Pharmaceutical Statistics最新文献_第5页

Unblinded by the Night: Predictive Power for Complex Bayesian Adaptive Trials When Sight Privileges Vary. 夜不能寐：视觉特权变化时复杂贝叶斯自适应试验的预测能力。

IF 1.5 4区医学

Pharmaceutical Statistics Pub Date : 2026-03-01 DOI: 10.1002/pst.70086

Byron J Gajewski, Jonathan Beall, Kaustubh Nimkar, Renee' H Martin

{"title":"Unblinded by the Night: Predictive Power for Complex Bayesian Adaptive Trials When Sight Privileges Vary.","authors":"Byron J Gajewski, Jonathan Beall, Kaustubh Nimkar, Renee' H Martin","doi":"10.1002/pst.70086","DOIUrl":"10.1002/pst.70086","url":null,"abstract":"Well-controlled clinical trials employ careful processes to reduce bias, often blinding investigators and sponsors to prevent knowledge of study outcomes and potential operational bias. Quality assurance of outcomes is also ensured through designation of unblinded data managers and statisticians, so that complex adaptive designs with multiple interim analyses can be executed. Our approach addresses potential ad-hoc requests by the Data and Safety Monitoring Board (DSMB) for monitoring safety, efficacy, and ethical oversight. A novel approach utilizing current trial data is proposed to predict trial outcomes for blinded decision-makers without unblinding those that should stay blinded. Bayesian predictive power, a trial prediction method, is employed and illustrated on simulated data. This study presents an approach for presenting updated Bayesian predictive power in complex adaptive designs, exemplified by the Hyperbaric Oxygen Brain Injury Treatment (HOBIT) trial. Simulation examples motivated from the trial demonstrate the utility of Bayesian predictive power in predicting trial outcomes and sample size distribution, aiding in resource allocation and decision-making with different reports for blinded and unblinded teams. Bayesian predictive power calculations offer valuable insights into future trial behavior for both blinded and unblinded groups, aiding in guidance during trial conduction. The approach outlined in this short communication can be applied to various trial designs.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":"25 2","pages":"e70086"},"PeriodicalIF":1.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13002123/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147481322","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

Handling Missing Data in Participants with Baseline but No Post-Baseline Data. 处理有基线但没有基线后数据的参与者的缺失数据。

IF 1.5 4区医学

Pharmaceutical Statistics Pub Date : 2026-03-01 DOI: 10.1002/pst.70076

Craig Mallinckrodt, Ilya Lipkovich, Samuel Dickson, Suzanne Hendrix, Geert Molenberghs

{"title":"Handling Missing Data in Participants with Baseline but No Post-Baseline Data.","authors":"Craig Mallinckrodt, Ilya Lipkovich, Samuel Dickson, Suzanne Hendrix, Geert Molenberghs","doi":"10.1002/pst.70076","DOIUrl":"10.1002/pst.70076","url":null,"abstract":"Participants who are randomized to treatment but have no post-baseline data pose a unique challenge. These participants need to be included to preserve randomization. Because there is no information about the outcome or the intercurrent event(s) that led to missing data, an estimand of interest, and the focus of this study, is a hypothetical strategy to estimate what would have been observed if participants had not discontinued. Various imputation-based and likelihood-based analyses were compared in simulated and real clinical trial data. Models that used baseline as a covariate or constrained baseline values to be equal yielded similar results and had greater power than an unconstrained analysis that fit baseline as a response. Assigning change to the first post-baseline visit as 0 and applying an analysis with baseline as a covariate controlled Type I error at the nominal level and had power equal to or greater than other methods. Treatment contrasts were not biased when the reason for missing all post-baseline data was random or treatment related. Within-group bias occurred with outcome-related missingness of all post-baseline data, but the bias was nearly equal in the two arms, leading to unbiased treatment contrasts. Bias occurred when missing all post-baseline data was related to treatment and outcome. Given the idiosyncratic nature of clinical trials, no universally best analytic approach exists for dealing with participants that have a baseline but no post-baseline data. Analysts can choose among the methods to tailor an approach to the situation at hand.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":"25 2","pages":"e70076"},"PeriodicalIF":1.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146181538","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

Multiplicity Adjustment Methods for a Three-Way Crossover Bioequivalence Study. 三种交叉生物等效性研究的多重调整方法。

