Journal of Biopharmaceutical Statistics最新文献_第10页

Response to comment on "Transporting survival of an HIV clinical trial to the external target populations by Lee et al. (2024)". 对 "Lee 等人将艾滋病临床试验的存活率转移到外部目标人群（2024 年）"评论的答复。

IF 1.2 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2024-07-08 DOI: 10.1080/10543406.2024.2373449

Shu Yang, Xiang Zhang

引用次数: 0

A Bayesian phase I-II clinical trial design to find the biological optimal dose on drug combination. 贝叶斯 I-II 期临床试验设计，寻找药物组合的生物最佳剂量。

IF 1.1 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2024-07-03 Epub Date: 2023-07-17 DOI: 10.1080/10543406.2023.2236208

Ziqing Wang, Jingyi Zhang, Tian Xia, Ruyue He, Fangrong Yan

引用次数: 0

Two-stage response adaptive randomization designs for multi-arm trials with binary outcome. 二元结果多臂试验的两阶段反应自适应随机化设计。

IF 1.1 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2024-07-03 Epub Date: 2023-07-15 DOI: 10.1080/10543406.2023.2234028

Xinlin Lu, Guogen Shan

{"title":"Two-stage response adaptive randomization designs for multi-arm trials with binary outcome.","authors":"Xinlin Lu, Guogen Shan","doi":"10.1080/10543406.2023.2234028","DOIUrl":"10.1080/10543406.2023.2234028","url":null,"abstract":"In recent years, adaptive randomization methods have gained significant popularity in clinical research and trial design due to their ability to provide both efficiency and flexibility in adjusting the statistical procedures of ongoing clinical trials. For a study to compare multiple treatments, a multi-arm two-stage design could be utilized to select the best treatment from the first stage and further compare that treatment with control in the second stage. The traditional design used equal randomization in both stages. To better utilize the interim results from the first stage, we propose to develop response adaptive randomization two-stage designs for a multi-arm clinical trial with binary outcome. Two allocation methods are considered: (1) an optimal allocation based on a sequential design; (2) the play-the-winner rule. Optimal multi-arm two-stage designs are obtained under three criteria: minimizing the expected number of failures, minimizing the average expected sample size, and minimizing the expected sample size under the null hypothesis. Simulation studies show that the proposed adaptive design based on the play-the-winner rule has good performance. A phase II trial for patients with pancreas adenocarcinoma and a germline BRCA<math><mrow><mo>/</mo></mrow></math>PALB2 mutation was used to illustrate the application of the proposed response adaptive randomization designs.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"526-538"},"PeriodicalIF":1.1,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10788381/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9782235","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

Statistical Considerations and Software for Designing Sequential, Multiple Assignment, Randomized Trials (SMART) with a Survival Final Endpoint. 设计以生存为最终终点的连续、多次分配、随机试验 (SMART) 的统计考虑因素和软件。

IF 1.1 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2024-07-03 Epub Date: 2023-07-11 DOI: 10.1080/10543406.2023.2233616

Sasha Kravets, Amy S Ruppert, Sawyer B Jacobson, Jennifer G Le-Rademacher, Sumithra J Mandrekar

