Epidemiology最新文献

{"title":"Rates of Receiving Medication for Opioid Use Disorder and Opioid Overdose Deaths During the Early Synthetic Opioid Crisis: A County-level Analysis.","authors":"Julian Santaella-Tenorio, Ariadne Rivera-Aguirre, Staci A Hepler, David M Kline, Jonathan Cantor, Maria DeYoreo, Silvia S Martins, Noa Krawczyk, Magdalena Cerda","doi":"10.1097/EDE.0000000000001816","DOIUrl":"10.1097/EDE.0000000000001816","url":null,"abstract":"<p><strong>Background: </strong>Medications for opioid use disorder are associated with a lower risk of drug overdoses at the individual level. However, little is known about whether these effects translate to population-level reductions. We investigated whether county-level efforts to increase access to medication for opioid use disorder in 2012-2014 were associated with opioid overdose deaths in New York State during the first years of the synthetic opioid crisis.</p><p><strong>Methods: </strong>We performed an ecologic county-level study including data from 60 counties (2010-2018). We calculated rates of people receiving medication for opioid use disorder among the population misusing opioids in 2012-2014 and categorized counties into quartiles of this exposure. We modeled synthetic and nonsynthetic opioid overdose death rates using Bayesian hierarchical models.</p><p><strong>Results: </strong>Counties with higher rates of receiving medications for opioid use disorder in 2012-2014 had lower synthetic opioid overdose deaths in 2016 (highest vs. lowest quartile: rate ratio [RR] = 0.33, 95% credible interval [CrI] = 0.12, 0.98; and second-highest vs. lowest: RR = 0.20, 95% CrI = 0.07, 0.59) and 2017 (quartile second-highest vs. lowest: RR = 0.22, 95% CrI = 0.06, 0.83), but not 2018. There were no differences in nonsynthetic opioid overdose death rates comparing higher quartiles versus lowest quartile of exposure.</p><p><strong>Conclusions: </strong>A spatio-temporal modeling approach incorporating counts of the population misusing opioids provided information about trends and interventions in the target population. Higher rates of receiving medications for opioid use disorder in 2012-2014 were associated with lower rates of synthetic opioid overdose deaths early in the crisis.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"186-195"},"PeriodicalIF":4.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11785500/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142946620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Parameterization of Beta Distributions for Bias Parameters of Binary Exposure Misclassification in Probabilistic Bias Analysis.","authors":"Qi Zhang, Richard F MacLehose, Lindsay J Collin, Thomas P Ahern, Timothy L Lash","doi":"10.1097/EDE.0000000000001818","DOIUrl":"10.1097/EDE.0000000000001818","url":null,"abstract":"<p><strong>Background: </strong>To account for misclassification of dichotomous variables using probabilistic bias analysis, beta distributions are often assigned to bias parameters (e.g., positive and negative predictive values) based on data from an internal validation substudy. Due to the small sample size of validation substudies, zero-cell frequencies can occur. In these scenarios, it may be helpful to assign prior distributions or apply continuity corrections to the predictive value estimates.</p><p><strong>Methods: </strong>We simulated cohort studies of varying sizes, with a binary exposure and outcome and a true risk ratio (RR) = 2.0, as well as internal validation substudies, to account for exposure misclassification. We conducted bias adjustment under five approaches assigning prior distributions to the positive and negative predictive value parameters: (1) conventional method (i.e., no prior), (2) uniform prior beta ( α = 1, β = 1), (3) Jeffreys prior beta ( α = 0.5, β = 0.5), (4) using Jeffreys prior as a continuity correction only when zero cells occurred, and (5) using the uniform prior as a continuity correction only when zero cells occurred. We evaluated performance by measuring coverage probability, bias, and mean squared error.</p><p><strong>Results: </strong>For sparse validation data, methods (2)-(5) all had better coverage and lower mean squared error than the conventional method, with the uniform prior (2) yielding the best performance. However, little difference between methods was observed when the validation substudy did not contain zero cells.</p><p><strong>Conclusion: </strong>If sparse data are expected in a validation substudy, using a uniform prior for the beta distribution of bias parameters can improve the validity of bias-adjusted measures.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"237-244"},"PeriodicalIF":4.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11785477/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142715610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Body Shapes of Multiple Anthropometric Traits and All-cause and Cause-specific Mortality in the UK Biobank.","authors":"Patricia Bohmann, Michael J Stein, Andrea Weber, Julian Konzok, Emma Fontvieille, Laia Peruchet-Noray, Quan Gan, Béatrice Fervers, Vivian Viallon, Hansjörg Baurecht, Michael F Leitzmann, Heinz Freisling, Anja M Sedlmeier","doi":"10.1097/EDE.0000000000001810","DOIUrl":"10.1097/EDE.0000000000001810","url":null,"abstract":"<p><strong>Background: </strong>Individual traditional anthropometric measures such as body mass index and waist circumference may not fully capture the relation of adiposity to mortality. Investigating multitrait body shapes could overcome this limitation, deepening insights into adiposity and mortality.