ArticleJournal of the Royal Statistical Society. Series C, Applied statistics2022
Bayesian modelling strategies for borrowing of information in randomised basket trials.
Article in Journal of the Royal Statistical Society. Series C, Applied statistics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Basket and umbrella trials in pediatric precision medicine: a systematic review of designs, opportunities, and challenges.BMC medical research methodology · 2026Pooled it
- Robust Bayesian hierarchical models for basket trials enabling joint evaluation of toxicity and efficacy.Statistical methods in medical research · 2026Article
- A Bayesian Adaptive Marker-Stratified Design for Phase II Clinical Trials Using Calibrated Spike-and-Slab priors.Statistics in biopharmaceutical research · 2026Article
- BIRTH: Bayesian integration of real-world data for trials with hybrid arms.BMC medical research methodology · 2026Article
- Augmented binary method for basket trials (ABBA).Statistical methods in medical research · 2026Article
- How to add baskets to an ongoing basket trial with information borrowing.Statistical methods in medical research · 2025Article
- Review article: Primer for clinical researchers on innovative trial designs for emergency medicine.Emergency medicine Australasia : EMA · 2025Review
- Adaptive Bayesian information borrowing methods for finding and optimizing subgroup-specific doses.Clinical trials (London, England) · 2024Review
- Bayesian modelling strategies for borrowing of information in randomised basket trials.Journal of the Royal Statistical Society. Series C, Applied statistics · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Basket trials are an innovative precision medicine clinical trial design evaluating a single targeted therapy across multiple diseases that share a common characteristic. To date, most basket trials have been conducted in early-phase oncology settings, for which several Bayesian methods permitting information sharing across subtrials have been proposed. With the increasing interest of implementing randomised basket trials, information borrowing could be exploited in two ways; considering the commensurability of either the treatment effects or the outcomes specific to each of the treatment groups between the subtrials. In this article, we extend a previous analysis model based on distributional discrepancy for borrowing over the subtrial treatment effects ('treatment effect borrowing', TEB) to borrowing over the subtrial groupwise responses ('treatment response borrowing', TRB). Simulation results demonstrate that both modelling strategies provide substantial gains over an approach with no borrowing. TRB outperforms TEB especially when subtrial sample sizes are small on all operational characteristics, while the latter has considerable gains in performance over TRB when subtrial sample sizes are large, or the treatment effects and groupwise mean responses are noticeably heterogeneous across subtrials. Further, we notice that TRB, and TEB can potentially lead to different conclusions in the analysis of real data.
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Registered trials
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