{"title":"Statistical Considerations and Software for Designing Sequential, Multiple Assignment, Randomized Trials (SMART) with a Survival Final Endpoint.","authors":"Sasha Kravets, Amy S Ruppert, Sawyer B Jacobson, Jennifer G Le-Rademacher, Sumithra J Mandrekar","doi":"10.1080/10543406.2023.2233616","DOIUrl":"10.1080/10543406.2023.2233616","url":null,"abstract":"Sequential, multiple assignment, randomized trial (SMART) designs are appropriate for comparing adaptive treatment interventions, in which intermediate outcomes (called tailoring variables) guide subsequent treatment decisions for individual patients. Within a SMART design, patients may be re-randomized to subsequent treatments following the outcomes of their intermediate assessments. In this paper, we provide an overview of statistical considerations necessary to design and implement a two-stage SMART design with a binary tailoring variable and a survival final endpoint. A chronic lymphocytic leukemia trial with a final endpoint of progression-free survival is used as an example for the simulations to assess how design parameters, including, choice of randomization ratios for each stage of randomization, and response rates of the tailoring variable affect the statistical power. We assess the choice of weights from restricted re-randomization on data analyses and appropriate hazard rate assumptions. Specifically, for a given first-stage therapy and prior to the tailoring variable assessment, we assume equal hazard rates for all patients randomized to a treatment arm. After the tailoring variable assessment, individual hazard rates are assumed for each intervention path. Simulation studies demonstrate that the response rate of the binary tailoring variable impacts power as it directly impacts the distribution of patients. We also confirm that when the first stage randomization is 1:1, it is not necessary to consider the first stage randomization ratio when applying the weights. We provide an R-shiny application for obtaining power for a given sample size for SMART designs.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"539-552"},"PeriodicalIF":1.1,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9826496","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

Direct estimation of volume under the ROC surface with verification bias. 带验证偏差的 ROC 表面下体积直接估算。

IF 1.1 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2024-07-03 Epub Date: 2023-07-20 DOI: 10.1080/10543406.2023.2236202

Shuangfei Shi, Gengsheng Qin

{"title":"Direct estimation of volume under the ROC surface with verification bias.","authors":"Shuangfei Shi, Gengsheng Qin","doi":"10.1080/10543406.2023.2236202","DOIUrl":"10.1080/10543406.2023.2236202","url":null,"abstract":"In practice, the receiver operating characteristic (ROC) curve of a diagnostic test is widely used to show the performance of the test for discriminating two-class events. The area under the ROC curve (AUC) is proposed as an index for the assessment of the diagnostic accuracy of the test under consideration. Due to ethical and cost considerations associated with application of gold standard (GS) tests, only a subset of the patients initially tested have verified disease status. Statistical evaluation of the test performance based only on test results from subjects with verified disease status are typically biased. Various AUC estimation methods for tests with verification biased data have been developed over the last few decades. In this article, we develop new direct estimation methods for the volume under the ROC surface (VUS) by extending the AUC estimation methods for two-class diagnostic tests to three-class diagnostic tests in the presence of verification bias. The proposed methods will provide a comprehensive guide to deal with the verification bias in three-class diagnostic test accuracy studies and lead to a better choice of diagnostic tests.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"553-581"},"PeriodicalIF":1.1,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10214604","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

Stochastic curtailment tests for phase II trial with time-to-event outcome using the concept of relative time in the case of non-proportional hazards. 在非比例危害的情况下，使用相对时间概念对具有时间到事件结果的 II 期试验进行随机缩减试验。

IF 1.1 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2024-07-03 Epub Date: 2023-08-14 DOI: 10.1080/10543406.2023.2244056

Palash Sharma, Milind A Phadnis

{"title":"Stochastic curtailment tests for phase II trial with time-to-event outcome using the concept of relative time in the case of non-proportional hazards.","authors":"Palash Sharma, Milind A Phadnis","doi":"10.1080/10543406.2023.2244056","DOIUrl":"10.1080/10543406.2023.2244056","url":null,"abstract":"As part of the drug development process, interim analysis is frequently used to design efficient phase II clinical trials. A stochastic curtailment framework is often deployed wherein a decision to continue or curtail the trial is taken at each interim look based on the likelihood of observing a positive or negative treatment effect if the trial were to continue to its anticipated end. Thus, curtailment can take place due to evidence of early efficacy or futility. Traditionally, in the case of time-to-event endpoints, interim monitoring is conducted in a two-arm clinical trial using the log-rank test, often with the assumption of proportional hazards. However, when this is violated, the log-rank test may not be appropriate, resulting in loss of power and subsequently inaccurate sample sizes. In this paper, we propose stochastic curtailment methods for two-arm phase II trial with the flexibility to allow non-proportional hazards. The proposed methods are built utilizing the concept of relative time assuming that the survival times in the two treatment arms follow two different Weibull distributions. Three methods - conditional power, predictive power and Bayesian predictive probability - are discussed along with corresponding sample size calculations. The monitoring strategy is discussed with a real-life example.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"596-611"},"PeriodicalIF":1.1,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10312957","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