</p><p><strong>Methods: </strong>Using UK Biobank data from 462,301 adults (40-69 years at baseline: 2006-2010), we derived four body shapes from principal component analysis on body mass index, height, weight, waist and hip circumference, and waist-to-hip ratio. We then used multivariable-adjusted Cox proportional hazard models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between body shapes and mortality for principal component scores of +1 and -1.</p><p><strong>Results: </strong>During 6,114,399 person-years of follow-up, 28,807 deaths occurred. A generally obese body shape exhibited a U-shaped mortality association. A tall and centrally obese body shape showed increased mortality risk in a dose-response manner (comparing a score of +1 and 0: HR = 1.16, 95% CI = 1.14, 1.18). Conversely, tall and lean or athletic body shapes displayed no increased mortality risks when comparing a score of +1 and 0, with positive relations for the comparison between a score of -1 and 0 in these shapes (short and stout shape: HR = 1.12, 95% CI = 1.10, 1.14; nonathletic shape: HR = 1.15, 95% CI = 1.13, 1.17).</p><p><strong>Conclusion: </strong>Four distinct body shapes, reflecting heterogeneous expressions of obesity, were differentially associated with all-cause and cause-specific mortality. Multitrait body shapes may refine our insights into the associations between different adiposity subtypes and mortality.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":"36 2","pages":"264-274"},"PeriodicalIF":4.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143064636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Do Early Weight Trajectories Explain Social Inequalities in Lung Function in Children With Cystic Fibrosis?: A Longitudinal Interventional Disparity Effects Analysis With Time-varying Mediators and Intermediate Confounders.","authors":"Daniela K Schlüter, Ruth H Keogh, Rhian M Daniel, Schadrac C Agbla, David Taylor-Robinson","doi":"10.1097/EDE.0000000000001826","DOIUrl":"10.1097/EDE.0000000000001826","url":null,"abstract":"<p><strong>Background: </strong>Children with cystic fibrosis (CF) from socioeconomically deprived areas have poorer growth, worse lung function, and shorter life expectancy than their less-deprived peers. While early growth is associated with lung function around age 6, it is unclear whether improving early growth in the most deprived children reduces inequalities in lung function.</p><p><strong>Methods: </strong>We used data from the UK CF Registry, tracking children born 2000-2010 up to 2016. We extended the interventional disparity effects approach to the setting of a longitudinally measured mediator. Applying this approach, we estimated the association between socioeconomic deprivation (children in the least vs. most deprived population quintile; exposure) and lung function at first measurement (ages 6-8, outcome), and the role of early weight trajectories (ages 0-6) as mediators of this relationship. We adjusted for baseline confounding by sex, birthyear, and genotype and time-varying intermediate confounding by lung infection.</p><p><strong>Results: </strong>The study included 853 children, with 165 children from the least and 172 from the most deprived quintiles. The average lung function difference between the least and most deprived quintiles was 4.5% of predicted forced expiratory volume in 1 second (95% confidence interval: 1.1-7.9). If the distribution of early weight trajectories in the most deprived children matched that in the least deprived children, this difference would reduce to 4% (95% confidence interval: 0.57- 7.4).</p><p><strong>Conclusion: </strong>Socioeconomic deprivation has a strong negative association with lung function for children with CF. We estimate that improving early weight trajectories in the most deprived children would only marginally reduce these inequalities.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"275-285"},"PeriodicalIF":4.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11774196/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142930962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interactive Effects of Long-term Exposure to Air Pollutants on SARS-CoV-2 Infection and Severity: A Northern Italian Population-based Cohort Study.","authors":"Giovanni Veronesi, Sara De Matteis, Camillo Silibello, Emanuele M Giusti, Walter Ageno, Marco M Ferrario","doi":"10.1097/EDE.0000000000001792","DOIUrl":"10.1097/EDE.0000000000001792","url":null,"abstract":"<p><strong>Background: </strong>We examined interactions, to our knowledge not yet explored, between long-term exposures to particulate matter (PM 10 ) with nitrogen dioxide (NO 2 ) and ozone (O 3 ) on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectivity and severity.</p><p><strong>Methods: </strong>We followed 709,864 adult residents of Varese Province from 1 February 2020 until the first positive test, COVID-19 hospitalization, or death, up to 31 December 2020. We estimated residential annual means of PM 10 , NO 2 , and O 3 in 2019 from chemical transport and random-forest models. We estimated the interactive effects of pollutants with urbanicity on SARS-CoV-2 infectivity, hospitalization, and mortality endpoints using Cox regression models adjusted for socio-demographic factors and comorbidities, and additional cases due to interactions using Poisson models.