Statistics in Medicine最新文献

A Practical Framework to Design Immunization Studies Based on the Beta Distribution. 基于Beta分布设计免疫研究的实用框架。

IF 1.8 4区医学

Statistics in Medicine Pub Date : 2025-10-01 DOI: 10.1002/sim.70293

Stefan Embacher, Andrea Berghold, Kirsten Maertens, Sereina A Herzog

{"title":"A Practical Framework to Design Immunization Studies Based on the Beta Distribution.","authors":"Stefan Embacher, Andrea Berghold, Kirsten Maertens, Sereina A Herzog","doi":"10.1002/sim.70293","DOIUrl":"10.1002/sim.70293","url":null,"abstract":"An optimally designed experiment reaches results quicker, at a lower cost, or with fewer observations and is therefore crucial in maximizing resource efficiency in research. In immunization studies, the primary goal is often to characterize antibody kinetics-the change in antibody concentration over time. However, nonlinear models for antibody kinetics present substantial challenges for study design, particularly the need to provide information on the parameters of interest. We propose a novel framework to facilitate the design of immunization studies using simple, understandable information. We assume that the mean antibody concentration follows the structural form of the beta density until reaching a plateau. Using the time and height of the maximum and the time and height of the plateau, we can uniquely determine the antibody kinetics curve. Optimal sampling schedules are determined using D-optimality, with D-efficiency used to compare designs. In a robustness analysis across 12 scenarios, we analyzed the framework's sensitivity to misspecification in the initial information. When misspecifying one parameter at a time, the median D-efficiencies exceeded 0.95 and the first quartiles were greater than or equal to 0.9 for all parameters, highlighting the robustness of the framework. Misspecification in the height of the plateau and time of the maximum affected the D-efficiency the most. The great advantage of the framework is that we only need intuitive information from the medical professionals to design an immunization study, in which determining the antibody kinetics is the main goal.","PeriodicalId":21879,"journal":{"name":"Statistics in Medicine","volume":"44 23-24","pages":"e70293"},"PeriodicalIF":1.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12503089/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145239671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive Biomarker-Based Design for Early Phase Clinical Trials. 基于适应性生物标志物的早期临床试验设计。

IF 1.8 4区医学

Statistics in Medicine Pub Date : 2025-10-01 DOI: 10.1002/sim.70275

Alessandra Serra, Gaëlle Saint-Hilary, Sandrine Guilleminot, Julia Geronimi, Pavel Mozgunov

{"title":"Adaptive Biomarker-Based Design for Early Phase Clinical Trials.","authors":"Alessandra Serra, Gaëlle Saint-Hilary, Sandrine Guilleminot, Julia Geronimi, Pavel Mozgunov","doi":"10.1002/sim.70275","DOIUrl":"10.1002/sim.70275","url":null,"abstract":"Identifying and quantifying predictive biomarkers is a critical issue of Precision Medicine approaches and patient-centric clinical development strategies. Early phase adaptive designs can improve trial efficiency by allowing for adaptations during the course of the trial. In this work, we are interested in adaptations based on interim analysis permitting a refinement of the existing study population according to their predictive biomarkers. At an early stage, the goal is not to precisely define the target population, but to not miss an efficacy signal that might be limited to a biomarker subgroup. In this work, we propose a one-arm two-stage early phase biomarker-guided design in the setting of an oncology trial where at the time of the interim analysis, several decisions can be made regarding stopping the entire trial early or continuing to recruit patients from the full or a selected patient population. Via simulations, we show that, although the sample size is limited, the proposed design leads to better decision-making compared to a classical design that does not consider an enrichment expansion.","PeriodicalId":21879,"journal":{"name":"Statistics in Medicine","volume":"44 23-24","pages":"e70275"},"PeriodicalIF":1.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12510287/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145252760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Rethinking the Handling of Method Failure in Comparison Studies. 对比较研究中方法失败处理的再思考。