Group sequential multi-arm multi-stage survival trial design with treatment selection. 分组顺序多臂多阶段生存试验设计与治疗选择。

IF 1.1 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2024-07-03 Epub Date: 2023-07-16 DOI: 10.1080/10543406.2023.2235409

Jianrong Wu, Yimei Li

{"title":"Group sequential multi-arm multi-stage survival trial design with treatment selection.","authors":"Jianrong Wu, Yimei Li","doi":"10.1080/10543406.2023.2235409","DOIUrl":"10.1080/10543406.2023.2235409","url":null,"abstract":"Multi-arm trials are increasingly of interest because for many diseases; there are multiple experimental treatments available for testing efficacy. Several novel multi-arm multi-stage (MAMS) clinical trial designs have been proposed. However, a major hurdle to adopting the group sequential MAMS routinely is the computational effort of obtaining stopping boundaries. For example, the method of Jaki and Magirr for time-to-event endpoint, implemented in R package MAMS, requires complicated computational efforts to obtain stopping boundaries. In this study, we develop a group sequential MAMS survival trial design based on the sequential conditional probability ratio test. The proposed method is an improvement of the Jaki and Magirr's method in the following three directions. First, the proposed method provides explicit solutions for both futility and efficacy boundaries to an arbitrary number of stages and arms. Thus, it avoids complicated computational efforts for the trial design. Second, the proposed method provides an accurate number of events for the fixed sample and group sequential designs. Third, the proposed method uses a new procedure for interim analysis which preserves the study power.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"453-468"},"PeriodicalIF":1.1,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9783887","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 new type of generalized information criterion for regularization parameter selection in penalized regression with application to treatment process data. 用于惩罚性回归正则化参数选择的新型广义信息准则，并将其应用于治疗过程数据。

IF 1.1 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2024-07-03 Epub Date: 2023-07-17 DOI: 10.1080/10543406.2023.2228399

Amir Hossein Ghatari, Mina Aminghafari

{"title":"A new type of generalized information criterion for regularization parameter selection in penalized regression with application to treatment process data.","authors":"Amir Hossein Ghatari, Mina Aminghafari","doi":"10.1080/10543406.2023.2228399","DOIUrl":"10.1080/10543406.2023.2228399","url":null,"abstract":"We propose a new approach to select the regularization parameter using a new version of the generalized information criterion (<math><mi>GIC</mi></math>) in the subject of penalized regression. We prove the identifiability of bridge regression model as a prerequisite of statistical modeling. Then, we propose asymptotically efficient generalized information criterion (<math><mi>AGIC</mi></math>) and prove that it has asymptotic loss efficiency. Also, we verified the better performance of <math><mi>AGIC</mi></math> in comparison to the older versions of <math><mi>GIC</mi></math>. Furthermore, we propose <math><mi>MSE</mi></math> search paths to order the selected features by lasso regression based on numerical studies. The <math><mi>MSE</mi></math> search paths provide a way to cover the lack of feature ordering in lasso regression model. The performance of <math><mi>AGIC</mi></math> with other types of <math><mi>GIC</mi></math> is compared using <math><mi>MSE</mi></math> and model utility in simulation study. We exert <math><mi>AGIC</mi></math> and other criteria to analyze breast and prostate cancer and Parkinson disease datasets. The results confirm the superiority of <math><mi>AGIC</mi></math> in almost all situations.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"488-512"},"PeriodicalIF":1.1,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9783898","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

Sample size reestimation and Bayesian predictive probability for single-arm clinical trials with a time-to-event endpoint using Weibull distribution with unknown shape parameter. 使用具有未知形状参数的 Weibull 分布，对具有时间到事件终点的单臂临床试验进行样本量再估计和贝叶斯预测概率。

