How to Add Baskets to an Ongoing Basket Trial with Information Borrowing
Libby Daniells, Pavel Mozgunov, Helen Barnett, Alun Bedding, Thomas, Jaki

TL;DR
This paper investigates methods for adding new baskets to ongoing basket trials using Bayesian information borrowing, proposing a calibration approach to improve decision robustness and analyzing the impact on trial power and error rates.
Contribution
It introduces a novel calibration method for decision criteria in basket trials and evaluates strategies for incorporating new baskets into ongoing studies with Bayesian borrowing.
Findings
Adding baskets with information borrowing improves power
Calibration reduces false positive rates
Borrowing can inflate error rates without proper calibration
Abstract
Basket trials test a single therapeutic treatment on several patient populations under one master protocol. A desirable adaptive design feature in these studies may be the incorporation of new baskets to an ongoing study. Limited basket sample sizes can cause issues in power and precision of treatment effect estimates which could be amplified in added baskets due to the shortened recruitment time. While various Bayesian information borrowing techniques have been introduced to tackle the issue of small sample sizes, the impact of including new baskets in the trial and into the borrowing model has yet to be investigated. We explore approaches for adding baskets to an ongoing trial under information borrowing and highlight when it is beneficial to add a basket compared to running a separate investigation for new baskets. We also propose a novel calibration approach for the decision…
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Taxonomy
TopicsSports Analytics and Performance · Mechanics and Biomechanics Studies
