Peter Mueller is a Research Scientist at the MGH Institute for Technology Assessment. He joined the ITA as a post-doctoral research fellow in 2017. He received his PhD and MA in Mathematics from the University of Wisconsin-Madison, and a BS in Math from the University of Minnesota-Twin Cities. Peter’s focus in graduate school was applied math and fluid dynamics, more specifically, biomixing (with a focus on the mixing caused by algae at the microscopic level). He began his schooling as a Chemistry major with the intent of going to medical school but ended up focusing on his talents for math and problem-solving. Peter was eventually called back to medicine through medical research presentations at fluid dynamics conferences. His favorite research areas include optimization and mathematical modeling. Aside from research, Peter also enjoys teaching and especially tutoring.
Peter is currently working with Dr. Pari Pandharipande and Dr. Jagpreet Chhatwal.
Selected Publications
Mueller, Peter P.; Chen, Qiushi; Ayer, Turgay; Nemutlu, Gizem; Hajjar, Ali; Bethea, Emily D.; Peters, Mary Linton B.; Lee, Brian P.; Janjua, Naveed Z.; Kanwal, Fasiha; Chhatwal, Jagpreet
Duration and cost-effectiveness of hepatocellular carcinoma surveillance in hepatitis C patients after viral eradication. Journal Article
In: Journal of hepatology, vol. 77, iss. 1, pp. 55-62, 2022, ISSN: 1600-0641.
@article{Mueller2022,
title = {Duration and cost-effectiveness of hepatocellular carcinoma surveillance in hepatitis C patients after viral eradication.},
author = {Peter P. Mueller and Qiushi Chen and Turgay Ayer and Gizem Nemutlu and Ali Hajjar and Emily D. Bethea and Mary Linton B. Peters and Brian P. Lee and Naveed Z. Janjua and Fasiha Kanwal and Jagpreet Chhatwal},
url = {https://pubmed.ncbi.nlm.nih.gov/35157959/},
doi = {10.1016/j.jhep.2022.01.027},
issn = {1600-0641},
year = {2022},
date = {2022-07-01},
urldate = {2022-02-01},
journal = {Journal of hepatology},
volume = {77},
issue = {1},
pages = {55-62},
abstract = {Successful treatment of chronic hepatitis C with oral direct-acting antiviral (DAA) leads to virological cure, however, the subsequent risk of hepatocellular carcinoma (HCC) persists. Our objective was to evaluate the cost-effectiveness of biannual surveillance for HCC in patients cured of hepatitis C and the optimal age to stop surveillance. We developed a microsimulation model of the natural history of HCC in hepatitis C individuals with advanced fibrosis or cirrhosis who achieved virological cure with oral DAAs. We used published data on HCC incidence, tumor progression, real-world HCC surveillance adherence, and costs and utilities of different health states. We compared biannual HCC surveillance using ultrasound and alpha-fetoprotein for varying durations of surveillance (from 5 years to lifetime) versus no surveillance. In virologically-cured patients with cirrhosis, the ICER of biannual surveillance remained below $150,000 per additional quality-adjusted life year (QALY) (range: $79,500-$94,800) when surveillance was stopped at age 70, irrespective of the start age (40-65). Compared with no surveillance, surveillance per 1000 cirrhosis patients detected 130 additional HCCs in 'very early'/early stage and yielded 51 additional QALYs. In virologically-cured patients with advanced fibrosis, the ICER of biannual surveillance remained below $150,000/QALY (range: $124,600-$129,800) when surveillance was