCIPAL FINDINGS: We evaluated the health benefits and cost-effectiveness of residual insecticide treatment, long-lasting insecticide-treated nets, routine dengue vaccination for children aged 9, catchup vaccination for individuals aged 10-19 or 10-29, and portfolios of these interventions. Model calibration resulted in 300 realistic transmission parameters sets that produced close matches to disease-specific incidence and deaths. Insecticide was the preferred intervention and was cost-effective. Insecticide averted an estimated 95 chikungunya cases and 114 dengue cases per 100,000 people, 61 deaths, and 4,523 disability-adjusted life years (DALYs). In sensitivity analysis, strategies that included dengue vaccination were cost-effective only when the vaccine cost was 14% of the current price.
CONCLUSIONS/SIGNIFICANCE: Insecticide to prevent chikungunya and dengue in Columbia could generate significant health benefits and be cost-effective. Because of limits on diagnostic accuracy and vaccine efficacy, the cost of dengue testing and vaccination must decrease dramatically for such vaccination to be cost-effective in Colombia. The vectors for chikungunya and dengue have recently spread to new regions, highlighting the importance of understanding the effectiveness and cost-effectiveness of policies aimed at preventing these diseases.
Damgacioglu, Haluk; Sonawane, Kalyani; Chhatwal, Jagpreet; Lairson, David R.; Clifford, Gary M.; Giuliano, Anna R.; Deshmukh, Ashish A.
Long-term impact of HPV vaccination and COVID-19 pandemic on oropharyngeal cancer incidence and burden among men in the USA: A modeling study. Journal Article
In: Lancet Regional Health. Americas, pp. 100143, 2021, ISSN: 2667-193X, ().
@article{Damgacioglu2021,
title = {Long-term impact of HPV vaccination and COVID-19 pandemic on oropharyngeal cancer incidence and burden among men in the USA: A modeling study.},
author = {Haluk Damgacioglu and Kalyani Sonawane and Jagpreet Chhatwal and David R. Lairson and Gary M. Clifford and Anna R. Giuliano and Ashish A. Deshmukh},
url = {https://pubmed.ncbi.nlm.nih.gov/34927126/},
doi = {10.1016/j.lana.2021.100143},
issn = {2667-193X},
year = {2021},
date = {2021-12-01},
journal = {Lancet Regional Health. Americas},
pages = {100143},
abstract = {Oropharyngeal cancer (OPC) incidence is rising rapidly among men in the United States of America (USA). We aimed to project the impact of maintaining the current HPV vaccination uptake and achieving 80% national (Healthy People) goal on OPC incidence and burden. We developed an open-cohort micro-simulation model of OPC natural history among contemporary and future birth cohorts of men, accounting for sexual behaviors, population growth, aging, and herd immunity. We used data from nationally representative databases, cancer registries from all 50 states, large clinical trials, and literature. We evaluated the status quo scenario (the current HPV vaccination uptake remained stable) and alternative scenarios of improvements in uptake rates in adolescents (aged 9-17 years) and young adults (aged 18-26 years) by 2025 to achieve and maintain the 80% goal. The primary outcome was to project OPC incidence and burden from 2009 to 2100. We also assessed the impact of disruption in HPV vaccine uptake during the COVID-19 pandemic. OPC incidence is projected to rise until the mid-2030s, reaching the age-standardized incidence rate of 9·8 (95% uncertainty interval [UI] 9·5-10·1) per 100 000 men, with the peak annual burden of 23 850 (UI, 23 200-24 500) cases. Under the status quo scenario, HPV vaccination could prevent 124 000 (UI, 117 000-131 000) by 2060, 400 000 (UI, 384 000-416 000) by 2080, and 792 000 (UI, 763 000-821 000) by 2100 OPC cases among men. Achievement and maintenance of 80% coverage among adolescent girls only, adolescent girls and boys, and adolescents plus young adults could prevent an additional number of 100 000 (UI, 95 000-105 000), 118 000 (UI, 113 000-123 000), and 142 000 (UI, 136 000-148 000) male OPC cases by 2100. Delayed recovery of the HPV vaccine uptake during the COVID-19 pandemic could lead to 600 (UI, 580-620) to 6200 (UI, 5940-6460) additional male OPC cases by 2100, conditional on the decline in the extent of the national HPV vaccination coverage and potential delay in rebounding. Oropharyngeal cancer burden is projected to rise among men in the USA. Nationwide efforts to achieve the HPV vaccination goal of 80% coverage should be a public health priority. Rapid recovery of the declined HPV vaccination uptake during the COVID-19 pandemic is also crucial to prevent future excess OPC burden. National Cancer Institute and National Institute on Minority Health and Health Disparities of the USA.},
