Bayesian Basket Trial Design Accounting for Multiple Cutoffs of an Ambiguous Biomarker

Belay, Sheferaw Y.; Guo, Xiang; Lin, Xiao; Xia, Fan Dora; Xu, Jin

doi:10.1080/19466315.2022.2029555

Cited by 1 publication

(1 citation statement)

References 18 publications

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“…Other design methods incorporate information borrowing by pooling all tumor types if deemed homogeneous at the interim analysis (53) or by pooling within subgroups that are defined using a clustering algorithm (54), clustering of tumor types (55)(56)(57)(58), modeling patient-level data with a tree ensemble method (59), and using Bayesian commensurate priors (60). Baumann et al (61) propose conditions that can improve the behavior of posterior probabilities when applied to various Bayesian approaches for basket trials.…”

Section: Other Design Types and Methodsmentioning

confidence: 99%

Basket trials in oncology: a systematic review of practices and methods, comparative analysis of innovative methods, and an appraisal of a missed opportunity

Kasim,

Bean,

Hendriksen

et al. 2023

Front. Oncol.

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BackgroundBasket trials are increasingly used in oncology drug development for early signal detection, accelerated tumor-agnostic approvals, and prioritization of promising tumor types in selected patients with the same mutation or biomarker. Participants are grouped into so-called baskets according to tumor type, allowing investigators to identify tumors with promising responses to treatment for further study. However, it remains a question as to whether and how much the adoption of basket trial designs in oncology have translated into patient benefits, increased pace and scale of clinical development, and de-risking of downstream confirmatory trials.MethodsInnovation in basket trial design and analysis includes methods that borrow information across tumor types to increase the quality of statistical inference within each tumor type. We build on the existing systematic reviews of basket trials in oncology to discuss the current practices and landscape. We conceptually illustrate recent innovative methods for basket trials, with application to actual data from recently completed basket trials. We explore and discuss the extent to which innovative basket trials can be used to de-risk future trials through their ability to aid prioritization of promising tumor types for subsequent clinical development.ResultsWe found increasing adoption of basket trial design in oncology, but largely in the design of single-arm phase II trials with a very low adoption of innovative statistical methods. Furthermore, the current practice of basket trial design, which does not consider its impact on the clinical development plan, may lead to a missed opportunity in improving the probability of success of a future trial. Gating phase II with a phase Ib basket trial reduced the size of phase II trials, and losses in the probability of success as a result of not using innovative methods may not be recoverable by running a larger phase II trial.ConclusionInnovative basket trial methods can reduce the size of early phase clinical trials, with sustained improvement in the probability of success of the clinical development plan. We need to do more as a community to improve the adoption of these methods.

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