IF 1.8 4区医学

Statistics in Medicine Pub Date : 2025-10-01 DOI: 10.1002/sim.70257

Milena Wünsch, Moritz Herrmann, Elisa Noltenius, Mattia Mohr, Tim P Morris, Anne-Laure Boulesteix

{"title":"Rethinking the Handling of Method Failure in Comparison Studies.","authors":"Milena Wünsch, Moritz Herrmann, Elisa Noltenius, Mattia Mohr, Tim P Morris, Anne-Laure Boulesteix","doi":"10.1002/sim.70257","DOIUrl":"10.1002/sim.70257","url":null,"abstract":"Comparison studies in methodological research are intended to compare methods in an evidence-based manner to help data analysts select a suitable method for their application. To provide trustworthy evidence, they must be carefully designed, implemented, and reported, especially given the many decisions made in planning and running. A common challenge in comparison studies is to handle the \"failure\" of one or more methods to produce a result for some (real or simulated) data sets, such that their performances cannot be measured in those instances. Despite an increasing emphasis on this topic in recent literature (focusing on non-convergence as a common manifestation), there is little guidance on proper handling and interpretation, and reporting of the chosen approach is often neglected. This paper aims to fill this gap and offers practical guidance on handling method failure in comparison studies. After exploring common handlings across various published comparison studies from classical statistics and predictive modeling, we show that the popular approaches of discarding data sets yielding failure (either for all or the failing methods only) and imputing are inappropriate in most cases. We then recommend a different perspective on method failure-viewing it as the result of a complex interplay of several factors rather than just its manifestation. Building on this, we provide recommendations on more adequate handling of method failure derived from realistic considerations. In particular, we propose considering fallback strategies that directly reflect the behavior of real-world users. Finally, we illustrate our recommendations and the dangers of inadequate handling of method failure through two exemplary comparison studies.","PeriodicalId":21879,"journal":{"name":"Statistics in Medicine","volume":"44 23-24","pages":"e70257"},"PeriodicalIF":1.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12509789/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145252786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Difference-in-Differences for Health Policy and Practice: A Review of Modern Methods. 卫生政策和实践的差异：现代方法的回顾。

IF 1.8 4区医学

Statistics in Medicine Pub Date : 2025-10-01 DOI: 10.1002/sim.70247

Shuo Feng, Ishani Ganguli, Youjin Lee, John Poe, Andrew Ryan, Alyssa Bilinski

{"title":"Difference-in-Differences for Health Policy and Practice: A Review of Modern Methods.","authors":"Shuo Feng, Ishani Ganguli, Youjin Lee, John Poe, Andrew Ryan, Alyssa Bilinski","doi":"10.1002/sim.70247","DOIUrl":"https://doi.org/10.1002/sim.70247","url":null,"abstract":"Difference-in-differences (DiD) is a popular observational causal inference method in health policy, employed to evaluate the real-world impact of policies and programs. To estimate treatment effects, DiD relies on a \"parallel trends assumption\" that treatment and comparison groups would have had parallel trajectories on average in the absence of an intervention. Recent years have seen both growing use of DiD in health policy and medicine and rapid advancements in DiD methods. To support DiD implementation in these fields, this paper reviews and synthesizes best practices and recent innovations. We provide recommendations to practitioners in four areas: (1) assessing causal assumptions; (2) adjusting for covariates and other approaches to relax causal assumptions; (3) accounting for staggered treatment timing; and (4) conducting robust inference, especially when normal-based clustered standard errors are inappropriate. For each, we explain challenges and common pitfalls in traditional DiD and recommend methods to address these. We explore current treatment of these topics through a focused literature review of medical DiD studies.","PeriodicalId":21879,"journal":{"name":"Statistics in Medicine","volume":"44 23-24","pages":"e70247"},"PeriodicalIF":1.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145239815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Corrected Score Approach for Proportional Hazards Model With Error-Contaminated Covariates Subject to Detection Limits. 误差污染协变量受检出限影响的比例风险模型的修正分数法。