keywords = {},
pubstate = {aheadofprint},
tppubtype = {article}
}
Oropharyngeal cancer (OPC) incidence is rising rapidly among men in the United States of America (USA). We aimed to project the impact of maintaining the current HPV vaccination uptake and achieving 80% national (Healthy People) goal on OPC incidence and burden. We developed an open-cohort micro-simulation model of OPC natural history among contemporary and future birth cohorts of men, accounting for sexual behaviors, population growth, aging, and herd immunity. We used data from nationally representative databases, cancer registries from all 50 states, large clinical trials, and literature. We evaluated the status quo scenario (the current HPV vaccination uptake remained stable) and alternative scenarios of improvements in uptake rates in adolescents (aged 9-17 years) and young adults (aged 18-26 years) by 2025 to achieve and maintain the 80% goal. The primary outcome was to project OPC incidence and burden from 2009 to 2100. We also assessed the impact of disruption in HPV vaccine uptake during the COVID-19 pandemic. OPC incidence is projected to rise until the mid-2030s, reaching the age-standardized incidence rate of 9·8 (95% uncertainty interval [UI] 9·5-10·1) per 100 000 men, with the peak annual burden of 23 850 (UI, 23 200-24 500) cases. Under the status quo scenario, HPV vaccination could prevent 124 000 (UI, 117 000-131 000) by 2060, 400 000 (UI, 384 000-416 000) by 2080, and 792 000 (UI, 763 000-821 000) by 2100 OPC cases among men. Achievement and maintenance of 80% coverage among adolescent girls only, adolescent girls and boys, and adolescents plus young adults could prevent an additional number of 100 000 (UI, 95 000-105 000), 118 000 (UI, 113 000-123 000), and 142 000 (UI, 136 000-148 000) male OPC cases by 2100. Delayed recovery of the HPV vaccine uptake during the COVID-19 pandemic could lead to 600 (UI, 580-620) to 6200 (UI, 5940-6460) additional male OPC cases by 2100, conditional on the decline in the extent of the national HPV vaccination coverage and potential delay in rebounding. Oropharyngeal cancer burden is projected to rise among men in the USA. Nationwide efforts to achieve the HPV vaccination goal of 80% coverage should be a public health priority. Rapid recovery of the declined HPV vaccination uptake during the COVID-19 pandemic is also crucial to prevent future excess OPC burden. National Cancer Institute and National Institute on Minority Health and Health Disparities of the USA.
Gowda, Vrushab; Cheng, Glen; Harvey, H. Benjamin
Safeguarding Data Security in the Era of Imaging mHealth. Journal Article
In: AJR. American journal of roentgenology, 2021, ISSN: 1546-3141, ().
@article{Gowda2021,
title = {Safeguarding Data Security in the Era of Imaging mHealth.},
author = {Vrushab Gowda and Glen Cheng and H. Benjamin Harvey},
url = {https://pubmed.ncbi.nlm.nih.gov/34910541/},
doi = {10.2214/AJR.21.26901},
issn = {1546-3141},
year = {2021},
date = {2021-12-01},
journal = {AJR. American journal of roentgenology},
abstract = {Mobile health (mHealth) technologies stand poised to find broad application in the radiology space. They hold considerable promise for millions of Americans, enabling at-home imaging and augmenting clinical decision-making. However, they often lie outside the ambit of the FDA and process vast quantities of data largely unprotected by HIPAA. This Viewpoint explores the features of federal mHealth policy relevant to imaging practice and advocates for greater regulatory clarity to assist radiologists, developers, and ultimately, patients.},
keywords = {},
pubstate = {aheadofprint},
tppubtype = {article}
}
Mobile health (mHealth) technologies stand poised to find broad application in the radiology space. They hold considerable promise for millions of Americans, enabling at-home imaging and augmenting clinical decision-making. However, they often lie outside the ambit of the FDA and process vast quantities of data largely unprotected by HIPAA. This Viewpoint explores the features of federal mHealth policy relevant to imaging practice and advocates for greater regulatory clarity to assist radiologists, developers, and ultimately, patients.