stopped at age 60, irrespective of the start age (40-50). Compared with no surveillance, surveillance per 1000 advanced fibrosis patients detected 24 additional HCCs in 'very early'/early stage and yielded 12 additional QALYs. Biannual surveillance for HCC in virologically-cured hepatitis C patients is cost-effective until the age of 70 for cirrhosis patients, and until the age of 60 for patients with stable advanced fibrosis. Individuals who are cured of hepatitis C using oral antiviral drugs remain at risk of developing liver cancer. The value of lifelong screening for liver cancer in these individuals is not known. By simulating the life course of hepatitis C cured individuals, we found that ultrasound-based bi-annual screening for liver cancer is cost-effective up to age 70 in those having cirrhosis and up to age 60 in those having stable advanced fibrosis.},
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Successful treatment of chronic hepatitis C with oral direct-acting antiviral (DAA) leads to virological cure, however, the subsequent risk of hepatocellular carcinoma (HCC) persists. Our objective was to evaluate the cost-effectiveness of biannual surveillance for HCC in patients cured of hepatitis C and the optimal age to stop surveillance. We developed a microsimulation model of the natural history of HCC in hepatitis C individuals with advanced fibrosis or cirrhosis who achieved virological cure with oral DAAs. We used published data on HCC incidence, tumor progression, real-world HCC surveillance adherence, and costs and utilities of different health states. We compared biannual HCC surveillance using ultrasound and alpha-fetoprotein for varying durations of surveillance (from 5 years to lifetime) versus no surveillance. In virologically-cured patients with cirrhosis, the ICER of biannual surveillance remained below $150,000 per additional quality-adjusted life year (QALY) (range: $79,500-$94,800) when surveillance was stopped at age 70, irrespective of the start age (40-65). Compared with no surveillance, surveillance per 1000 cirrhosis patients detected 130 additional HCCs in 'very early'/early stage and yielded 51 additional QALYs. In virologically-cured patients with advanced fibrosis, the ICER of biannual surveillance remained below $150,000/QALY (range: $124,600-$129,800) when surveillance was stopped at age 60, irrespective of the start age (40-50). Compared with no surveillance, surveillance per 1000 advanced fibrosis patients detected 24 additional HCCs in 'very early'/early stage and yielded 12 additional QALYs. Biannual surveillance for HCC in virologically-cured hepatitis C patients is cost-effective until the age of 70 for cirrhosis patients, and until the age of 60 for patients with stable advanced fibrosis. Individuals who are cured of hepatitis C using oral antiviral drugs remain at risk of developing liver cancer. The value of lifelong screening for liver cancer in these individuals is not known. By simulating the life course of hepatitis C cured individuals, we found that ultrasound-based bi-annual screening for liver cancer is cost-effective up to age 70 in those having cirrhosis and up to age 60 in those having stable advanced fibrosis.
Keyes, Katherine M; Rutherford, Caroline; Hamilton, Ava; Barocas, Joshua A; Gelberg, Kitty H; Mueller, Peter P; Feaster, Daniel J; El-Bassel, Nabila; Cerdá, Magdalena
In: Drug Alcohol Depend Rep, vol. 3, 2022, ISSN: 2772-7246.
