Journal of Biopharmaceutical Statistics最新文献_第4页

Bayesian meta-analysis for rare outcomes. 罕见结果的贝叶斯荟萃分析。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-10-01 Epub Date: 2025-06-09 DOI: 10.1080/10543406.2025.2512205

Ohud Alqasem, Haydar Demirhan, Anil Dolgun

{"title":"Bayesian meta-analysis for rare outcomes.","authors":"Ohud Alqasem, Haydar Demirhan, Anil Dolgun","doi":"10.1080/10543406.2025.2512205","DOIUrl":"10.1080/10543406.2025.2512205","url":null,"abstract":"Binary meta-analysis studies with rare outcomes frequently include zero or a small number of observations in study groups, creating a sparsity issue with the data. The corrections applied to eliminate the impact of the zero cell counts introduce a bias to the meta-analysis results and potentially distort the inferences about the treatment effect and heterogeneity among the studies. The boundaries of interval estimates become highly biased due to the sparsity of the data. This study proposes two Bayesian random-effects meta-analysis models based on the beta-binomial model with an arc-sine-square-root transformation. The performance of the models in estimating the treatment effect and the in-between study variance is assessed with an extensive Monte Carlo simulation study, and a frequently referred meta-analysis dataset is revisited. The models provide accurate estimates of treatment effect and heterogeneity parameters without a continuity correction. They provide well-calibrated, narrow interval estimates with sufficient coverage of true treatment effect and in-between study variance. They are robust against zero cell counts, very low event probabilities, and unbalanced, skewed data distributions. Recommendations are given for the practical use of the proposed models, and the required model scripts are provided to implement the models using R software.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"1313-1335"},"PeriodicalIF":1.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144250951","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

Joint linear and nonlinear mixed effects model with random change points for left-censored longitudinal data: application to HIV surveillance. 左截尾纵向数据随机变点的线性和非线性混合效应联合模型：在HIV监测中的应用。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-10-01 Epub Date: 2025-08-22 DOI: 10.1080/10543406.2025.2547592

Binod Manandhar, Hongbin Zhang

引用次数: 0

Weighted sum and order statistics methods for dynamic information borrowing in basket trials. 篮子试验中动态信息借用的加权和序统计方法。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-10-01 Epub Date: 2025-08-01 DOI: 10.1080/10543406.2025.2537088

Cheng Huang, Chenghao Chu, Yimeng Lu, Bingming Yi, Ming-Hui Chen

{"title":"Weighted sum and order statistics methods for dynamic information borrowing in basket trials.","authors":"Cheng Huang, Chenghao Chu, Yimeng Lu, Bingming Yi, Ming-Hui Chen","doi":"10.1080/10543406.2025.2537088","DOIUrl":"10.1080/10543406.2025.2537088","url":null,"abstract":"In basket trials, the same investigational therapy is studied on multiple sub-populations simultaneously under a single protocol. The goal of basket trials is to identify the sub-populations in which the therapy is effective. Basket trials have become a popular and generally accepted study design in disease areas including but not limited to oncology and rare diseases, for their advantages in operation and ethical considerations. Extensive research work on information borrowing has been conducted to explore the statistical efficiency in basket trials. In this paper, two novel frequentist methods for basket trials are proposed. The first method borrows information to minimize the mean squared errors in the treatment effect estimation. The second method uses information across all baskets to optimize the multiple testing task in detecting the treatment effects in each basket. Extensive simulation studies show that the proposed methods substantially improved statistical efficiency in basket trials while limiting family-wise error rate inflation. Both methods can be implemented with common statistical models with or without adjustment for covariates.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"1420-1439"},"PeriodicalIF":1.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144762352","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

Interval estimation for three-class Youden index with verification bias. 具有验证偏差的三类约登指数的区间估计。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-10-01 Epub Date: 2025-08-25 DOI: 10.1080/10543406.2025.2549361

Shuangfei Shi, Shirui Wang, Gengsheng Qin

引用次数: 0

BPED: A Bayesian basket design for pediatric trials with external data. 基于外部数据的儿科试验贝叶斯篮子设计。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-10-01 Epub Date: 2025-06-04 DOI: 10.1080/10543406.2025.2512203

Yimei Li, Ying Yuan

{"title":"BPED: A Bayesian basket design for pediatric trials with external data.","authors":"Yimei Li, Ying Yuan","doi":"10.1080/10543406.2025.2512203","DOIUrl":"10.1080/10543406.2025.2512203","url":null,"abstract":"The basket trial is a novel type of trial that evaluates one treatment in multiple indications (such as cancer types) simultaneously. One challenge of applying the basket trial design to pediatric studies is limited accrual, resulting in low statistical power. To address this issue, we propose a Bayesian basket design for pediatric trials with external data (BPED) that performs dual-information borrowing to improve the design efficiency: borrow information from the external data to the pediatric trial, and borrow information between the cancer types within the pediatric trial. BPED also accommodates potential heterogeneous treatment effects across cancer types by allowing each cancer type belonging to the sensitive or insensitive latent subgroups. The design adaptively updates the members of the subgroups based on the accumulated pediatric and external data to make go/no-go decisions for each cancer type. The simulation study shows that, compared to some existing designs, BPED yields higher power to detect the treatment effect for sensitive cancer types and maintains a desirable type I error rate for insensitive cancer types.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"1293-1312"},"PeriodicalIF":1.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12354168/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144217621","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