Schnell-Inderst, Petra; Laschkolnig, Anja; Marckmann, Georg; Antony, Daniela; Siebert, Uwe; Mühlberger, Nikolai
In: Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)), 2021, ISSN: 1439-4421, ().
@article{SchnellInderst2021,
title = {[Testicular Cancer Screening in Men Aged 16 Years and Older: IQWiG ThemenCheck Health Technology Assessment Report on Medical, Economic, Social, Ethical, Legal and Organisational Aspects].},
author = {Petra Schnell-Inderst and Anja Laschkolnig and Georg Marckmann and Daniela Antony and Uwe Siebert and Nikolai M\"{u}hlberger},
url = {https://pubmed.ncbi.nlm.nih.gov/34872119/},
doi = {10.1055/a-1658-0057},
issn = {1439-4421},
year = {2021},
date = {2021-12-01},
journal = {Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany))},
abstract = {Testicular cancer occurs mainly in young men between 25 and 45 years and is the most common cancer at this age. Possible testicular cancer early detection measures, clinical palpation and scrotal ultrasound (CUS) or testicular self-examination (TSE) in asymptomatic men aged 16 years and older, could perhaps avoid deaths and aggressive late therapies. Therefore, we investigated whether these measures have an additional benefit compared to the current situation. Ethical, legal, social and organisational aspects were considered as well. The methodology of this review follows IQWiG's "Allgemeine[n] Methoden Version 5.0". In addition, to estimate the theoretically possible benefits and potential harms of screening, a supplementary presentation was used for the benefit assessment based on published data from tumour registries and data on predictive values from diagnostic studies. No intervention studies were identified, therefore evidence-based statements on additional benefit or harm of the studied interventions could not be made. The epidemiological data showed that per 100,000 men participating in screening annually, a maximum of 1.2 advanced tumours and 0.4 deaths would have been preventable. Harm calculations suggest that with CUS of 100,000 men, 1 to 22 unnecessary testicular exposures or removals might be expected, with TSE it would be 2 cases. However, these data on the possible harm of screening are subject to great uncertainty. There are no intervention studies demonstrating that the benefit of testicular cancer screening in men aged 16 years and older outweighs the harm. The maximum possible additional benefit is low and chances of detection and cure are good even without screening. At present, testicular cancer screening cannot be recommended.},
keywords = {},
pubstate = {aheadofprint},
tppubtype = {article}
}
Testicular cancer occurs mainly in young men between 25 and 45 years and is the most common cancer at this age. Possible testicular cancer early detection measures, clinical palpation and scrotal ultrasound (CUS) or testicular self-examination (TSE) in asymptomatic men aged 16 years and older, could perhaps avoid deaths and aggressive late therapies. Therefore, we investigated whether these measures have an additional benefit compared to the current situation. Ethical, legal, social and organisational aspects were considered as well. The methodology of this review follows IQWiG's "Allgemeine[n] Methoden Version 5.0". In addition, to estimate the theoretically possible benefits and potential harms of screening, a supplementary presentation was used for the benefit assessment based on published data from tumour registries and data on predictive values from diagnostic studies. No intervention studies were identified, therefore evidence-based statements on additional benefit or harm of the studied interventions could not be made. The epidemiological data showed that per 100,000 men participating in screening annually, a maximum of 1.2 advanced tumours and 0.4 deaths would have been preventable. Harm calculations suggest that with CUS of 100,000 men, 1 to 22 unnecessary testicular exposures or removals might be expected, with TSE it would be 2 cases. However, these data on the possible harm of screening are subject to great uncertainty. There are no intervention studies demonstrating that the benefit of testicular cancer screening in men aged 16 years and older outweighs the harm. The maximum possible additional benefit is low and chances of detection and cure are good even without screening. At present, testicular cancer screening cannot be recommended.