</p><p><strong>Results: </strong>In total 41,065 individuals were infected, 5203 were hospitalized and 1543 died from COVID-19 during follow-up. Mean PM 10 was 1.6 times higher and NO 2 2.6 times higher than WHO limits, with wide gradients between urban and nonurban areas. PM 10 and NO 2 were positively associated with SARS-CoV-2 infectivity and mortality, and PM 10 with hospitalizations in urban areas. Interaction analyses estimated that the effect of PM 10 (per 3.5 µg/m 3 ) on infectivity was strongest in urban areas [hazard ratio (HR) = 1.12; 95% CI =1.09, 1.16], corresponding to 854 additional cases per 100,000 person-years, and in areas at high NO 2 co-exposure (HR = 1.15; 1.08, 1.22). At higher levels of PM 10 co-exposure, the protective association of O 3 reversed (HR =1.32, 1.17, 1.49), yielding 278 additional cases per µg/m 3 increase in O 3 . We estimated similar interactive effects for severity endpoints.</p><p><strong>Conclusions: </strong>We estimate that interactive effects between pollutants exacerbated the burden of the SARS-CoV-2 pandemic in urban areas.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"11-19"},"PeriodicalIF":4.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11594552/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142343942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geospatial Data Aggregation Methods for Novel Geographies: Validating Congressional District Life Expectancy Estimates.","authors":"Alina Schnake-Mahl, Giancarlo Anfuso, Stephanie M Hernandez, Usama Bilal","doi":"10.1097/EDE.0000000000001797","DOIUrl":"10.1097/EDE.0000000000001797","url":null,"abstract":"<p><strong>Background: </strong>Place is a critical determinant of health. Recent novel analyses have explored health outcome estimation for small geographies, such as census tracts, as well as health outcome aggregation to geopolitical geographies with accountable political representatives, such as congressional districts. In one such application, combining these approaches, researchers aggregated census tract estimates of life expectancy at the congressional district level to derive local estimates, but such an approach has not been validated.</p><p><strong>Methods: </strong>Here, we compared two sources and approaches to calculating life expectancy data for Pennsylvania congressional districts. We used 2010-2015 census tract life expectancy estimates from the US Small-area Life Expectancy Estimates Project and dasymetric methods to compute population-weighted life expectancy aggregated to the congressional district level. Using georeferenced Vital Statistics data, we aggregated age-specific census tract death and population counts to congressional districts and used abridged life tables to estimate life expectancy. To validate the dasymetric aggregated estimates we compared absolute differences, assessed the correlation, and created Bland-Altman plots to visualize the agreement between the two measures.</p><p><strong>Results: </strong>We found strong agreement between congressional district estimates of life expectancy at birth derived using the dasymetric Life Expectancy Estimates Project model-based approach and the Vital Statistics direct estimates approach, though life expectancy at older ages (75 years and older) showed weak correlations.</p><p><strong>Conclusions: </strong>This validation contributes to our understanding of geospatial aggregation methods for novel geographies including congressional districts. Health outcome data aggregated to the congressional district geography can support congressional policymaking aimed at improving population health outcomes.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"119-125"},"PeriodicalIF":4.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11822868/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142343941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multilevel Resilience and Appointment Attendance Among African American/Black Adults with HIV: A Prospective Multisite Cohort Study.","authors":"Marta G Wilson-Barthes, Jee Won Park, Michael J Mugavero, Sonia Napravnik, Michael P Carey, Joseph L Fava, Sannisha K Dale, Valerie A Earnshaw, Deana Agil, Chanelle J Howe, Akilah J Dulin","doi":"10.1097/EDE.0000000000001801","DOIUrl":"10.1097/EDE.0000000000001801","url":null,"abstract":"<p><strong>Background: </strong>Attending clinic appointments supports HIV viral suppression, yet racial disparities are documented. We assessed whether multilevel resilience resources were associated with appointment attendance among African American/Black (AA/B) adults living with HIV in the United States.</p><p><strong>Methods: </strong>We ascertained data from 291 AA/B clinical cohort participants from 2018 to 2021. We assessed resilience using the Multilevel Resilience Resource Measure. Binary outcomes were a nonrepeated indicator of attending ≥87.5% of scheduled HIV appointments over 12 months (i.e., visit adherence) and a repeated measure of attending appointments during two sequential 6-month follow-up windows (i.e., clinic attendance). Modified Poisson models estimated adjusted risk ratios (aRRs).</p><p><strong>Results: </strong>The aRR for clinic attendance among participants with greater versus lesser multilevel resilience resource endorsement was 0.95 (95% confidence interval: 0.88, 1.0). The aRR for visit adherence among participants with greater versus lesser multilevel resilience resource endorsement was 1.2 (0.95, 1.4).</p><p><strong>Conclusions: </strong>This analysis is one of the first to assess appointment attendance as a function of resilience. Findings should be confirmed in larger cohorts.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":"36 1","pages":"99-106"},"PeriodicalIF":4.