@article{pmid35783994,
title = {What is the prevalence of and trend in opioid use disorder in the United States from 2010 to 2019? Using multiplier approaches to estimate prevalence for an unknown population size},
author = {Katherine M Keyes and Caroline Rutherford and Ava Hamilton and Joshua A Barocas and Kitty H Gelberg and Peter P Mueller and Daniel J Feaster and Nabila El-Bassel and Magdalena Cerd\'{a}},
doi = {10.1016/j.dadr.2022.100052},
issn = {2772-7246},
year = {2022},
date = {2022-06-01},
journal = {Drug Alcohol Depend Rep},
volume = {3},
abstract = {Opioid-related overdose deaths have increased since 2010 in the U.S., but information on trends in opioid use disorder (OUD) prevalence is limited due to unreliable data. Multiplier methods are a classical epidemiological technique to estimate prevalence when direct estimation is infeasible or unreliable. We used two different multiplier approaches to estimate OUD prevalence from 2010 to 2019. First, we estimated OUD in National Survey on Drug Use and Health (NSDUH), and based on existing capture-recapture studies, multiplied prevalence by 4.5x. Second, we estimated the probability of drug poisoning death among people with OUD (Meta-analysis indicates 0.52/100,000), and divided the number of drug poisoning deaths in the US by this probability. Estimates were weighted to account for increase in drug-related mortality in recent years due to fentanyl. Estimated OUD prevalence was lowest when estimated in NSDUH with no multiplier, and highest when estimated from vital statistics data without adjustment. Consistent findings emerged with two methods: NSDUH data with multiplier correction, and vital statistics data with multiplier and adjustment. From these two methods, OUD prevalence increased from 2010 to 2014; then stabilized and slightly declined annually (survey data with multiplier, highest prevalence of 4.0% in 2015; death data with a multiplier and correction, highest prevalence of 2.35% in 2016). The number of US adolescent and adult individuals with OUD in 2019 was estimated between 6.7-7.6 million. When multipliers and corrections are used, OUD may have stabilized or slightly declined after 2015. Nevertheless, it remains highly prevalent, affecting 6-7 million US adolescents and adults.},
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Opioid-related overdose deaths have increased since 2010 in the U.S., but information on trends in opioid use disorder (OUD) prevalence is limited due to unreliable data. Multiplier methods are a classical epidemiological technique to estimate prevalence when direct estimation is infeasible or unreliable. We used two different multiplier approaches to estimate OUD prevalence from 2010 to 2019. First, we estimated OUD in National Survey on Drug Use and Health (NSDUH), and based on existing capture-recapture studies, multiplied prevalence by 4.5x. Second, we estimated the probability of drug poisoning death among people with OUD (Meta-analysis indicates 0.52/100,000), and divided the number of drug poisoning deaths in the US by this probability. Estimates were weighted to account for increase in drug-related mortality in recent years due to fentanyl. Estimated OUD prevalence was lowest when estimated in NSDUH with no multiplier, and highest when estimated from vital statistics data without adjustment. Consistent findings emerged with two methods: NSDUH data with multiplier correction, and vital statistics data with multiplier and adjustment. From these two methods, OUD prevalence increased from 2010 to 2014; then stabilized and slightly declined annually (survey data with multiplier, highest prevalence of 4.0% in 2015; death data with a multiplier and correction, highest prevalence of 2.35% in 2016). The number of US adolescent and adult individuals with OUD in 2019 was estimated between 6.7-7.6 million. When multipliers and corrections are used, OUD may have stabilized or slightly declined after 2015. Nevertheless, it remains highly prevalent, affecting 6-7 million US adolescents and adults.
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.
Linas, Benjamin P; Savinkina, Alexandra; Barbosa, Carolina; Mueller, Peter P.; Cerdá, Magdalena; Keyes, Katherine; Chhatwal, Jagpreet
A clash of epidemics: Impact of the COVID-19 pandemic response on opioid overdose. Journal Article
In: Journal of substance abuse treatment, vol. 120, pp. 108158, 2021, ISSN: 1873-6483, ().
@article{Linas2021,
title = {A clash of epidemics: Impact of the COVID-19 pandemic response on opioid overdose.},
author = {Benjamin P Linas and Alexandra Savinkina and Carolina Barbosa and Peter P. Mueller and Magdalena Cerd\'{a} and Katherine Keyes and Jagpreet Chhatwal},
url = {https://pubmed.ncbi.nlm.nih.gov/33298298/},
doi = {10.1016/j.jsat.2020.108158},
issn = {1873-6483},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Journal of substance abuse treatment},
volume = {120},
pages = {108158},
abstract = {Coronavirus disease 2019 (COVID-19) will have a lasting impact on public health. In addition to the direct effects of COVID-19 infection, physical distancing and quarantine interventions have indirect effects on health. While necessary, physical distancing interventions to control the spread of COVID-19 could have multiple impacts on people living with opioid use disorder, including impacts on mental health that lead to greater substance use, the availability of drug supply, the ways that people use drugs, treatment-seeking behaviors, and retention in care. The degree to which COVID-19 will impact the opioid epidemic and through which of the possible mechanisms that we discuss is important to monitor. We employed simulation modeling to demonstrate the potential impact of physical distancing on overdose mortality.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Coronavirus disease 2019 (COVID-19) will have a lasting impact on public health. In addition to the direct effects of COVID-19 infection, physical distancing and quarantine interventions have indirect effects on health. While necessary, physical distancing interventions to control the spread of COVID-19 could have multiple impacts on people living with opioid use disorder, including impacts on mental health that lead to greater substance use, the availability of drug supply, the ways that people use drugs, treatment-seeking behaviors, and retention in care. The degree to which COVID-19 will impact the opioid epidemic and through which of the possible mechanisms that we discuss is important to monitor. We employed simulation modeling to demonstrate the potential impact of physical distancing on overdose mortality.