Wachtel, Heather; Roses, Robert E.; Kuo, Lindsay E.; Lindeman, Brenessa M.; Nehs, Matthew A.; Tavakkoli, Ali; Parangi, Sareh; Hodin, Richard A.; Fraker, Douglas L.; James, Benjamin C.; Carr, Azadeh A.; Wang, Tracy S.; Solórzano, Carmen C.; Lubitz, Carrie C.
Adrenalectomy for Secondary Malignancy: Patients, Outcomes, and Indications. Journal Article
In: Annals of surgery, vol. 274, no. 6, pp. 1073-1080, 2021, ISSN: 1528-1140, ().
@article{Wachtel2020,
title = {Adrenalectomy for Secondary Malignancy: Patients, Outcomes, and Indications.},
author = {Heather Wachtel and Robert E. Roses and Lindsay E. Kuo and Brenessa M. Lindeman and Matthew A. Nehs and Ali Tavakkoli and Sareh Parangi and Richard A. Hodin and Douglas L. Fraker and Benjamin C. James and Azadeh A. Carr and Tracy S. Wang and Carmen C. Sol\'{o}rzano and Carrie C. Lubitz},
url = {https://www.ncbi.nlm.nih.gov/pubmed/32427760},
doi = {10.1097/SLA.0000000000003876},
issn = {1528-1140},
year = {2021},
date = {2021-12-01},
urldate = {2020-05-01},
journal = {Annals of surgery},
volume = {274},
number = {6},
pages = {1073-1080},
abstract = {The goal of this study was to examine a multi-institutional experience with adrenal metastases to describe survival outcomes and identify subpopulations who benefit from adrenal metastasectomy. Adrenalectomy for metastatic disease is well-described, although indications and outcomes are incompletely defined. A retrospective cohort study was performed of patients undergoing adrenalectomy for secondary malignancy (2002-2015) at 6 institutions. The primary outcomes were disease free survival (DFS) and overall survival (OS). Analysis methods included Kaplan-Meier and Cox proportional hazards. Of 269 patients, mean age was 60.1 years; 50% were male. The most common primary malignancies were lung (n = 125, 47%), renal cell (n = 38, 14%), melanoma (n = 33, 12%), sarcoma (n = 18, 7%), and colorectal (n = 12, 5%). The median time to detection of adrenal metastasis after initial diagnosis of the primary tumor was 17 months (interquartile range: 6-41). Post-adrenalectomy, the median DFS was 18 months (1-year DFS: 54%, 5-year DFS: 31%). On multivariable analysis, lung primary was associated with longer DFS [hazard ratio (HR): 0.4},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The goal of this study was to examine a multi-institutional experience with adrenal metastases to describe survival outcomes and identify subpopulations who benefit from adrenal metastasectomy. Adrenalectomy for metastatic disease is well-described, although indications and outcomes are incompletely defined. A retrospective cohort study was performed of patients undergoing adrenalectomy for secondary malignancy (2002-2015) at 6 institutions. The primary outcomes were disease free survival (DFS) and overall survival (OS). Analysis methods included Kaplan-Meier and Cox proportional hazards. Of 269 patients, mean age was 60.1 years; 50% were male. The most common primary malignancies were lung (n = 125, 47%), renal cell (n = 38, 14%), melanoma (n = 33, 12%), sarcoma (n = 18, 7%), and colorectal (n = 12, 5%). The median time to detection of adrenal metastasis after initial diagnosis of the primary tumor was 17 months (interquartile range: 6-41). Post-adrenalectomy, the median DFS was 18 months (1-year DFS: 54%, 5-year DFS: 31%). On multivariable analysis, lung primary was associated with longer DFS [hazard ratio (HR): 0.4
Decouttere, Catherine; Banzimana, Stany; Davidsen, Pål; Riet, Carla Van; Vandermeulen, Corinne; Mason, Elizabeth; Jalali, Mohammad S.; Vandaele, Nico
Insights into vaccine hesitancy from systems thinking, Rwanda. Journal Article
In: Bulletin of the World Health Organization, vol. 99, pp. 783–794D, 2021, ISSN: 1564-0604, ().