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11599769/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142715627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Potential of a Second Screening Test for Alloimmunization in Pregnancies of Rhesus-positive Women: A Swedish Population-based Cohort Study.","authors":"Nishan Lamichhane, Shengxin Liu, Agneta Wikman, Marie Reilly","doi":"10.1097/EDE.0000000000001794","DOIUrl":"10.1097/EDE.0000000000001794","url":null,"abstract":"<p><strong>Introduction: </strong>There is lack of consensus regarding whether a second screening in rhesus-positive pregnant women is worthwhile, with different guidelines, recommendations, and practices. We aimed to estimate the number and timing of missed alloimmunizations in rhesus-positive pregnancies screened once and weigh the relative burden of additional screening and monitoring versus the estimated reduction in adverse pregnancy outcomes.</p><p><strong>Methods: </strong>We extracted information on maternal, pregnancy, and screening results for 682,126 pregnancies for 2003-2012 from Swedish national registers. We used data from counties with a routine second screening to develop and validate a logistic model for a positive second test after an earlier negative. We used this model to predict the number of missed alloimmunizations in counties offering only one screening. Interval-censored survival analysis identified an optimal time window for a second test. We compared the burden of additional screening with estimated adverse pregnancy outcomes avoided.</p><p><strong>Results: </strong>The model provided an accurate estimate of positive tests at the second screening. For counties with the lowest screening rates, we estimated that a second screening would increase the alloimmunization prevalence by 33% (from 0.19% to 0.25%), detecting the 25% (304/1222) of cases that are currently missed. The suggested timing of a second screen was gestational week 28. For pregnancies currently screened once, the estimated cost of a second test followed by maternal monitoring was approximately 10% of the cost incurred by the excess adverse pregnancy outcomes.</p><p><strong>Conclusion: </strong>Investment in routine second screening can identify many alloimmunizations that currently go undetected or are detected late, with the potential for cost savings.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"40-47"},"PeriodicalIF":4.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142343964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Structural Description of Biases That Generate Immortal Time.","authors":"Miguel A Hernán, Jonathan A C Sterne, Julian P T Higgins, Ian Shrier, Sonia Hernández-Díaz","doi":"10.1097/EDE.0000000000001808","DOIUrl":"10.1097/EDE.0000000000001808","url":null,"abstract":"<p><p>Immortal time may arise in survival analyses when individuals are assigned to treatment strategies based on post-eligibility information or selected based on post-assignment eligibility criteria. Selection based on eligibility criteria applied after treatment assignment results in immortal time when the analysis starts the follow-up at assignment. Misclassification of assignment to treatment strategies based on treatment received after eligibility results in immortal time when the treatment strategies are not distinguishable at the start of follow-up. Target trial emulation prevents the introduction of immortal time by explicitly specifying eligibility and assignment to the treatment strategies, and by synchronizing them at the start of follow-up. We summarize analytic approaches that prevent immortal time when longitudinal data are available to emulate the target trial from the time of treatment assignment. The term \"immortal time bias\" suggests that the source of the bias is the immortal time, but it is selection or misclassification that generates the immortal time, leading to bias.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"107-114"},"PeriodicalIF":4.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11598638/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142567283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using Limited Trial Evidence to Credibly Choose Treatment Dosage when Efficacy and Adverse Effects Weakly Increase with Dose.","authors":"Charles F Manski","doi":"10.1097/EDE.0000000000001793","DOIUrl":"10.1097/EDE.0000000000001793","url":null,"abstract":"<p><p>It has become standard in medical treatment to base dosage on evidence in randomized trials. Yet it has been rare to study how outcomes vary with dosage. In trials to obtain drug approval, the norm has been to compare some dose of a new drug with an established therapy or placebo. Standard trial analysis views each trial arm as qualitatively different, but it may be credible to assume that efficacy and adverse effects weakly increase with dosage. Optimization of patient care requires joint attention to both, as well as to treatment cost. This article develops a methodology to use limited trial evidence to choose dosage when efficacy and adverse effects weakly increase with dose. I suppose that dosage is an integer t ∊ (0,1,..., T ), T being a specified maximum dose. I study dosage choice when trial evidence on outcomes is available for only K dose levels, where K < T + 1. Then the population distribution of dose response is partially identified. I show that the identification region is a convex polygon. I characterize clinical and population decision-making using the minimax regret criterion. A simple analytical solution exists when T = 2. Computation is tractable when T is larger.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"60-65"},"PeriodicalIF":4.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142343967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}