IF 1.1 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2024-07-03 Epub Date: 2023-08-06 DOI: 10.1080/10543406.2023.2234998

Muhammad Waleed, Jianghua He, Milind A Phadnis

{"title":"Sample size reestimation and Bayesian predictive probability for single-arm clinical trials with a time-to-event endpoint using Weibull distribution with unknown shape parameter.","authors":"Muhammad Waleed, Jianghua He, Milind A Phadnis","doi":"10.1080/10543406.2023.2234998","DOIUrl":"10.1080/10543406.2023.2234998","url":null,"abstract":"This manuscript consists of two topics. Firstly, we explore the utility of internal pilot study (IPS) approach for reestimating sample size at an interim stage when a reliable estimate of the nuisance shape parameter of the Weibull distribution for modeling survival data is unavailable during the planning phase of a study. Although IPS approach can help rescue the study power, it is noted that the adjusted sample size can be as much as twice the initially planned sample size, which may put substantial practical constraints to continue the study. Secondly, we discuss Bayesian predictive probability for conducting interim analyses to obtain preliminary evidence of efficacy or futility of an experimental treatment warranting early termination of a clinical trial. In the context of single-arm clinical trials with time-to-event endpoints following Weibull distribution, we present the calculation of the Bayesian predictive probability when the shape parameter of the Weibull distribution is unknown. Based on the data accumulated at the interim, we propose two approaches which rely on the posterior mode or the entire posterior distribution of the shape parameter. To account for uncertainty in the shape parameter, it is recommended to incorporate its entire posterior distribution in our calculation.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"469-487"},"PeriodicalIF":1.1,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9949124","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

Using Bayesian hierarchical models for controlled post hoc subgroup analysis of clinical trials: application to smoking cessation treatment in American Indians and Alaska Natives. 使用贝叶斯分层模型对临床试验进行控制性事后亚组分析：应用于美国印第安人和阿拉斯加原住民的戒烟治疗。

IF 1.2 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2024-07-03 Epub Date: 2023-07-07 DOI: 10.1080/10543406.2023.2233598

Elena Shergina, Kimber P Richter, Christine Makosky Daley, Babalola Faseru, Won S Choi, Byron J Gajewski

{"title":"Using Bayesian hierarchical models for controlled post hoc subgroup analysis of clinical trials: application to smoking cessation treatment in American Indians and Alaska Natives.","authors":"Elena Shergina, Kimber P Richter, Christine Makosky Daley, Babalola Faseru, Won S Choi, Byron J Gajewski","doi":"10.1080/10543406.2023.2233598","DOIUrl":"10.1080/10543406.2023.2233598","url":null,"abstract":"Clinical trials powered to detect subgroup effects provide the most reliable data on heterogeneity of treatment effect among different subpopulations. However, pre-specified subgroup analysis is not always practical and post hoc analysis results should be examined cautiously. Bayesian hierarchical modelling provides grounds for defining a controlled post hoc analysis plan that is developed after seeing outcome data for the population but before unblinding the outcome by subgroup. Using simulation based on the results from a tobacco cessation clinical trial conducted among the general population, we defined an analysis plan to assess treatment effect among American Indians and Alaska Natives (AI/AN) enrolled in the study. Patients were randomized into two arms using Bayesian adaptive design. For the opt-in arm, clinicians offered a cessation treatment plan after verifying that a patient was ready to quit. For the opt-out arm, clinicians provided all participants with free cessation medications and referred them to a Quitline. The study was powered to test a hypothesis of significantly higher quit rates for the opt-out arm at one-month post randomization. Overall, one-month abstinence rates were 15.9% and 21.5% (opt-in and opt-out arm, respectively). For AI/AN, one-month abstinence rates were 10.2% and 22.0% (opt-in and opt-out arm, respectively). The posterior probability that the abstinence rate in the treatment arm is higher is 0.96, indicating that AI/AN demonstrate response to treatment at almost the same probability as the whole population.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"513-525"},"PeriodicalIF":1.2,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10771533/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10201603","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