New clinical trial design borrowing information across patient subgroups based on fusion-penalized regression models Journal Article


Authors: Kerioui, M.; Iasonos, A.; Gönen, M.; Arfé, A.
Article Title: New clinical trial design borrowing information across patient subgroups based on fusion-penalized regression models
Abstract: In cancer research, basket trials aim to assess the efficacy of a drug using baskets, wherein patients are organized into subgroups according to their tumor type. In this context, using information borrowing strategy may increase the probability of detecting drug efficacy in active baskets, by shrinking together the estimates of the parameters characterizing the drug efficacy in baskets with similar drug activity. Here, we propose to use fusion-penalized logistic regression models to borrow information in the setting of a phase 2 single-arm basket trial with binary outcome. We describe our proposed strategy and assess its performance via a simulation study. We assessed the impact of heterogeneity in drug efficacy, prevalence of each tumor types and implementation of interim analyses on the operating characteristics of our proposed design. We compared our approach with two existing designs, relying on the specification of prior information in a Bayesian framework to borrow information across similar baskets. Notably, our approach performed well when the effect of the drug varied greatly across the baskets. Our approach offers several advantages, including limited implementation efforts and fast computation, which is essential when planning a new trial as such planning requires intensive simulation studies.
Keywords: oncology; tumors; phase-ii; regression; clinical trial design; open-label; cancers; variable selection; penalized; frequentist; regularization; basket trials; adaptive design
Journal Title: Statistical Methods in Medical Research
Volume: 33
Issue: 10
ISSN: 0962-2802
Publisher: Sage Publications  
Date Published: 2024-10-01
Start Page: 1718
End Page: 1730
Language: English
ACCESSION: WOS:001293163600001
DOI: 10.1177/09622802241267355
PROVIDER: wos
PUBMED: 39158499
PMCID: PMC12136055
Notes: Article -- Source: Wos
Altmetric
Citation Impact
BMJ Impact Analytics
MSK Authors
  1. Mithat Gonen
    1028 Gonen
  2. Alexia Elia Iasonos
    362 Iasonos
  3. Andrea Arfe
    12 Arfe
Related MSK Work