IF 1.8 4区医学

Statistics in Medicine Pub Date : 2025-10-01 DOI: 10.1002/sim.70243

Xiao Song, Ching-Yun Wang

引用次数: 0

A New Test for Assessing the Covariate Effect in ROC Curves. 评估ROC曲线协变量效应的新检验。

IF 1.8 4区医学

Statistics in Medicine Pub Date : 2025-10-01 DOI: 10.1002/sim.70284

Arís Fanjul-Hevia, Juan Carlos Pardo-Fernández, Wenceslao González-Manteiga

引用次数: 0

A Noise-Tolerant Inference Procedure for Quasi-Monte Carlo Likelihood Estimation of a Joint Model for Multiple Longitudinal Markers and Competing Risks. 多纵向标记和竞争风险联合模型准蒙特卡罗似然估计的耐噪声推理方法。

IF 1.8 4区医学

Statistics in Medicine Pub Date : 2025-10-01 DOI: 10.1002/sim.70298

L Chabeau, P Rinder, S Desmée, M Giral, E Dantan

{"title":"A Noise-Tolerant Inference Procedure for Quasi-Monte Carlo Likelihood Estimation of a Joint Model for Multiple Longitudinal Markers and Competing Risks.","authors":"L Chabeau, P Rinder, S Desmée, M Giral, E Dantan","doi":"10.1002/sim.70298","DOIUrl":"https://doi.org/10.1002/sim.70298","url":null,"abstract":"Despite increasingly widespread use, complex joint models for longitudinal and survival data can be difficult to estimate. Notably, this could be due to the computation of the intractable integral over random effects involved in the likelihood and whose dimensionality increases with the number of shared random effects. In this article, we propose approximating the integral over random effects through a Quasi-Monte Carlo (QMC) approach combined with a noise-tolerant Quasi-Newton algorithm to consider the likelihood randomness induced by the QMC framework. From a simulation study, we demonstrate the suitability of the noise-tolerant Quasi-Newton algorithm to estimate the parameters of a shared random-effect joint model for two longitudinal markers in the presence of two competing events. The noise-tolerant Quasi-Newton algorithm is also compared with a Quasi-Newton algorithm with common draws in the QMC approach that showed good performance. Finally, we illustrate the interest of the noise-tolerant Quasi-Newton algorithm on kidney transplantation data. We jointly modeled the evolution of serum creatinine and donor-specific antibody immunization, as well as their associations with the cause-specific risks of graft failure and death with a functioning graft, using data from the French prospective and observational DIVAT cohort of kidney transplant recipients. The proposed noise-tolerant inference procedure for QMC likelihood estimation is shown to be relevant for estimating a joint model with multiple longitudinal markers and competing risks.","PeriodicalId":21879,"journal":{"name":"Statistics in Medicine","volume":"44 23-24","pages":"e70298"},"PeriodicalIF":1.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145275829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Covariate Balancing With Measurement Error. 带有测量误差的协变量平衡。

IF 1.8 4区医学

Statistics in Medicine Pub Date : 2025-10-01 DOI: 10.1002/sim.70300

Xialing Wen, Ying Yan

引用次数: 0

Doubly Robust Estimators for Heterogeneous Treatment Effects in Heteroskedastic Survival Data. 异方差生存数据中异质治疗效果的双稳健估计。

