Statistical Methods in Medical Research最新文献_第4页

Influence function-based empirical likelihood for area under the receiver operating characteristic curve in presence of covariates. 在协变量存在的情况下，基于影响函数的接收者工作特征曲线下面积的经验似然。

IF 1.9 3区医学

Statistical Methods in Medical Research Pub Date : 2025-08-01 Epub Date: 2025-05-29 DOI: 10.1177/09622802251345343

Baoying Yang, Xinjie Hu, Gengsheng Qin

{"title":"Influence function-based empirical likelihood for area under the receiver operating characteristic curve in presence of covariates.","authors":"Baoying Yang, Xinjie Hu, Gengsheng Qin","doi":"10.1177/09622802251345343","DOIUrl":"10.1177/09622802251345343","url":null,"abstract":"In receiver operating characteristicROC analysis, the area under the ROC curve (AUC) is a popular one number summary of the discriminatory accuracy of a diagnostic test. AUC measures the overall diagnostic accuracy of a test but fails to account for the effect of covariates when covariates are present and associated with the test results. Adjustment for covariate effects can greatly improve the diagnostic accuracy of a test. In this paper, using information provided by the influence function, empirical likelihood (EL) methods are proposed for inferences of AUC in presence of covariates. For parameters in the AUC regression model, it is shown that the asymptotic distribution of the influence function-based empirical log-likelihood ratio statistic is a standard chi-square distribution. Hence, confidence regions for the regression parameters can be obtained without any variance estimation. Simulation studies are conducted to compare the finite sample performances of the proposed EL based methods with the existing normal approximation (NA) based method in the AUC regression. Simulation results indicate that the bootstrap-calibrated influence function-based empirical likelihood (BIFEL ) confidence region outperforms the NA-based confidence region in terms of coverage probability. We also propose an interval estimation method for the covariate-adjusted AUC based on the BIFEL confidence region. Finally, we illustrate the recommended method with a real prostate-specific antigen data example.","PeriodicalId":22038,"journal":{"name":"Statistical Methods in Medical Research","volume":" ","pages":"1574-1589"},"PeriodicalIF":1.9,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144175030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Group sequential analysis of marked point processes: Plasma donation trials. 标记点过程的组序贯分析：血浆捐献试验。

IF 1.9 3区医学

Statistical Methods in Medical Research Pub Date : 2025-08-01 Epub Date: 2025-07-02 DOI: 10.1177/09622802251350263

Kecheng Li, Richard J Cook

{"title":"Group sequential analysis of marked point processes: Plasma donation trials.","authors":"Kecheng Li, Richard J Cook","doi":"10.1177/09622802251350263","DOIUrl":"10.1177/09622802251350263","url":null,"abstract":"Plasma donation plays a critical role in modern medicine by providing lifesaving treatments for patients with a wide range of conditions like bleeding disorders, immune deficiencies, and infections. Evaluation of devices used to collect blood plasma from donors is essential to ensure donor safety. We consider the design of plasma donation trials when the goal is to assess the safety of a new device on the response to transfusions compared to the standard device. A unique feature is that the number of donations per donor varies substantially so some individuals contribute more information and others less. The sample size formula is derived to ensure power requirements are met when analyses are based on generalized estimating equations and robust variance estimation. Strategies for interim monitoring based on group sequential designs using alpha spending functions are developed based on a robust covariance matrix for estimates of treatment effect over successive analyses. The design of a plasma donation study is illustrated where the focus is on assessing the safety of a new device with serious hypotensive adverse events as the primary outcome.","PeriodicalId":22038,"journal":{"name":"Statistical Methods in Medical Research","volume":" ","pages":"1646-1664"},"PeriodicalIF":1.9,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12365355/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144544952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Closed-form confidence intervals for saved time using summary statistics in Alzheimer's disease studies. 阿尔茨海默病研究中使用汇总统计节省时间的封闭式置信区间。

IF 1.9 3区医学

Statistical Methods in Medical Research Pub Date : 2025-08-01 Epub Date: 2025-07-04 DOI: 10.1177/09622802251348796

Guogen Shan, Yahui Zhang, Guoqiao Wang, Samuel S Wu, Aidong A Ding

引用次数: 0

Multiple imputation for systematically missing effect modifiers in individual participant data meta-analysis. 个体参与者数据荟萃分析中系统缺失效应修正因子的多重归因。

IF 1.9 3区医学

Statistical Methods in Medical Research Pub Date : 2025-08-01 Epub Date: 2025-06-20 DOI: 10.1177/09622802251348800