Chen, Qiushi; Larochelle, Marc R.; Weaver, Davis; Lietz, Anna; Mueller, Peter P.; Mercaldo, Sarah Fletcher; Wakeman, Sarah E.; Freedberg, Kenneth A.; Raphel, Tiana; Knudsen, Amy; Pandharipande, Pari; Chhatwal, Jagpreet
Prevention of Prescription Opioid Misuse and Projected Overdose Deaths in the United States Journal Article
In: JAMA Network Open, vol. 2, no. 2, pp. e187621-e187621, 2019, ISSN: 2574-3805, ().
@article{10.1001/jamanetworkopen.2018.7621,
title = {Prevention of Prescription Opioid Misuse and Projected Overdose Deaths in the United States},
author = {Qiushi Chen and Marc R. Larochelle and Davis Weaver and Anna Lietz and Peter P. Mueller and Sarah Fletcher Mercaldo and Sarah E. Wakeman and Kenneth A. Freedberg and Tiana Raphel and Amy Knudsen and Pari Pandharipande and Jagpreet Chhatwal},
url = {https://dx.doi.org/10.1001/jamanetworkopen.2018.7621},
doi = {10.1001/jamanetworkopen.2018.7621},
issn = {2574-3805},
year = {2019},
date = {2019-02-01},
journal = {JAMA Network Open},
volume = {2},
number = {2},
pages = {e187621-e187621},
abstract = {Deaths due to opioid overdose have tripled in the last decade. Efforts to curb this trend have focused on restricting the prescription opioid supply; however, the near-term effects of such efforts are unknown.To project effects of interventions to lower prescription opioid misuse on opioid overdose deaths from 2016 to 2025.This system dynamics (mathematical) model of the US opioid epidemic projected outcomes of simulated individuals who engage in nonmedical prescription or illicit opioid use from 2016 to 2025. The analysis was performed in 2018 by retrospectively calibrating the model from 2002 to 2015 data from the National Survey on Drug Use and Health and the Centers for Disease Control and Prevention.Comparison of interventions that would lower the incidence of prescription opioid misuse from 2016 to 2025 based on historical trends (a 7.5% reduction per year) and 50% faster than historical trends (an 11.3% reduction per year), vs a circumstance in which the incidence of misuse remained constant after 2015.Opioid overdose deaths from prescription and illicit opioids from 2016 to 2025 under each intervention.Under the status quo, the annual number of opioid overdose deaths is projected to increase from 33 100 in 2015 to 81 700 (95% uncertainty interval [UI], 63 600-101 700) in 2025 (a 147% increase from 2015). From 2016 to 2025, 700 400 (95% UI, 590 200-817 100) individuals in the United States are projected to die from opioid overdose, with 80% of the deaths attributable to illicit opioids. The number of individuals using illicit opioids is projected to increase by 61%\textemdashfrom 0.93 million (95% UI, 0.83-1.03 million) in 2015 to 1.50 million (95% UI, 0.98-2.22 million) by 2025. Across all interventions tested, further lowering the incidence of prescription opioid misuse from 2015 levels is projected to decrease overdose deaths by only 3.0% to 5.3%.This study’s findings suggest that interventions targeting prescription opioid misuse such as prescription monitoring programs may have a modest effect, at best, on the number of opioid overdose deaths in the near future. Additional policy interventions are urgently needed to change the course of the epidemic.},
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pubstate = {published},