Sample size determination for a study with variable follow-up time. 可变随访时间研究的样本量确定。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-10-01 Epub Date: 2025-02-26 DOI: 10.1080/10543406.2025.2469879

Guogen Shan, Yahui Zhang, Xinlin Lu, Yulin Li, Minggen Lu, Zhigang Li

{"title":"Sample size determination for a study with variable follow-up time.","authors":"Guogen Shan, Yahui Zhang, Xinlin Lu, Yulin Li, Minggen Lu, Zhigang Li","doi":"10.1080/10543406.2025.2469879","DOIUrl":"10.1080/10543406.2025.2469879","url":null,"abstract":"For a study to detect the outcome change at the follow-up visit from baseline, the pre-test and post-test design is commonly used to assess the treatment-control difference. Several existing methods were developed for sample size calculation including the subtraction method, analysis of covariance (ANCOVA), and linear mixed model. The first two methods can be used when the follow-up time is the same as scheduled. Although the linear mixed model can analyze the repeated measures by including the actual visit time to account for the variability of the follow-up time, it often assumes a constant treatment-control difference at any follow-up time which may not be correct in practice. We propose to develop a new statistical model to compare the treatment-control difference at the planned follow-up time while controlling for the follow-up time variation. The spline functions are used to estimate the trajectories of the treatment arm and the control arm. We compared the performance of these methods with regards to type I error rate, statistical power, and sample size under various conditions. These four methods all control for the type I error rate. The new method and the ANCOVA method are often more powerful than the other two methods, and they have similar statistical power when a linear disease progression is satisfied. For a study with non-linear disease progression, the new method can be more powerful than the ANCOVA method. We used data from a completed Alzheimer's disease trial to illustrate the application of the proposed method.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"1211-1226"},"PeriodicalIF":1.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12353296/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143517579","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

Saddlepoint p-values for the class of bivariate two-sample tests under generalized randomized block design. 广义随机区组设计下二元双样本检验类的鞍点p值。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-10-01 Epub Date: 2025-12-05 DOI: 10.1080/10543406.2025.2592617

Abd El-Raheem M Abd El-Raheem, Ibrahim A A Shanan, Mona Hosny

引用次数: 0

Blinded sample size re-estimation in a crossover study. 交叉研究中的盲法样本量重新估计。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-10-01 Epub Date: 2025-11-18 DOI: 10.1080/10543406.2025.2575947

Shaofei Zhao, Balakrishna Hosmane, Chen Chen, Yi-Lin Chiu

{"title":"Blinded sample size re-estimation in a crossover study.","authors":"Shaofei Zhao, Balakrishna Hosmane, Chen Chen, Yi-Lin Chiu","doi":"10.1080/10543406.2025.2575947","DOIUrl":"10.1080/10543406.2025.2575947","url":null,"abstract":"Bioequivalence studies play a pivotal role in drug development by establishing the clinical equivalence of two drug formulations. These studies often utilize crossover designs to facilitate within-subject treatment comparisons, optimizing statistical power with fewer subjects. However, uncertainty regarding the variance of a new drug or formulation during planning presents a challenge for sample size determination. While adaptive designs offer a potential solution, their application in crossover studies is less explored compared to group sequential designs, and many existing adaptive methods require data unblinding during the trial. Only two blinded sample size re-estimation approaches have been developed in crossover settings to date. In this paper, we propose a novel method for blinded within-subject variance estimation at interim analysis and re-estimate the sample size to achieve the desired power. We thoroughly investigate its analytical properties and introduce a refined, unbiased estimator. Through extensive simulation studies, our method shows comparable performance to existing blinded approaches and offers a distinct advantage in scenarios with small treatment differences and large subject variances.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"1615-1633"},"PeriodicalIF":1.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145551806","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

Defining optimal cut-off points for multiple class ROC analysis: generalization of the Index of Union method. 定义多类别ROC分析的最佳截断点：联合指数法的推广。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-10-01 Epub Date: 2025-07-10 DOI: 10.1080/10543406.2025.2528639

İlker Ünal, Esin Ünal, Yaşar Sertdemir, Murat Kobaner

引用次数: 0

Multi-armed bandits backfill Bayesian optimal interval design. 多臂土匪回填贝叶斯最优区间设计。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-10-01 Epub Date: 2025-12-21 DOI: 10.1080/10543406.2025.2602463

Masahiro Kojima, Kentaro Takeda

引用次数: 0