Robert Thiesmeier, Scott M Hofer, Nicola Orsini

{"title":"Multiple imputation for systematically missing effect modifiers in individual participant data meta-analysis.","authors":"Robert Thiesmeier, Scott M Hofer, Nicola Orsini","doi":"10.1177/09622802251348800","DOIUrl":"10.1177/09622802251348800","url":null,"abstract":"Individual participant data (IPD) meta-analysis of randomised trials is a crucial method for detecting and investigating effect modifications in medical research. However, few studies have explored scenarios involving systematically missing data on discrete effect modifiers (EMs) in IPD meta-analyses with a limited number of trials. This simulation study examines the impact of systematic missing values in IPD meta-analysis using a two-stage imputation method. We simulated IPD meta-analyses of randomised trials with multiple studies that had systematically missing data on the EM. A multivariable Weibull survival model was specified to assess beneficial (Hazard Ratio (HR)<math><mo>=</mo></math>0.8), null (HR<math><mo>=</mo></math>1.0), and harmful (HR<math><mo>=</mo></math>1.2) treatment effects for low, medium, and high levels of an EM, respectively. Bias and coverage were evaluated using Monte-Carlo simulations. The absolute bias for common and heterogeneous effect IPD meta-analyses was less than 0.016 and 0.007, respectively, with coverage close to its nominal value across all EM levels. An uncongenial imputation model resulted in larger bias, even when the proportion of studies with systematically missing data on the EM was small. Overall, the proposed two-stage imputation approach provided unbiased estimates with improved precision. The assumptions and limitations of this approach are discussed.","PeriodicalId":22038,"journal":{"name":"Statistical Methods in Medical Research","volume":" ","pages":"1590-1604"},"PeriodicalIF":1.9,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12365359/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144333871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Bayesian inference for nonlinear mixed-effects location scale and interval-censoring cure-survival models: An application to pregnancy miscarriage. 非线性混合效应的贝叶斯推断：位置尺度和间隔筛选治疗-生存模型：在妊娠流产中的应用。

IF 1.9 3区医学

Statistical Methods in Medical Research Pub Date : 2025-08-01 Epub Date: 2025-05-29 DOI: 10.1177/09622802251345485

Danilo Alvares, Cristian Meza, Rolando De la Cruz

{"title":"Bayesian inference for nonlinear mixed-effects location scale and interval-censoring cure-survival models: An application to pregnancy miscarriage.","authors":"Danilo Alvares, Cristian Meza, Rolando De la Cruz","doi":"10.1177/09622802251345485","DOIUrl":"10.1177/09622802251345485","url":null,"abstract":"Motivated by a pregnancy miscarriage study, we propose a Bayesian joint model for longitudinal and time-to-event outcomes that takes into account different complexities of the problem. In particular, the longitudinal process is modeled by means of a nonlinear specification with subject-specific error variance. In addition, the exact time of fetal death is unknown, and a subgroup of women is not susceptible to miscarriage. Hence, we model the survival process via a mixture cure model for interval-censored data. Finally, both processes are linked through the subject-specific longitudinal mean and variance. A simulation study is conducted in order to validate our joint model. In the real application, we use individual weighted and Cox-Snell residuals to assess the goodness-of-fit of our proposal versus a joint model that shares only the subject-specific longitudinal mean (standard approach). In addition, the leave-one-out cross-validation criterion is applied to compare the predictive ability of both models.","PeriodicalId":22038,"journal":{"name":"Statistical Methods in Medical Research","volume":" ","pages":"1525-1533"},"PeriodicalIF":1.9,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12365357/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144175029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Strategies to boost statistical efficiency in randomized oncology trials with primary time-to-event endpoints. 以主要事件时间为终点的随机肿瘤学试验提高统计效率的策略。

IF 1.9 3区医学

Statistical Methods in Medical Research Pub Date : 2025-08-01 Epub Date: 2025-06-23 DOI: 10.1177/09622802251343599

Alan D Hutson, Han Yu

引用次数: 0

Group sequential designs for survival outcomes with adaptive randomization. 适应随机化的生存结果组序设计。

IF 1.6 3区医学

Statistical Methods in Medical Research Pub Date : 2025-07-17 DOI: 10.1177/09622802251340250

Yaxian Chen, Yeonhee Park

{"title":"Group sequential designs for survival outcomes with adaptive randomization.","authors":"Yaxian Chen, Yeonhee Park","doi":"10.1177/09622802251340250","DOIUrl":"https://doi.org/10.1177/09622802251340250","url":null,"abstract":"Driven by evolving Food and Drug Administration recommendations, modern clinical trials demand innovative designs that strike a balance between statistical rigor and ethical considerations. Covariate-adjusted response-adaptive randomization (CARA) designs bridge this gap by utilizing patient attributes and responses to skew treatment allocation in favor of the treatment to be best for an individual patient's profiles. However, existing CARA designs for survival outcomes often rely on specific parametric models, constraining their applicability in clinical practice. To overcome this limitation, we propose a novel CARA method for survival outcomes (called CARAS) based on the Cox model, which improves model flexibility and mitigate risks of model misspecification. Additionally, we introduce a group sequential overlap-weighted log-rank test to preserve the type I error rate in group sequential trials using CARAS. Comprehensive simulation studies and a real-world trial example demonstrate the proposed method's clinical benefit, statistical efficiency, and robustness to model misspecification compared to traditional randomized controlled trial designs and response-adaptive randomization designs.","PeriodicalId":22038,"journal":{"name":"Statistical Methods in Medical Research","volume":" ","pages":"9622802251340250"},"PeriodicalIF":1.6,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144650606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Optimal treatment regimes in the presence of a cure fraction. 存在治愈分数的最佳治疗方案。

