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Basket trials are increasingly used for the simultaneous evaluation of a new treatment in various patient subgroups under one overarching protocol. We propose a Bayesian approach to sample size determination in basket trials that permit…

Methodology · Statistics 2022-09-02 Haiyan Zheng , Michael J. Grayling , Pavel Mozgunov , Thomas Jaki , James M. S. Wason

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 paper, we extend the key ideas to disease areas outside of oncology, developing a…

Methodology · Statistics 2020-06-01 Haiyan Zheng , James M. S. Wason

Research in oncology has changed the focus from histological properties of tumors in a specific organ to a specific genomic aberration potentially shared by multiple cancer types. This motivates the basket trial, which assesses the efficacy…

Applications · Statistics 2020-02-11 Jin Jin , Marie-Karelle Riviere , Xiaodong Luo , Yingwen Dong

In recent years, basket trials, which allow the evaluation of an experimental therapy across multiple tumor types within a single protocol, have gained prominence in early-phase oncology development. Unlike traditional trials, which…

Applications · Statistics 2025-07-18 Haiming Zhou , Rex Shen , Sutan Wu , Philip He

Precision medicine has led to a paradigm shift allowing the development of targeted drugs that are agnostic to the tumor location. In this context, basket trials aim to identify which tumor types - or baskets - would benefit from the…

Methodology · Statistics 2026-01-05 Marcio A. Diniz , Hulya Kocyigit , Erin Moshier , Madhu Mazumdar , Deukwoo Kwon

Basket trials examine the efficacy of an intervention in multiple patient subgroups simultaneously. The division into subgroups, called baskets, is based on matching medical characteristics, which may result in small sample sizes within…

Methodology · Statistics 2024-09-17 Sabrina Schmitt , Lukas Baumann

Basket trials can efficiently evaluate a single treatment across multiple diseases with a common shared target. Prior methods for randomized basket trials required baskets to have the same sample and effect sizes. To that end, we developed…

Methodology · Statistics 2024-11-22 Sahil S. Patel , Desmond Zeya Chen , David Castle , Clement Ma

Therapeutic advancements in oncology have shifted towards targeted therapy based on genomic aberrations. This necessitates innovative statistical approaches in clinical trials, particularly in master protocol studies. Basket trials, a type…

Applications · Statistics 2025-02-12 Antonios Daletzakis , Rutger van den Bor , Vincent van der Noort , Kit CB Roes

We propose an information borrowing strategy for the design and monitoring of phase II basket trials based on the local multisource exchangeability assumption between baskets (disease types). In our proposed local-MEM framework, information…

Methodology · Statistics 2022-07-13 Yilin Liu , Michael Kane , Denise Esserman , Ondrej Blaha , Daniel Zelterman , Wei Wei

Basket designs are prospective clinical trials that are devised with the hypothesis that the presence of selected molecular features determine a patient's subsequent response to a particular "targeted" treatment strategy. Basket trials are…

Computation · Statistics 2019-08-05 Michael J. Kane , Nan Chen , Alexander M. Kaizer , Xun Jiang , H. Amy Xia , Brian P. Hobbs

Adaptive enrichment trials aim to identify and recruit participants most likely to benefit from treatment based on evolving biomarker evidence, with the goal of informing individualized treatment recommendations. Bayesian methods are well…

Methodology · Statistics 2026-03-11 Lara Maleyeff , Shirin Golchi , Erica E. M. Moodie

Recent substantial advances of molecular targeted oncology drug development is requiring new paradigms for early-phase clinical trial methodologies to enable us to evaluate efficacy of several subtypes simultaneously and efficiently. The…

Methodology · Statistics 2023-02-17 Satoshi Hattori , Satoshi Morita

Bayesian clinical trials can benefit of available historical information through the elicitation of informative prior distributions. Concerns are however often raised about the potential for prior-data conflict and the impact of Bayes test…

Methodology · Statistics 2022-12-01 Silvia Calderazzo , Annette Kopp-Schneider

With the advancement of precision medicine there is an increasing need for design and analysis methods in clinical trials with the objective of investigating effect heterogeneity and estimating subgroup effects. As this requires precise…

Methodology · Statistics 2026-03-12 Shirin Golchi , Satoshi Morita

In several clinical areas, traditional clinical trials often use a responder outcome, a composite endpoint that involves dichotomising a continuous measure. An augmented binary method that improves power whilst retaining the original…

Methodology · Statistics 2024-08-19 Svetlana Cherlin , James M S Wason

External data borrowing in clinical trial designs has increased in recent years. This is accomplished in the Bayesian framework by specifying informative prior distributions. To mitigate the impact of potential inconsistency (bias) between…

Basket trial designs are a type of master protocol in which the same therapy is tested in several strata of the patient cohort. Many basket trial designs implement borrowing mechanisms. These allow sharing information between similar strata…

Methodology · Statistics 2024-05-20 Lukas D Sauer , Alexander Ritz , Meinhard Kieser

In situations where it is difficult to enroll patients in randomized controlled trials, external data can improve efficiency and feasibility. In such cases, adaptive trial designs could be used to decrease enrollment in the control arm of…

Methodology · Statistics 2020-10-02 Brian D. Segal , W. Katherine Tan

There is growing interest in Bayesian clinical trial designs with informative prior distributions, e.g. for extrapolation of adult data to pediatrics, or use of external controls. While the classical type I error is commonly used to…

Methodology · Statistics 2023-09-06 Nicky Best , Maxine Ajimi , Beat Neuenschwander , Gaelle Saint-Hilary , Simon Wandel

Boosting algorithms to simultaneously estimate and select predictor effects in statistical models have gained substantial interest during the last decade. This review article aims to highlight recent methodological developments regarding…

Methodology · Statistics 2014-11-19 Andreas Mayr , Harald Binder , Olaf Gefeller , Matthias Schmid
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