Journal of Biopharmaceutical Statistics最新文献_第5页

Enhancing dose selection in phase I cancer trials: Extending the Bayesian Logistic Regression Model with non-DLT adverse events integration. 加强I期癌症试验的剂量选择：扩展非dlt不良事件整合的贝叶斯逻辑回归模型。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-10-01 Epub Date: 2025-11-24 DOI: 10.1080/10543406.2025.2589734

Andrea Nizzardo, Luca Genetti, Marco Pergher

{"title":"Enhancing dose selection in phase I cancer trials: Extending the Bayesian Logistic Regression Model with non-DLT adverse events integration.","authors":"Andrea Nizzardo, Luca Genetti, Marco Pergher","doi":"10.1080/10543406.2025.2589734","DOIUrl":"10.1080/10543406.2025.2589734","url":null,"abstract":"This work introduces the Burdened Bayesian Logistic Regression Model (BBLRM), an enhancement of the Bayesian Logistic Regression Model (BLRM) for dose-finding in phase I oncology trials. The BLRM determines the maximum tolerated dose (MTD) based on dose-limiting toxicities (DLTs). However, clinicians often perceive model-based designs like BLRM as complex and less conservative than rule-based designs, such as the widely used 3 + 3 method. To address these concerns, BBLRM incorporates non-DLT adverse events (nDLTAEs), which, although not severe enough to be DLTs, indicate potential toxicity risks at higher doses. BBLRM introduces an additional parameter δ to account for nDLTAEs, adjusting toxicity probability estimates to make dose escalation more conservative while maintaining accurate MTD allocation. This parameter, generated basing on the proportion of patients experiencing nDLTAEs, is tuned to balance conservatism with model performance, reducing the risk of selecting overly toxic doses. Additionally, involving clinicians in identifying nDLTAEs enhances their engagement in the dose-finding process. A simulation study compares BBLRM with two other BLRM methods and a two-stage Continual Reassessment Method (CRM) incorporating nDLTAEs. Results show that BBLRM reduces the proportion of toxic doses selected as MTD without compromising the accuracy in MTD identification. These findings suggest that integrating nDLTAEs can improve the safety and acceptance of model-based designs in phase I oncology trials.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"1648-1668"},"PeriodicalIF":1.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145589649","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

On improving the accuracy of prediction in Cox models for failure times using copulas. 利用copula提高Cox模型失效时间预测的准确性。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-10-01 Epub Date: 2025-09-19 DOI: 10.1080/10543406.2025.2557573

Xiaofeng Liu, Ayyub Sheikhi

引用次数: 0

Sample size reduction in preclinical experiments: A Bayesian sequential decision-making framework. 临床前实验的样本量减少：贝叶斯顺序决策框架。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-10-01 Epub Date: 2025-09-10 DOI: 10.1080/10543406.2025.2556680

Jizhou Kang, Theodoro Koulis, Tony Pourmohamad

{"title":"Sample size reduction in preclinical experiments: A Bayesian sequential decision-making framework.","authors":"Jizhou Kang, Theodoro Koulis, Tony Pourmohamad","doi":"10.1080/10543406.2025.2556680","DOIUrl":"10.1080/10543406.2025.2556680","url":null,"abstract":"When animals are used in a preclinical experiment, ethical concerns may arise regarding animal welfare. The 3Rs principles were developed to guide more humane animal research practices. This article specifically addresses the reduction aspect of the 3Rs. Under our proposed framework, the preclinical experiment is conducted sequentially, and at every stage of the experiment we examine the outcome and decide whether to stop early for efficacy or futility. Compared to traditional methods in the literature, which typically only check for efficacy, the proposed method has the potential to further reduce the number of animals needed in an experiment. The proposed design requires specifying loss functions at every stage of the experiment. These functions may be directly related to the actual cost of conducting the study or can be calibrated to reflect the prior belief that the drug will be effective. Decisions are made based on minimizing the posterior expected loss. We evaluate the design methodology through simulation studies that involve two-arm experiments with either binary or continuous endpoints. Additionally, we also provide examples taken from real preclinical experiments.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"1544-1559"},"PeriodicalIF":1.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145034648","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

Novel machine learning approach to differential cell flow cytometry analysis based on projection pursuit. 基于投影寻踪的差分细胞流式细胞术分析的新机器学习方法。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-10-01 Epub Date: 2025-04-20 DOI: 10.1080/10543406.2025.2490725

Mahan Dastgiri, Javier Cabrera, Yajie Duan, Davit Sargsyan, Craig W Gambogi, Abraham Adokwei, Rebecca Mary Peter, PoChung Chou, Ge Cheng, Chun-Pang Lin, Jocelyn Sendecki, Helena Geys, Kanaka Tatikola, Ah-Ng Kong