IF 1.6 3区医学

Statistical Methods in Medical Research Pub Date : 2025-07-17 DOI: 10.1177/09622802251338399

Chenrui Qi, Zicheng Lin, Baqun Zhang, Cunjie Lin, Zishu Zhan

{"title":"Optimal treatment regimes in the presence of a cure fraction.","authors":"Chenrui Qi, Zicheng Lin, Baqun Zhang, Cunjie Lin, Zishu Zhan","doi":"10.1177/09622802251338399","DOIUrl":"https://doi.org/10.1177/09622802251338399","url":null,"abstract":"Despite the widespread use of time-to-event data in precision medicine, existing research has often neglected the presence of the cure fraction, assuming that all individuals will inevitably experience the event of interest. When a cure fraction is present, the cure rate and survival time of uncured patients should be considered in estimating the optimal individualized treatment regimes. In this study, we propose direct methods for estimating the optimal individualized treatment regimes that either maximize the cure rate or mean survival time of uncured patients. Additionally, we propose two optimal individualized treatment regimes that balance the tradeoff between the cure rate and mean survival time of uncured patients based on a constrained estimation framework for a more comprehensive assessment of individualized treatment regimes. This framework allows us to estimate the optimal individualized treatment regime that maximizes the population's cure rate without significantly compromising the mean survival time of those who remain uncured or maximizes the mean survival time of uncured patients while having the cure rate controlled at a desired level. The exterior-point algorithm is adopted to expedite the resolution of the constrained optimization problem and statistical validity is rigorously established. Furthermore, the advantages of the proposed methods are demonstrated via simulations and analysis of esophageal cancer data.","PeriodicalId":22038,"journal":{"name":"Statistical Methods in Medical Research","volume":" ","pages":"9622802251338399"},"PeriodicalIF":1.6,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144650607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Design of egocentric network-based studies to estimate causal effects under interference. 设计以自我为中心的网络为基础的研究，以估计干扰下的因果效应。

IF 1.6 3区医学

Statistical Methods in Medical Research Pub Date : 2025-07-17 DOI: 10.1177/09622802251357021

Junhan Fang, Donna Spiegelman, Ashley L Buchanan, Laura Forastiere

{"title":"Design of egocentric network-based studies to estimate causal effects under interference.","authors":"Junhan Fang, Donna Spiegelman, Ashley L Buchanan, Laura Forastiere","doi":"10.1177/09622802251357021","DOIUrl":"https://doi.org/10.1177/09622802251357021","url":null,"abstract":"Many public health interventions are conducted in settings where individuals are connected and the intervention assigned to some individuals may spill over to other individuals. In these settings, we can assess: (a) the individual effect on the treated, (b) the spillover effect on untreated individuals through an indirect exposure to the intervention, and (c) the overall effect on the whole population. Here, we consider an egocentric network-based randomized design in which a set of index participants is recruited and randomly assigned to treatment, while data are also collected on their untreated network members. Such a design is common in peer education interventions conceived to leverage behavioral influence among peers. Using the potential outcomes framework, we first clarify the assumptions required to rely on an identification strategy that is commonly used in the well-studied two-stage randomized design. Under these assumptions, causal effects can be jointly estimated using a regression model with a block-diagonal structure. We then develop sample size formulas for detecting individual, spillover, and overall effects for single and joint hypothesis tests, and investigate the role of different parameters. Finally, we illustrate the use of our sample size formulas for an egocentric network-based randomized experiment to evaluate a peer education intervention for HIV prevention.","PeriodicalId":22038,"journal":{"name":"Statistical Methods in Medical Research","volume":" ","pages":"9622802251357021"},"PeriodicalIF":1.6,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144650605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Semiparametric regression analysis of interval-censored failure time data with a cure subgroup and nonignorable missing covariates. 具有可治愈子群和不可忽略的缺失协变量的间隔截尾失效时间数据的半参数回归分析。

IF 1.6 3区医学

Statistical Methods in Medical Research Pub Date : 2025-07-14 DOI: 10.1177/09622802251356592

Yichen Lou, Mingyue Du, Peijie Wang, Xinyuan Song

引用次数: 0