@article{Decouttere2021,
title = {Insights into vaccine hesitancy from systems thinking, Rwanda.},
author = {Catherine Decouttere and Stany Banzimana and Pr{a}l Davidsen and Carla Van Riet and Corinne Vandermeulen and Elizabeth Mason and Mohammad S. Jalali and Nico Vandaele},
url = {https://pubmed.ncbi.nlm.nih.gov/34737471/},
doi = {10.2471/BLT.20.285258},
issn = {1564-0604},
year = {2021},
date = {2021-11-01},
journal = {Bulletin of the World Health Organization},
volume = {99},
pages = {783--794D},
abstract = {To investigate vaccine hesitancy leading to underimmunization and a measles outbreak in Rwanda and to develop a conceptual, community-level model of behavioural factors. Local immunization systems in two Rwandan communities (one recently experienced a measles outbreak) were explored using systems thinking, human-centred design and behavioural frameworks. Data were collected between 2018 and 2020 from: discussions with 11 vaccination service providers (i.e. hospital and health centre staff); interviews with 161 children's caregivers at health centres; and nine validation interviews with health centre staff. Factors influencing vaccine hesitancy were categorized using the 3Cs framework: confidence, complacency and convenience. A conceptual model of vaccine hesitancy mechanisms with feedback loops was developed. A comparison of service providers' and caregivers' perspectives in both rural and peri-urban settings showed that similar factors strengthened vaccine uptake: (i) high trust in vaccines and service providers based on personal relationships with health centre staff; (ii) the connecting role of community health workers; and (iii) a strong sense of community. Factors identified as increasing vaccine hesitancy (e.g. service accessibility and inadequate follow-up) differed between service providers and caregivers and between settings. The conceptual model could be used to explain drivers of the recent measles outbreak and to guide interventions designed to increase vaccine uptake. The application of behavioural frameworks and systems thinking revealed vaccine hesitancy mechanisms in Rwandan communities that demonstrate the interrelationship between immunization services and caregivers' vaccination behaviour. Confidence-building social structures and context-dependent challenges that affect vaccine uptake were also identified.},
keywords = {},
pubstate = {ppublish},
tppubtype = {article}
}
To investigate vaccine hesitancy leading to underimmunization and a measles outbreak in Rwanda and to develop a conceptual, community-level model of behavioural factors. Local immunization systems in two Rwandan communities (one recently experienced a measles outbreak) were explored using systems thinking, human-centred design and behavioural frameworks. Data were collected between 2018 and 2020 from: discussions with 11 vaccination service providers (i.e. hospital and health centre staff); interviews with 161 children's caregivers at health centres; and nine validation interviews with health centre staff. Factors influencing vaccine hesitancy were categorized using the 3Cs framework: confidence, complacency and convenience. A conceptual model of vaccine hesitancy mechanisms with feedback loops was developed. A comparison of service providers' and caregivers' perspectives in both rural and peri-urban settings showed that similar factors strengthened vaccine uptake: (i) high trust in vaccines and service providers based on personal relationships with health centre staff; (ii) the connecting role of community health workers; and (iii) a strong sense of community. Factors identified as increasing vaccine hesitancy (e.g. service accessibility and inadequate follow-up) differed between service providers and caregivers and between settings. The conceptual model could be used to explain drivers of the recent measles outbreak and to guide interventions designed to increase vaccine uptake. The application of behavioural frameworks and systems thinking revealed vaccine hesitancy mechanisms in Rwandan communities that demonstrate the interrelationship between immunization services and caregivers' vaccination behaviour. Confidence-building social structures and context-dependent challenges that affect vaccine uptake were also identified.
Adee, Madeline; Zhuo, Yueran; Zhong, Huaiyang; Zhan, Tiannan; Aggarwal, Rakesh; Shilton, Sonjelle; Chhatwal, Jagpreet
Assessing cost-effectiveness of hepatitis C testing pathways in Georgia using the Hep C Testing Calculator. Journal Article
In: Scientific reports, vol. 11, pp. 21382, 2021, ISSN: 2045-2322, ().