{"title":"Novel machine learning approach to differential cell flow cytometry analysis based on projection pursuit.","authors":"Mahan Dastgiri, Javier Cabrera, Yajie Duan, Davit Sargsyan, Craig W Gambogi, Abraham Adokwei, Rebecca Mary Peter, PoChung Chou, Ge Cheng, Chun-Pang Lin, Jocelyn Sendecki, Helena Geys, Kanaka Tatikola, Ah-Ng Kong","doi":"10.1080/10543406.2025.2490725","DOIUrl":"10.1080/10543406.2025.2490725","url":null,"abstract":"This paper introduces the novel methodology of differential projection pursuit and its applications to the analysis of large datasets. The method was applied to a cell flow cytometry dataset as an alternative approach to analyze this type of data. Multicolor cell flow cytometry is a well-established laboratory technique to identify cell subpopulations by measuring their physical and biochemical characteristics. Differential projection pursuit helps to find regions with maximal differences between two or more treatments or distributions. Data analysis in flow cytometry relies on gating, the process of manually selecting successive subpopulations of cells using two-dimensional plots. Plotting the variables only two at a time could mask the hidden structure present in the data, and manual selection makes the analysis inconsistent and arbitrary. The new methodology could automate flow cytometry analysis by utilizing the combination of projection pursuit, data nuggets, and factor analysis. When applied to flow cytometry data, differential projection pursuit allows researchers to quickly identify differences in cell populations exposed to different experimental conditions. This methodology could create a platform to explore differences in large datasets and improve the cell flow cytometry analysis clarity and reproducibility by considering the data in its true dimensional space and through automation, respectively.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"1244-1256"},"PeriodicalIF":1.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144060868","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

Application of marginal structural models for causal inference on the treatment effect for overall survival in randomized controlled trials with control arm patients switching to active intervention after disease progression. 应用边际结构模型对随机对照试验中治疗效果对总生存率的因果推断，对照组患者在疾病进展后转为积极干预。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-10-01 Epub Date: 2025-08-26 DOI: 10.1080/10543406.2025.2547591

Jing Xu, Camden Bay, Bingxia Wang, Guohui Liu, Cong Li

{"title":"Application of marginal structural models for causal inference on the treatment effect for overall survival in randomized controlled trials with control arm patients switching to active intervention after disease progression.","authors":"Jing Xu, Camden Bay, Bingxia Wang, Guohui Liu, Cong Li","doi":"10.1080/10543406.2025.2547591","DOIUrl":"10.1080/10543406.2025.2547591","url":null,"abstract":"This research explores the application of marginal structural models (MSMs) in evaluating the causal treatment effect of active intervention versus control on overall survival in randomized clinical trials (RCTs) allowing for control arm patients to switch to active intervention after disease progression. When MSMs are applied in RCTs under this type of treatment switching setting, the question of interest and model specifications differ from both observational studies and from RCTs where patients in both arms are permitted to take alternative treatments after disease progression. A violation of structural positivity may result as an undesired consequence if MSM model weights are constructed using data directly from both arms. This research proposes a two-step approach to avoid this issue. Through simulation studies, it is demonstrated that the proposed approach allows for MSM to be used for analyzing survival data to detect causal active treatment effects under this one-way treatment switching setting. Additionally, estimation for the causal effect of the active intervention as the next line (post-disease progression) therapy can also be obtained from the MSM approach. A case study is presented to illustrate the application of MSMs under this type of treatment switching setting.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"1493-1510"},"PeriodicalIF":1.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144979493","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

Bayesian optimal Phase II survival trial design with event-driven approach. 基于事件驱动方法的贝叶斯最优II期生存试验设计。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-10-01 Epub Date: 2025-06-08 DOI: 10.1080/10543406.2025.2512202

Yuntong Li, Jianrong Wu

引用次数: 0

Accounting for long-term survival: a smoothed piecewise model for event time projection in cellular immunotherapy trials. 考虑长期生存：细胞免疫治疗试验中事件时间投射的平滑分段模型。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-09-30 DOI: 10.1080/10543406.2026.2731184

Zixing Wang, Qingyang Zhang, Jin Xie, Allen Xue, James Whitmore

引用次数: 0

Model generalizability considerations in development and evaluation of SaMD. SaMD开发与评价中的模型通用性考虑。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-09-28 DOI: 10.1080/10543406.2026.2729800

Ning Leng, Yichen Lu, Jane Fridlyand, Tiffany Tang, Ting Qi, Yingying Wei, Rodrigo Rojo Sanchez, Noah Simon, Gregory Alexander

