Pharmaceutical Statistics最新文献

Correction to "The Flaw of Averages: Bayes Factors as Posterior Means of the Likelihood Ratio".

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2025-03-03 DOI: 10.1002/pst.2441

引用次数: 0

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2025-03-01 Epub Date: 2024-11-21 DOI: 10.1002/pst.2452

Piero Quatto, Enrico Ripamonti, Donata Marasini

{"title":"Beyond the Fragility Index.","authors":"Piero Quatto, Enrico Ripamonti, Donata Marasini","doi":"10.1002/pst.2452","DOIUrl":"10.1002/pst.2452","url":null,"abstract":"The results of randomized clinical trials (RCTs) are frequently assessed with the fragility index (FI). Although the information provided by FI may supplement the p value, this indicator presents intrinsic weaknesses and shortcomings. In this article, we establish an analysis of fragility within a broader framework so that it can reliably complement the information provided by the p value. This perspective is named the analysis of strength. We first propose a new strength index (SI), which can be adopted in normal distribution settings. This measure can be obtained for both significance and nonsignificance and is straightforward to calculate, thus presenting compelling advantages over FI, starting from the presence of a threshold. The case of time-to-event outcomes is also addressed. Then, beyond the p value, we develop the analysis of strength using likelihood ratios from Royall's statistical evidence viewpoint. A new R package is provided for performing strength calculations, and a simulation study is conducted to explore the behavior of SI and the likelihood-based indicator empirically across different settings. The newly proposed analysis of strength is applied in the assessment of the results of three recent trials involving the treatment of COVID-19.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":"e2452"},"PeriodicalIF":1.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11889990/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142687990","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

Subgroup Identification Based on Quantitative Objectives. 基于量化目标的分组识别。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2025-03-01 Epub Date: 2024-11-17 DOI: 10.1002/pst.2455

Yan Sun, A S Hedayat

引用次数: 0

A Phase I Dose-Finding Design Incorporating Intra-Patient Dose Escalation. 纳入患者内剂量递增的I期剂量寻找设计。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2025-03-01 Epub Date: 2024-12-25 DOI: 10.1002/pst.2461

Beibei Guo, Suyu Liu

{"title":"A Phase I Dose-Finding Design Incorporating Intra-Patient Dose Escalation.","authors":"Beibei Guo, Suyu Liu","doi":"10.1002/pst.2461","DOIUrl":"10.1002/pst.2461","url":null,"abstract":"Conventional Phase I trial designs assign a single dose to each patient, necessitating a minimum number of patients per dose to reliably identify the maximum tolerated dose (MTD). However, in many clinical trials, such as those involving pediatric patients or patients with rare cancers, recruiting an adequate number of patients can pose challenges, limiting the applicability of standard trial designs. To address this challenge, we propose a new Phase I dose-finding design, denoted as IP-CRM, that integrates intra-patient dose escalation with the continual reassessment method (CRM). In the IP-CRM design, intra-patient dose escalation is allowed, guided by both individual patients' toxicity outcomes and accumulated data across patients, and the starting dose for each cohort of patients is adaptively updated. We further extend the IP-CRM design to address carryover effects and/or intra-patient correlations. Due to the potential for each patient to contribute multiple data points at varying doses owing to intra-patient dose escalation, the IP-CRM design offers the advantage of determining the MTD with a considerably reduced sample size compared to standard Phase I dose-finding designs. Simulation studies show that our IP-CRM design can efficiently reduce sample size while concurrently enhancing the probability of identifying the MTD when compared with standard CRM designs and the 3 + 3 design.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":"e2461"},"PeriodicalIF":1.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142896374","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 Bayesian Hybrid Design With Borrowing From Historical Study. 借鉴历史研究的贝叶斯混合设计。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2025-03-01 Epub Date: 2024-12-27 DOI: 10.1002/pst.2466

Zhaohua Lu, John Toso, Girma Ayele, Philip He

{"title":"A Bayesian Hybrid Design With Borrowing From Historical Study.","authors":"Zhaohua Lu, John Toso, Girma Ayele, Philip He","doi":"10.1002/pst.2466","DOIUrl":"10.1002/pst.2466","url":null,"abstract":"In early phase drug development of combination therapy, the primary objective is to preliminarily assess whether there is additive activity from a novel agent when combined with an established monotherapy. Due to potential feasibility issues for conducting a large randomized study, uncontrolled single-arm trials have been the mainstream approach in cancer clinical trials. However, such trials often present significant challenges in deciding whether to proceed to the next phase of development due to the lack of randomization in traditional two-arm trials. A hybrid design, leveraging data from a completed historical clinical study of the monotherapy, offers a valuable option to enhance study efficiency and improve informed decision-making. Compared to traditional single-arm designs, the hybrid design may significantly enhance power by borrowing external information, enabling a more robust assessment of activity. The primary challenge of hybrid design lies in handling information borrowing. We introduce a Bayesian dynamic power prior (DPP) framework with three components of controlling amount of dynamic borrowing. The framework offers flexible study design options with explicit interpretation of borrowing, allowing customization according to specific needs. Furthermore, the posterior distribution in the proposed framework has a closed form, offering significant advantages in computational efficiency. The proposed framework's utility is demonstrated through simulations and a case study.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":"e2466"},"PeriodicalIF":1.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142896437","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

