ArticleClinical trials (London, England)2019
Variance prior specification for a basket trial design using Bayesian hierarchical modeling.
Article in Clinical trials (London, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Practical basket design for binary outcomes with control of family-wise error rate.BMC medical research methodology · 2023Trial
- Extrapolation of Time-to-Event Survival Outcomes of Histology-Independent Therapies Using a Bayesian Hierarchical Model.Medical decision making : an international journal of the Society for Medical Decision Making · 2026Article
- Covariate Adjustment in Basket Trials Borrowing Information Across Subgroups.Statistics in medicine · 2026Article
- Augmented binary method for basket trials (ABBA).Statistical methods in medical research · 2026Article
- Incorporating historic information to further improve power when conducting Bayesian information borrowing in basket trials.Biostatistics (Oxford, England) · 2025Article
- Enhancing interpretability for Bayesian basket trial designs by effective sample size.BMC medical research methodology · 2025Article
- New clinical trial design borrowing information across patient subgroups based on fusion-penalized regression models.Statistical methods in medical research · 2024Article
- Adaptive Bayesian information borrowing methods for finding and optimizing subgroup-specific doses.Clinical trials (London, England) · 2024Review
- A generalized calibrated Bayesian hierarchical modeling approach to basket trials with multiple endpoints.Biometrical journal. Biometrische Zeitschrift · 2024Article
- A comparison of Bayesian information borrowing methods in basket trials and a novel proposal of modified exchangeability-nonexchangeability method.Statistics in medicine · 2023Review
- Evolution of Phase II Oncology Trial Design: from Single Arm to Master Protocol.Therapeutic innovation & regulatory science · 2023Review
- Basket Trials: Review of Current Practice and Innovations for Future Trials.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2022Review
- Subgroup-specific dose finding for phase I-II trials using Bayesian clustering.Statistics in medicine · 2022Article
- Borrowing of information across patient subgroups in a basket trial based on distributional discrepancy.Biostatistics (Oxford, England) · 2022Article
- Exploring Heterogeneity in Histology-Independent Technologies and the Implications for Cost-Effectiveness.Medical decision making : an international journal of the Society for Medical Decision Making · 2021Article
- Reporting of master protocols towards a standardized approach: A systematic review.Contemporary clinical trials communications · 2019Article
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4 authors.
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Abstract
backgroundIn the era of targeted therapies, clinical trials in oncology are rapidly evolving, wherein patients from multiple diseases are now enrolled and treated according to their genomic mutation(s). In such trials, known as basket trials, the different disease cohorts form the different baskets for inference. Several approaches have been proposed in the literature to efficiently use information from all baskets while simultaneously screening to find individual baskets where the drug works. Most proposed methods are developed in a Bayesian paradigm that requires specifying a prior distribution for a variance parameter, which controls the degree to which information is shared across baskets.
methodsA common approach used to capture the correlated binary endpoints across baskets is Bayesian hierarchical modeling. We evaluate a Bayesian adaptive design in the context of a non-randomized basket trial and investigate three popular prior specifications: an inverse-gamma prior on the basket-level variance, a uniform prior and half-t prior on the basket-level standard deviation.
resultsFrom our simulation study, we can see that the inverse-gamma prior is highly sensitive to the input hyperparameters. When the prior mean value of the variance parameter is set to be near zero
conclusionBased on the simulation results, we recommend that those involved in designing basket trials that implement hierarchical modeling avoid using a prior distribution that places a majority of the density mass near zero for the variance parameter. Priors with this property force the model to share information regardless of the true efficacy configuration of the baskets. Many commonly used inverse-gamma prior specifications have this undesirable property. We recommend to instead consider the more robust uniform prior or half-t prior on the standard deviation.
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