IF 1.5 4区医学

Pharmaceutical Statistics Pub Date : 2026-03-01 DOI: 10.1002/pst.70083

David Hinds, Stella Grosser, Wanjie Sun

{"title":"Multiplicity Adjustment Methods for a Three-Way Crossover Bioequivalence Study.","authors":"David Hinds, Stella Grosser, Wanjie Sun","doi":"10.1002/pst.70083","DOIUrl":"10.1002/pst.70083","url":null,"abstract":"For generic drugs, a three-way crossover bioequivalence (BE) study is often used to compare two generic (T) formulations against the common brand-name (R) formulation. Adjustment for multiplicity in equivalence testing, however, is little researched. The new ICH M13A guidance mentioned multiplicity control for equivalence but did not recommend any specific methods. In this paper, we evaluate the applicability of traditional multiplicity adjustment methods in equivalence testing. We propose three revised methods (Bonferroni, Holm, and Hochberg) which are applied on not only p-values but also the more commonly used confidence intervals in equivalence testing. We also apply the 'two-at-a-time' rule as recommended by regulatory agencies and incorporate the correlation among test statistics in simulation. All of these are advances compared to current multiplicity control methods for equivalence. Simulation shows that our proposed methods in a three-way crossover study greatly improve power and reduce needed sample size compared to conducting two two-way crossover studies, control the family-wise error rate at a desired level, and only slightly increase the required sample size compared to no alpha adjustment. Therefore, we recommend our revised Bonferroni, Holm, or Hochberg method in a three-way crossover design when assessing the BE of 2 Ts to 1 R.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":"25 2","pages":"e70083"},"PeriodicalIF":1.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147434804","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

Informing the Borrowing Process for Dose-Finding Trials by Estimating the Similarity Between Population-Specific Dose-Toxicity Curves. 通过估计人群特异性剂量-毒性曲线之间的相似性，为剂量寻找试验的借用过程提供信息。

IF 1.4 4区医学

Pharmaceutical Statistics Pub Date : 2026-01-01 DOI: 10.1002/pst.70067

Dario Zocholl, Heiko Götte, Christina Habermehl, Burak Kürsad Günhan

{"title":"Informing the Borrowing Process for Dose-Finding Trials by Estimating the Similarity Between Population-Specific Dose-Toxicity Curves.","authors":"Dario Zocholl, Heiko Götte, Christina Habermehl, Burak Kürsad Günhan","doi":"10.1002/pst.70067","DOIUrl":"10.1002/pst.70067","url":null,"abstract":"The conduct of dose-finding trials can be specifically challenging in small populations, for example, in pediatric settings. Recently, research has shown that Bayesian borrowing from adult trials combined with appropriately robust prior distributions enables the conduct of pediatric dose-finding trials with very small sample sizes. However, the appropriate degree of borrowing remains a subjective choice, relying on default methods or expert opinion. This paper proposes an approach to empirically determine the degree of borrowing based on a meta-analysis of the similarity between population-specific dose-toxicity curves of other biologically similar compounds. Focusing on the pediatric use case, the approach may be applicable to any dose-finding trial with information borrowing from another population. With the ExNex and a hierarchical model, two popular statistical modeling approaches are applied. The estimated degree of similarity is then translated into the statistical model for the dose-finding algorithm using either variance inflation or robust mixture prior distributions. The performance of each combination of statistical model approaches is investigated in a simulation study. The results with mixture priors are promising for the application of the proposed methods, especially with many (20) compounds, while variance inflation models require additional fine-tuning and seem to be less robust. With fewer (3 or 7) compounds, our proposed methods are either in line with robust priors that ignore the data from other compounds or are slightly better. We further provide a case study analyzing real dose-finding data from 6 compounds with our models, demonstrating applicability in real-world situations. For clinical trials teams, the decision for or against the proposed approach might be connected to the efforts in terms of time and cost to receive the external data.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":"25 1","pages":"e70067"},"PeriodicalIF":1.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12742552/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145794326","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

Prospectively Specified Adaptive Bayesian Borrowing: Considerations, Methodologies, and Implementations. 前瞻性指定自适应贝叶斯借用：考虑、方法和实现。

IF 1.4 4区医学

Pharmaceutical Statistics Pub Date : 2026-01-01 DOI: 10.1002/pst.70051

Saurabh Mukhopadhyay, Yujie Zhao, Xiaotian Chen, Anthony J Cannon, Julie Adams, Martina Kron