IF 1.8 4区医学

Statistics in Medicine Pub Date : 2025-10-01 DOI: 10.1002/sim.70301

Yuhui Yang, Weiwei Hu, Zhenli Liao, Fangyao Chen

{"title":"Doubly Robust Estimators for Heterogeneous Treatment Effects in Heteroskedastic Survival Data.","authors":"Yuhui Yang, Weiwei Hu, Zhenli Liao, Fangyao Chen","doi":"10.1002/sim.70301","DOIUrl":"https://doi.org/10.1002/sim.70301","url":null,"abstract":"Given the increasing interest focus on personalized medicine, a number of advanced statistical methods have been developed for estimating heterogeneous treatment effects (HTEs). However, methods for estimating HTEs in medical applications are limited, as they often involve potentially censored and heteroskedastic survival outcomes. Ignoring censoring and heteroskedasticity may introduce bias into HTEs. Therefore, in this study, we proposed two doubly robust (DR) methods for estimating HTEs based on nonparametric failure time (NFT) Bayesian additive regression trees (BART). Our contributions are as follows: (1) by using NFT BART as the prediction model, we avoid many restrictive assumptions, such as linearity, proportional hazards, and homoscedasticity; (2) we extend the DR-Learner to survival data, allowing it to handle the common issue of censoring and confounding in observational data; (3) we conduct a comprehensive simulation study of the present HTEs estimation strategies using several data generation processes in which we systematically vary the sample size of the training set, treatment-specific propensity score distribution, censoring rate, unbalanced treatment assignment, complexity of the model and bias function, and heteroskedastic or homoscedastic outcome. Through simulations, we demonstrate the effectiveness and robustness of the two proposed approaches in estimating HTEs. We also conduct a real data application of individualized hypertension management on observational data from the National Health and Nutrition Examination Survey (NHANES). Consequently, the proposed methods could yield robust estimates of HTE in observational survival data.","PeriodicalId":21879,"journal":{"name":"Statistics in Medicine","volume":"44 23-24","pages":"e70301"},"PeriodicalIF":1.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145281150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

What's the Weight? Estimating Controlled Outcome Differences in Complex Surveys for Health Disparities Research. 重量是多少？估计健康差异研究中复杂调查的受控结果差异。

IF 1.8 4区医学

Statistics in Medicine Pub Date : 2025-10-01 DOI: 10.1002/sim.70289

Stephen Salerno, Emily K Roberts, Belinda L Needham, Tyler H McCormick, Fan Li, Bhramar Mukherjee, Xu Shi

{"title":"What's the Weight? Estimating Controlled Outcome Differences in Complex Surveys for Health Disparities Research.","authors":"Stephen Salerno, Emily K Roberts, Belinda L Needham, Tyler H McCormick, Fan Li, Bhramar Mukherjee, Xu Shi","doi":"10.1002/sim.70289","DOIUrl":"https://doi.org/10.1002/sim.70289","url":null,"abstract":"In this work, we are motivated by the problem of estimating racial disparities in health outcomes, specifically the average controlled difference (ACD) in telomere length between Black and White individuals, using data from the National Health and Nutrition Examination Survey (NHANES). To do so, we build a propensity for race to properly adjust for other social determinants while characterizing the controlled effect of race on telomere length. Propensity score methods are broadly employed with observational data as a tool to achieve covariate balance, but how to implement them in complex surveys is less studied-in particular, when the survey weights depend on the group variable under comparison (as the NHANES sampling scheme depends on self-reported race). We propose identification formulas to properly estimate the ACD in outcomes between Black and White individuals, with appropriate weighting for both covariate imbalance across the two racial groups and generalizability. Via extensive simulation, we show that our proposed methods outperform traditional analytic approaches in terms of bias, mean squared error, and coverage when estimating the ACD for our setting of interest. In our data, we find that evidence of racial differences in telomere length between Black and White individuals attenuates after accounting for confounding by socioeconomic factors and utilizing appropriate propensity score and survey weighting techniques. Software to implement these methods and code to reproduce our results can be found in the R package svycdiff, available through the Comprehensive R Archive Network (CRAN) at cran.r-project.org/web/packages/svycdiff/, or in a development version on GitHub at github.com/salernos/svycdiff.","PeriodicalId":21879,"journal":{"name":"Statistics in Medicine","volume":"44 23-24","pages":"e70289"},"PeriodicalIF":1.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145239759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0