Confidence Intervals for the Risk Difference Between Secondary and Primary Infection Based on the Method of Variance Estimates Recovery. 基于方差估计方法的继发感染和原发感染风险差异的置信区间。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2025-03-01 Epub Date: 2024-12-09 DOI: 10.1002/pst.2458

Chao Chen, Yuanzhen Li, Qitong Wei, Zhigang Huang, Yanting Chen

引用次数: 0

Success and Futility Criteria for Accelerated Approval of Oncology Drugs.

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2025-03-01 DOI: 10.1002/pst.70004

Dong Xi, Jiangtao Gou

{"title":"Success and Futility Criteria for Accelerated Approval of Oncology Drugs.","authors":"Dong Xi, Jiangtao Gou","doi":"10.1002/pst.70004","DOIUrl":"https://doi.org/10.1002/pst.70004","url":null,"abstract":"Project FrontRunner encourages development of cancer drugs for advanced or metastatic disease in an earlier clinical setting by promoting regulatory approaches such as the accelerated approval pathway. The FDA draft guideline proposes a one-trial approach to combine accelerated approval and regular approval in a single trial to maintain efficiency. This article describes our idea of controlling Type I error for accelerated and regular approvals in the one-trial approach. We introduce success and futility boundaries on p-values for accelerated approval to create three outcomes: success, RA, and futility. If success, accelerated approval can be claimed for; for RA, only regular approval (RA) is considered; if futility, we stop the trial early for futility. For both success and RA, the endpoint for regular approval can be tested with no penalty on its significance level. The proposed approach is robust to all possible values of correlation between test statistics of the endpoints for accelerated and regular approvals. This framework is flexible to allow clinical trial teams to tailor success and futility boundaries to meet clinical and regulatory needs, while maintaining the overall Type I error control in the strong sense.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":"24 2","pages":"e70004"},"PeriodicalIF":1.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143567868","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 Response Adaptive Randomization for Randomized Clinical Trials With Continuous Outcomes: The Role of Covariate Adjustment. 连续结果随机临床试验的贝叶斯反应自适应随机化：协变量调整的作用》。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2025-03-01 Epub Date: 2024-10-24 DOI: 10.1002/pst.2443

Vahan Aslanyan, Trevor Pickering, Michelle Nuño, Lindsay A Renfro, Judy Pa, Wendy J Mack

{"title":"Bayesian Response Adaptive Randomization for Randomized Clinical Trials With Continuous Outcomes: The Role of Covariate Adjustment.","authors":"Vahan Aslanyan, Trevor Pickering, Michelle Nuño, Lindsay A Renfro, Judy Pa, Wendy J Mack","doi":"10.1002/pst.2443","DOIUrl":"10.1002/pst.2443","url":null,"abstract":"Study designs incorporate interim analyses to allow for modifications to the trial design. These analyses may aid decisions regarding sample size, futility, and safety. Furthermore, they may provide evidence about potential differences between treatment arms. Bayesian response adaptive randomization (RAR) skews allocation proportions such that fewer participants are assigned to the inferior treatments. However, these allocation changes may introduce covariate imbalances. We discuss two versions of Bayesian RAR (with and without covariate adjustment for a binary covariate) for continuous outcomes analyzed using change scores and repeated measures, while considering either regression or mixed models for interim analysis modeling. Through simulation studies, we show that RAR (both versions) allocates more participants to better treatments compared to equal randomization, while reducing potential covariate imbalances. We also show that dynamic allocation using mixed models for repeated measures yields a smaller allocation proportion variance while having a similar covariate imbalance as regression models. Additionally, covariate imbalance was smallest for methods using covariate-adjusted RAR (CARA) in scenarios with small sample sizes and covariate prevalence less than 0.3. Covariate imbalance did not differ between RAR and CARA in simulations with larger sample sizes and higher covariate prevalence. We thus recommend a CARA approach for small pilot/exploratory studies for the identification of candidate treatments for further confirmatory studies.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":"e2443"},"PeriodicalIF":1.3,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142505735","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

Treatment Effect Measures Under Nonproportional Hazards. 非比例危害下的治疗效果测量。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2025-03-01 Epub Date: 2024-10-27 DOI: 10.1002/pst.2449

Dan Jackson, Michael Sweeting, Rose Baker

引用次数: 0

Pre-Posterior Distributions in Drug Development and Their Properties. 药物开发中的前后分布及其特性。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2025-03-01 Epub Date: 2024-11-25 DOI: 10.1002/pst.2450

Andrew P Grieve

引用次数: 0