{"title":"Prospectively Specified Adaptive Bayesian Borrowing: Considerations, Methodologies, and Implementations.","authors":"Saurabh Mukhopadhyay, Yujie Zhao, Xiaotian Chen, Anthony J Cannon, Julie Adams, Martina Kron","doi":"10.1002/pst.70051","DOIUrl":"10.1002/pst.70051","url":null,"abstract":"In clinical research, it is increasingly difficult to conduct fully powered and well-balanced randomized controlled trials, particularly when studying rare or devastating diseases and pediatric patients. While Bayesian methodologies are very useful for leveraging historical control data to meet some of these challenges, many practical and statistical concerns emerge when prospectively specifying a design to implement Bayesian methods. In this article, we discuss these concerns and propose novel methods to ensure statistical rigor when applying Bayesian methodology. A novel adaptive Bayesian borrowing (ABB) method proposed here borrows from historical control data to increase the precision of the control arm based on the observed congruence of the historical and current data. The method would also enable an adaptive increase of sample size to accommodate accumulating information. We demonstrate that this approach can be prospectively specified and provides a statistically rigorous and transparent inference while mitigating the risk of potential conflict between historical and current control data, as well as misspecifications of variability in the endpoints.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":"25 1","pages":"e70051"},"PeriodicalIF":1.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145715410","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

Selection of Quantitative Decision-Making Criteria Using Weighted Decision Error Rates. 基于加权决策错误率的定量决策准则选择。

IF 1.4 4区医学

Pharmaceutical Statistics Pub Date : 2026-01-01 DOI: 10.1002/pst.70057

Daniel J Bratton

{"title":"Selection of Quantitative Decision-Making Criteria Using Weighted Decision Error Rates.","authors":"Daniel J Bratton","doi":"10.1002/pst.70057","DOIUrl":"10.1002/pst.70057","url":null,"abstract":"Quantitative decision-making frameworks provide objective criteria for advancing a drug development program. Within this process, two types of decision error can occur: proceeding to the next phase and failing (incorrect go) or not proceeding when success would have been achieved (incorrect no-go). This paper discusses strategies to reduce these errors in the context of a phase 2/3 development programme by selecting an optimal go threshold, which minimises the combined risk of an incorrect go or incorrect no-go decision. If the importance of these two errors differs, we propose the use of a weighted decision error rate (WDER) to select the optimal go threshold. We explore the influence of the choice of weighting and the prior beliefs about the drug efficacy on the optimal decision rule and demonstrate how the WDER can guide phase 2 sample size determination, often resulting in a larger sample size paired with a more stringent go threshold for efficiency. We advocate for a new definition of the probability of success in phase 2, emphasizing that it should reflect the probability of making the correct decision about proceeding, rather than just the probability of advancing to phase 3. This approach ensures that decision-making in drug development is both robust and tailored, enhancing the risk-benefit assessment for each phase transition.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":"25 1","pages":"e70057"},"PeriodicalIF":1.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145669181","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 Weighted Geometric Average Hazard Ratio Based Sample Size Formula for Non-Proportional Hazards and Its Application to a Smoothed Piecewise Model in Cancer Immunotherapy Trial Design. 基于加权几何平均风险比的非比例风险样本量公式及其在肿瘤免疫治疗试验设计平滑分段模型中的应用。

IF 1.4 4区医学

Pharmaceutical Statistics Pub Date : 2026-01-01 DOI: 10.1002/pst.70058

Qingyang Zhang, Zixing Wang, Allen Xue, James Whitmore

{"title":"A Weighted Geometric Average Hazard Ratio Based Sample Size Formula for Non-Proportional Hazards and Its Application to a Smoothed Piecewise Model in Cancer Immunotherapy Trial Design.","authors":"Qingyang Zhang, Zixing Wang, Allen Xue, James Whitmore","doi":"10.1002/pst.70058","DOIUrl":"10.1002/pst.70058","url":null,"abstract":"Cancer immunotherapy trials often present unique challenges for time-to-event data modeling and analysis due to heterogeneous treatment effects across time or subgroups. A few known scenarios are delayed treatment effects and cure rates, where survival and hazard functions often take complex shapes. Sophisticated survival models like piecewise model are commonly used to capture the shapes of the functions. However, the time of hazard transition for individual patients varies, making it necessary to model it as a latent random variable. In this study, we propose a smoothed piecewise model to account for the random hazard transition time, based on the linear relationship between hazard function and the distribution function of the individual transition time within the smoothing window. We then develop the weighted geometric average hazard ratio (wgAHR) to estimate sample size and power based on the non-centrality parameter of the weighted log-rank statistics under non-proportional hazard (non-PH). We demonstrate that the wgAHR is not only directly linked to the sample size formula, but can also be interpreted as a measure of treatment effect, even when the proportional hazard assumption is violated. Additionally, we provide maxCombo, a combination of weighted log-rank statistics, for robust testing across different non-proportional hazard scenarios. Simulation studies and real trial examples illustrate the performance and robustness of the wgAHR based method in power and sample size estimation in cancer immunotherapy trials.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":"25 1","pages":"e70058"},"PeriodicalIF":1.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145637561","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 Validation of Analytical Procedures Under ICH Q2(R2). ICH Q2（R2）中分析方法验证的置信区间。