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Deaths due to opioid overdose have tripled in the last decade. Efforts to curb this trend have focused on restricting the prescription opioid supply; however, the near-term effects of such efforts are unknown.To project effects of interventions to lower prescription opioid misuse on opioid overdose deaths from 2016 to 2025.This system dynamics (mathematical) model of the US opioid epidemic projected outcomes of simulated individuals who engage in nonmedical prescription or illicit opioid use from 2016 to 2025. The analysis was performed in 2018 by retrospectively calibrating the model from 2002 to 2015 data from the National Survey on Drug Use and Health and the Centers for Disease Control and Prevention.Comparison of interventions that would lower the incidence of prescription opioid misuse from 2016 to 2025 based on historical trends (a 7.5% reduction per year) and 50% faster than historical trends (an 11.3% reduction per year), vs a circumstance in which the incidence of misuse remained constant after 2015.Opioid overdose deaths from prescription and illicit opioids from 2016 to 2025 under each intervention.Under the status quo, the annual number of opioid overdose deaths is projected to increase from 33 100 in 2015 to 81 700 (95% uncertainty interval [UI], 63 600-101 700) in 2025 (a 147% increase from 2015). From 2016 to 2025, 700 400 (95% UI, 590 200-817 100) individuals in the United States are projected to die from opioid overdose, with 80% of the deaths attributable to illicit opioids. The number of individuals using illicit opioids is projected to increase by 61%—from 0.93 million (95% UI, 0.83-1.03 million) in 2015 to 1.50 million (95% UI, 0.98-2.22 million) by 2025. Across all interventions tested, further lowering the incidence of prescription opioid misuse from 2015 levels is projected to decrease overdose deaths by only 3.0% to 5.3%.This study’s findings suggest that interventions targeting prescription opioid misuse such as prescription monitoring programs may have a modest effect, at best, on the number of opioid overdose deaths in the near future. Additional policy interventions are urgently needed to change the course of the epidemic.
Chhatwal, Jagpreet; Chen, Qiushi; Bethea, Emily; Ladd, Mary Ann; Mueller, Peter P.; Hutin, Yvan; Aggarwal, Rakesh
Hep C Calculator: an online tool for cost-effectiveness analysis of DAAs Journal Article
In: The Lancet Gastroenterology & Hepatology, vol. 3, no. 12, pp. 819, 2018, ISSN: 2468-1253.
@article{CHHATWAL2018819,
title = {Hep C Calculator: an online tool for cost-effectiveness analysis of DAAs},
author = {Jagpreet Chhatwal and Qiushi Chen and Emily Bethea and Mary Ann Ladd and Peter P. Mueller and Yvan Hutin and Rakesh Aggarwal},
url = {http://www.sciencedirect.com/science/article/pii/S2468125318302814},
doi = {https://doi.org/10.1016/S2468-1253(18)30281-4},
issn = {2468-1253},
year = {2018},
date = {2018-12-01},
urldate = {2018-12-01},
journal = {The Lancet Gastroenterology \& Hepatology},
volume = {3},
number = {12},
pages = {819},
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Peters, Mary Linton B.; Eckel, Andrew; Mueller, Peter P.; Tramontano, Angela; Weaver, Davis; Lietz, Anna; Hur, Chin; Kong, Chung Yin; Pandharipande, Pari
Progression to pancreatic ductal adenocarcinoma from pancreatic intraepithelial neoplasia: Results of a simulation model. Journal Article
In: Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.], vol. 18, no. 8, pp. 928-934, 2018, ISSN: 1424-3911.