{"title":"Model generalizability considerations in development and evaluation of SaMD.","authors":"Ning Leng, Yichen Lu, Jane Fridlyand, Tiffany Tang, Ting Qi, Yingying Wei, Rodrigo Rojo Sanchez, Noah Simon, Gregory Alexander","doi":"10.1080/10543406.2026.2729800","DOIUrl":"https://doi.org/10.1080/10543406.2026.2729800","url":null,"abstract":"Software as a Medical Device (SaMD) has been transforming medical practices by improving patient care with more precise and timely information. Key capabilities of SaMD are often powered by Artificial Intelligence (AI) algorithms. However, significant challenges arise in developing robust algorithms for SaMD, as these algorithms can perform well during development but poorly during pivotal validation studies. Due to the rapid advancement in medical research, data from new studies or real-world sources are likely to differ significantly from the legacy data used for development; with this, algorithms need to account for these potential data heterogeneity differences. This paper discusses the shortcomings of conventional cross-validation methods widely used in SaMD algorithm development and demonstrates model performance overestimation in the presence of data heterogeneity. To address this bias, we propose a simple and practical alternative: the leave-one-set-out (LOSO) cross-validation method. Additionally, we outline best practices for designing independent validation pivotal studies.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"1-13"},"PeriodicalIF":1.3,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149076767","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

Trial designs for assessing induction, maintenance and other treatment effects on a continuous endpoint. 在连续终点评估诱导、维持和其他治疗效果的试验设计。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-09-22 DOI: 10.1080/10543406.2026.2728047

Hui Quan, Zhixing Xu, Chunfu Qiu, Xun Chen

{"title":"Trial designs for assessing induction, maintenance and other treatment effects on a continuous endpoint.","authors":"Hui Quan, Zhixing Xu, Chunfu Qiu, Xun Chen","doi":"10.1080/10543406.2026.2728047","DOIUrl":"https://doi.org/10.1080/10543406.2026.2728047","url":null,"abstract":"A pivotal clinical trial designed to demonstrate the benefit of a new treatment for treating a chronic disease usually has multiple objectives of affirming that the treatment is an appropriate induction, maintenance and long-term therapy. To fulfill some of these and other objectives for the trial, various designs have been applied. They include the active treatment lead-in followed by randomized maintenance design, the randomized induction followed by re-randomized withdrawal maintenance design, and the treat-through design. A sequential parallel comparison design (SPCD) has also been proposed for a trial with a binary endpoint. This SPCD can be treated as a hybrid of the above three designs and has some additional advantages. As the model and method for data analysis heavily depend on the type of endpoint, in this paper, we extend the application of the SPCD to a trial with a continuous endpoint. To fully utilize all available data of the induction and maintenance phases for an overall treatment effect evaluation, we consider a weighted combination test for an overall treatment effect assessment which incorporates the correlations of the components. Further, approaches for handling missing data are discussed. Simulations are conducted to evaluate the performances of the methods, and an example is used to illustrate the application of the methods.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"1-20"},"PeriodicalIF":1.3,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149018870","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

Leveraging external control for accelerating development: A case study from cell gene therapy in Duchenne muscular dystrophy. 利用外部控制加速发展：细胞基因治疗杜氏肌营养不良的案例研究。

IF 1.3 4区医学

Journal of Biopharmaceutical Statistics Pub Date : 2026-09-20 DOI: 10.1080/10543406.2026.2729799

Huihua Li, Satrajit Roychoudhury, Heliang Shi, Balarama Gundapaneni, Margaret Gamalo

{"title":"Leveraging external control for accelerating development: A case study from cell gene therapy in Duchenne muscular dystrophy.","authors":"Huihua Li, Satrajit Roychoudhury, Heliang Shi, Balarama Gundapaneni, Margaret Gamalo","doi":"10.1080/10543406.2026.2729799","DOIUrl":"10.1080/10543406.2026.2729799","url":null,"abstract":"Cell and gene therapies (CGTs) hold transformative potential for rare genetic diseases by offering durable or even curative outcomes. However, the development of CGTs for conditions such as Duchenne muscular dystrophy (DMD) is particularly challenging due to small patient populations, high treatment cost, and ethical concerns surrounding the use of placebo control. These constraints make traditional randomized clinical trials challenging to conduct, necessitating alternative strategies like external control groups to support clinical development. However, the use of external controls requires careful data and methodological considerations to ensure valid and unbiased comparisons. Key elements include rigorous data selection, precise estimand definition, and statistical adjustments to address potential confounding and selection bias. Regulatory agencies emphasize the importance of rigorous methodologies to ensure credibility of treatment effect findings derived from external controls. To illustrate these principles, we present a case study of a single-arm DMD trial incorporating an external control. By evaluating data sources, assessing exchangeability, applying statistical adjustments, and conducting sensitivity analyses, the case study illustrates the potential for using external control in studies designed to rigorously explore the benefits of CGTs in rare genetic conditions.","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"1-18"},"PeriodicalIF":1.3,"publicationDate":"2026-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149013246","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