IF 1.4 4区医学

Pharmaceutical Statistics Pub Date : 2026-01-01 DOI: 10.1002/pst.70055

Paul Faya, Chad N Wolfe, Adam P Rauk

引用次数: 0

Simulation-Based Bayesian Predictive Probability of Success for Interim Monitoring of Clinical Trials With Competing Event Data: Two Case Studies. 基于模拟的贝叶斯预测成功概率对具有竞争事件数据的临床试验中期监测：两个案例研究。

IF 1.4 4区医学

Pharmaceutical Statistics Pub Date : 2026-01-01 DOI: 10.1002/pst.70050

Chiara Micoli, Alessio Crippa, Jason T Connor, Martin Eklund, Andrea Discacciati

{"title":"Simulation-Based Bayesian Predictive Probability of Success for Interim Monitoring of Clinical Trials With Competing Event Data: Two Case Studies.","authors":"Chiara Micoli, Alessio Crippa, Jason T Connor, Martin Eklund, Andrea Discacciati","doi":"10.1002/pst.70050","DOIUrl":"10.1002/pst.70050","url":null,"abstract":"Bayesian predictive probabilities of success (PPoS) use interim trial data to calculate the probability of trial success. These quantities can be used to optimise trial size or to stop for futility. In this paper, we describe a simulation-based approach to compute the PPoS for clinical trials with competing event data, for which no specific methodology is currently available. The proposed procedure hinges on modelling the joint distribution of time to event and event type by specifying Bayesian models for the cause-specific hazards of all event types. This allows the prediction of outcome data at the conclusion of the trial. The PPoS is obtained by numerically averaging the probability of success evaluated at fixed parameter values over the posterior distribution of the parameters. Our work is motivated by two randomised clinical trials: the I-SPY COVID phase II trial for the treatment of severe COVID-19 (NCT04488081) and the STHLM3 prostate cancer diagnostic trial (ISRCTN84445406), both of which are characterised by competing event data. We present different modelling alternatives for the joint distribution of time to event and event type and show how the choice of the prior distributions can be used to assess the PPoS under different scenarios. The role of the PPoS analyses in the decision-making process for these two trials is also discussed.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":"25 1","pages":"e70050"},"PeriodicalIF":1.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12646369/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145605462","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

A Tree-Based Scan Statistic for Detecting Signals of Drug-Drug Interactions in Spontaneous Reporting Databases. 自发报告数据库中检测药物-药物相互作用信号的基于树的扫描统计。

IF 1.4 4区医学

Pharmaceutical Statistics Pub Date : 2026-01-01 DOI: 10.1002/pst.70068

Seok-Jae Heo, Inkyung Jung

{"title":"A Tree-Based Scan Statistic for Detecting Signals of Drug-Drug Interactions in Spontaneous Reporting Databases.","authors":"Seok-Jae Heo, Inkyung Jung","doi":"10.1002/pst.70068","DOIUrl":"10.1002/pst.70068","url":null,"abstract":"The concomitant use of multiple drugs increases the risk of adverse events (AEs) due to drug-drug interactions (DDIs), which remain challenging to identify since clinical trials primarily focus on individual drugs, necessitating postmarket safety monitoring through spontaneous reporting systems. Although several statistical methodologies have been proposed to detect DDI signals with disproportionately high reporting rates, existing methods inadequately account for the hierarchical structure of AEs and potential reporting bias. To address these limitations, we developed a statistical methodology that incorporates the hierarchical structure of AEs using tree-based scan statistics while mitigating reporting bias by assuming DDIs follow a multiplicative interaction model. In simulation studies, our proposed method effectively controlled type I error rate at prespecified significance levels across all simulation scenarios and demonstrated consistent performance in power, sensitivity, and false discovery rate, even with reporting bias present. This novel tree-based scan statistic methodology for detecting DDI signals that accounts for both hierarchical AE structure and potential reporting bias can serve as a valuable tool for postmarket drug safety surveillance.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":"25 1","pages":"e70068"},"PeriodicalIF":1.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145768762","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