@article{Peters2018,
title = {Progression to pancreatic ductal adenocarcinoma from pancreatic intraepithelial neoplasia: Results of a simulation model.},
author = {Mary Linton B. Peters and Andrew Eckel and Peter P. Mueller and Angela Tramontano and Davis Weaver and Anna Lietz and Chin Hur and Chung Yin Kong and Pari Pandharipande},
url = {https://www.ncbi.nlm.nih.gov/pubmed/30143405},
doi = {10.1016/j.pan.2018.07.009},
issn = {1424-3911},
year = {2018},
date = {2018-12-01},
urldate = {2018-12-01},
journal = {Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]},
volume = {18},
number = {8},
pages = {928-934},
abstract = {To gain insight into the natural history and carcinogenesis pathway of Pancreatic Intraepithelial Neoplasia (PanIN) lesions by building a calibrated simulation model of PanIN progression to pancreatic ductal adenocarcinoma (PDAC) METHODS: We revised a previously validated simulation model of solid PDAC, calibrating the model to fit data from the National Cancer Institute's Surveillance, Epidemiology, and End Results program and published literature on PanIN prevalence by age. We estimated the likelihood of progression from PanIN states (1, 2, and 3) to PDAC and the time between PanIN onset and PDAC (dwell time). We evaluated a hypothetical intervention to test for and treat PanIN 3 lesions to estimate the potential benefits from PanIN detection. We estimated the lifetime probability of progressing from PanIN 1 to PDAC to be 1.5% (men), 1.3% (women). Progression from PanIN 1 to PDAC took 33.6 years and 35.3 years, respectively, and from PanIN 3 to PDAC took 11.3 years and 12.3 years. A hypothetical test for PanIN 3 detection and treatment could provide a maximum, average life expectancy gain of 40 days. Our modeling analysis estimates PanINs have a relatively indolent course to PDAC, supporting the feasibility of potential future early detection strategies.},
keywords = {},
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To gain insight into the natural history and carcinogenesis pathway of Pancreatic Intraepithelial Neoplasia (PanIN) lesions by building a calibrated simulation model of PanIN progression to pancreatic ductal adenocarcinoma (PDAC) METHODS: We revised a previously validated simulation model of solid PDAC, calibrating the model to fit data from the National Cancer Institute's Surveillance, Epidemiology, and End Results program and published literature on PanIN prevalence by age. We estimated the likelihood of progression from PanIN states (1, 2, and 3) to PDAC and the time between PanIN onset and PDAC (dwell time). We evaluated a hypothetical intervention to test for and treat PanIN 3 lesions to estimate the potential benefits from PanIN detection. We estimated the lifetime probability of progressing from PanIN 1 to PDAC to be 1.5% (men), 1.3% (women). Progression from PanIN 1 to PDAC took 33.6 years and 35.3 years, respectively, and from PanIN 3 to PDAC took 11.3 years and 12.3 years. A hypothetical test for PanIN 3 detection and treatment could provide a maximum, average life expectancy gain of 40 days. Our modeling analysis estimates PanINs have a relatively indolent course to PDAC, supporting the feasibility of potential future early detection strategies.
Mueller, Peter P.; Thiffeault, Jean-Luc
Fluid transport and mixing by an unsteady microswimmer Journal Article
In: Phys. Rev. Fluids, vol. 2, pp. 013103, 2017, ().
@article{PhysRevFluids.2.013103,
title = {Fluid transport and mixing by an unsteady microswimmer},
author = {Peter P. Mueller and Jean-Luc Thiffeault},
url = {https://link.aps.org/doi/10.1103/PhysRevFluids.2.013103},
doi = {10.1103/PhysRevFluids.2.013103},
year = {2017},
date = {2017-01-01},
journal = {Phys. Rev. Fluids},
volume = {2},
pages = {013103},
publisher = {American Physical Society},
keywords = {},
pubstate = {published},
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}