@article{Adee2021a,
title = {Assessing cost-effectiveness of hepatitis C testing pathways in Georgia using the Hep C Testing Calculator.},
author = {Madeline Adee and Yueran Zhuo and Huaiyang Zhong and Tiannan Zhan and Rakesh Aggarwal and Sonjelle Shilton and Jagpreet Chhatwal},
url = {https://pubmed.ncbi.nlm.nih.gov/34725356/},
doi = {10.1038/s41598-021-00362-y},
issn = {2045-2322},
year = {2021},
date = {2021-11-01},
journal = {Scientific reports},
volume = {11},
pages = {21382},
abstract = {The cost of testing can be a substantial contributor to hepatitis C virus (HCV) elimination program costs in many low- and middle-income countries such as Georgia, resulting in the need for innovative and cost-effective strategies for testing. Our objective was to investigate the most cost-effective testing pathways for scaling-up HCV testing in Georgia. We developed a Markov-based model with a lifetime horizon that simulates the natural history of HCV, and the cost of detection and treatment of HCV. We then created an interactive online tool that uses results from the Markov-based model to evaluate the cost-effectiveness of different HCV testing pathways. We compared the current standard-of-care (SoC) testing pathway and four innovative testing pathways for Georgia. The SoC testing was cost-saving compared to no testing, but all four new HCV testing pathways further increased QALYs and decreased costs. The pathway with the highest patient follow-up, due to on-site testing, resulted in the highest discounted QALYs (123 QALY more than the SoC) and lowest costs ($127,052 less than the SoC) per 10,000 persons screened. The current testing algorithm in Georgia can be replaced with a new pathway that is more effective while being cost-saving.},
keywords = {},
pubstate = {epublish},
tppubtype = {article}
}
The cost of testing can be a substantial contributor to hepatitis C virus (HCV) elimination program costs in many low- and middle-income countries such as Georgia, resulting in the need for innovative and cost-effective strategies for testing. Our objective was to investigate the most cost-effective testing pathways for scaling-up HCV testing in Georgia. We developed a Markov-based model with a lifetime horizon that simulates the natural history of HCV, and the cost of detection and treatment of HCV. We then created an interactive online tool that uses results from the Markov-based model to evaluate the cost-effectiveness of different HCV testing pathways. We compared the current standard-of-care (SoC) testing pathway and four innovative testing pathways for Georgia. The SoC testing was cost-saving compared to no testing, but all four new HCV testing pathways further increased QALYs and decreased costs. The pathway with the highest patient follow-up, due to on-site testing, resulted in the highest discounted QALYs (123 QALY more than the SoC) and lowest costs ($127,052 less than the SoC) per 10,000 persons screened. The current testing algorithm in Georgia can be replaced with a new pathway that is more effective while being cost-saving.
Harvey, Harlan Benjamin; Gowda, Vrushab
Regulatory Issues and Challenges to Artificial Intelligence Adoption. Journal Article
In: Radiologic clinics of North America, vol. 59, pp. 1075–1083, 2021, ISSN: 1557-8275, ().
@article{Harvey2021a,
title = {Regulatory Issues and Challenges to Artificial Intelligence Adoption.},
author = {Harlan Benjamin Harvey and Vrushab Gowda},
url = {https://pubmed.ncbi.nlm.nih.gov/34689875/},
doi = {10.1016/j.rcl.2021.07.007},
issn = {1557-8275},
year = {2021},
date = {2021-11-01},
journal = {Radiologic clinics of North America},
volume = {59},
pages = {1075--1083},
abstract = {Artificial intelligence technology promises to redefine the practice of radiology. However, it exists in a nascent phase and remains largely untested in the clinical space. This nature is both a cause and consequence of the uncertain legal-regulatory environment it enters. This discussion aims to shed light on these challenges, tracing the various pathways toward approval by the US Food and Drug Administration, the future of government oversight, privacy issues, ethical dilemmas, and practical considerations related to implementation in radiologist practice.},
keywords = {},
pubstate = {ppublish},
tppubtype = {article}
}
Artificial intelligence technology promises to redefine the practice of radiology. However, it exists in a nascent phase and remains largely untested in the clinical space. This nature is both a cause and consequence of the uncertain legal-regulatory environment it enters. This discussion aims to shed light on these challenges, tracing the various pathways toward approval by the US Food and Drug Administration, the future of government oversight, privacy issues, ethical dilemmas, and practical considerations related to implementation in radiologist practice.
