ArticleBiostatistics (Oxford, England)2022
Borrowing of information across patient subgroups in a basket trial based on distributional discrepancy.
Article in Biostatistics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Basket trials in oncology: a systematic review of practices and methods, comparative analysis of innovative methods, and an appraisal of a missed opportunity.Frontiers in oncology · 2023Pooled it
- Design and analysis of umbrella trials: Where do we stand?Frontiers in medicine · 2022Pooled it
- Bayesian sample size determination in basket trials borrowing information between subsets.Biostatistics (Oxford, England) · 2023Trial
- Practical basket design for binary outcomes with control of family-wise error rate.BMC medical research methodology · 2023Trial
- Robust Bayesian hierarchical models for basket trials enabling joint evaluation of toxicity and efficacy.Statistical methods in medical research · 2026Article
- Modern Clinical Trials: Seamless Designs and Master Protocols.Cancer medicine · 2026Review
- Bayesian sample size determination using robust commensurate priors with interpretable discrepancy weights.Statistical methods in medical research · 2026Article
- Covariate Adjustment in Basket Trials Borrowing Information Across Subgroups.Statistics in medicine · 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
- Incorporating historic information to further improve power when conducting Bayesian information borrowing in basket trials.Biostatistics (Oxford, England) · 2025Article
- Incorporating data from multiple ongoing trials for Bayesian two-stage phase II single-arm studies.Clinical trials (London, England) · 2025Article
- How to add baskets to an ongoing basket trial with information borrowing.Statistical methods in medical research · 2025Article
- 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
- Review
- Global mortality and readmission rates following COPD exacerbation-related hospitalisation: a meta-analysis of 65 945 individual patients.ERJ open research · 2024Article
- A comparison of Bayesian information borrowing methods in basket trials and a novel proposal of modified exchangeability-nonexchangeability method.Statistics in medicine · 2023Review
- Bayesian sample size determination using commensurate priors to leverage preexperimental data.Biometrics · 2023Article
- 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
2 authors.
Funding
Abstract
Basket trials have emerged as a new class of efficient approaches in oncology to evaluate a new treatment in several patient subgroups simultaneously. In this article, we extend the key ideas to disease areas outside of oncology, developing a robust Bayesian methodology for randomized, placebo-controlled basket trials with a continuous endpoint to enable borrowing of information across subtrials with similar treatment effects. After adjusting for covariates, information from a complementary subtrial can be represented into a commensurate prior for the parameter that underpins the subtrial under consideration. We propose using distributional discrepancy to characterize the commensurability between subtrials for appropriate borrowing of information through a spike-and-slab prior, which is placed on the prior precision factor. When the basket trial has at least three subtrials, commensurate priors for point-to-point borrowing are combined into a marginal predictive prior, according to the weights transformed from the pairwise discrepancy measures. In this way, only information from subtrial(s) with the most commensurate treatment effect is leveraged. The marginal predictive prior is updated to a robust posterior by the contemporary subtrial data to inform decision making. Operating characteristics of the proposed methodology are evaluated through simulations motivated by a real basket trial in chronic diseases. The proposed methodology has advantages compared to other selected Bayesian analysis models, for (i) identifying the most commensurate source of information and (ii) gauging the degree of borrowing from specific subtrials. Numerical results also suggest that our methodology can improve the precision of estimates and, potentially, the statistical power for hypothesis testing.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.