Bicher, Martin; Rippinger, Claire; Urach, Christoph; Brunmeir, Dominik; Siebert, Uwe; Popper, Niki
Evaluation of Contact-Tracing Policies against the Spread of SARS-CoV-2 in Austria: An Agent-Based Simulation. Journal Article
In: Medical decision making : an international journal of the Society for Medical Decision Making, vol. 41, no. 8, pp. 1017-1032, 2021, ISSN: 1552-681X, ().
@article{Bicher2021,
title = {Evaluation of Contact-Tracing Policies against the Spread of SARS-CoV-2 in Austria: An Agent-Based Simulation.},
author = {Martin Bicher and Claire Rippinger and Christoph Urach and Dominik Brunmeir and Uwe Siebert and Niki Popper},
url = {https://pubmed.ncbi.nlm.nih.gov/34027734/},
doi = {10.1177/0272989X211013306},
issn = {1552-681X},
year = {2021},
date = {2021-11-01},
journal = {Medical decision making : an international journal of the Society for Medical Decision Making},
volume = {41},
number = {8},
pages = {1017-1032},
abstract = {Many countries have already gone through several infection waves and mostly managed to successfully stop the exponential spread of SARS-CoV-2 through bundles of restrictive measures. Still, the danger of further waves of infections is omnipresent, and it is apparent that every containment policy must be carefully evaluated and possibly replaced by a different, less restrictive policy before it can be lifted. Tracing of contacts and consequential breaking of infection chains is a promising strategy to help contain the disease, although its precise impact on the epidemic is unknown. In this work, we aim to quantify the impact of tracing on the containment of the disease and investigate the dynamic effects involved. We developed an agent-based model that validly depicts the spread of the disease and allows for exploratory analysis of containment policies. We applied this model to quantify the impact of different approaches of contact tracing in Austria to derive general conclusions on contract tracing. The study displays that strict tracing complements other intervention strategies. For the containment of the disease, the number of secondary infections must be reduced by about 75%. Implementing the proposed tracing strategy supplements measures worth about 5%. Evaluation of the number of preventively quarantined persons shows that household quarantine is the most effective in terms of avoided cases per quarantined person. The results are limited by the validity of the modeling assumptions, model parameter estimates, and the quality of the parametrization data. The study shows that tracing is indeed an efficient measure to keep case numbers low but comes at a high price if the disease is not well contained. Therefore, contact tracing must be executed strictly, and adherence within the population must be held up to prevent uncontrolled outbreaks of the disease.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Many countries have already gone through several infection waves and mostly managed to successfully stop the exponential spread of SARS-CoV-2 through bundles of restrictive measures. Still, the danger of further waves of infections is omnipresent, and it is apparent that every containment policy must be carefully evaluated and possibly replaced by a different, less restrictive policy before it can be lifted. Tracing of contacts and consequential breaking of infection chains is a promising strategy to help contain the disease, although its precise impact on the epidemic is unknown. In this work, we aim to quantify the impact of tracing on the containment of the disease and investigate the dynamic effects involved. We developed an agent-based model that validly depicts the spread of the disease and allows for exploratory analysis of containment policies. We applied this model to quantify the impact of different approaches of contact tracing in Austria to derive general conclusions on contract tracing. The study displays that strict tracing complements other intervention strategies. For the containment of the disease, the number of secondary infections must be reduced by about 75%. Implementing the proposed tracing strategy supplements measures worth about 5%. Evaluation of the number of preventively quarantined persons shows that household quarantine is the most effective in terms of avoided cases per quarantined person. The results are limited by the validity of the modeling assumptions, model parameter estimates, and the quality of the parametrization data. The study shows that tracing is indeed an efficient measure to keep case numbers low but comes at a high price if the disease is not well contained. Therefore, contact tracing must be executed strictly, and adherence within the population must be held up to prevent uncontrolled outbreaks of the disease.