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Bayesian and frequentist approaches to sequential monitoring for futility in oncology basket trials: A comparison of Simon’s two-stage design and Bayesian predictive probability monitoring with information sharing across baskets

This article discusses and compares statistical designs of basket trial, from both frequentist and Bayesian perspectives. Baskets trials are used in oncology to study interventions that are developed to target a specific feature (often genetic alteration or immune phenotype) that is observed across...

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Autores principales: Kaizer, Alexander, Zabor, Emily, Nie, Lei, Hobbs, Brian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9345361/
https://www.ncbi.nlm.nih.gov/pubmed/35917296
http://dx.doi.org/10.1371/journal.pone.0272367
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author Kaizer, Alexander
Zabor, Emily
Nie, Lei
Hobbs, Brian
author_facet Kaizer, Alexander
Zabor, Emily
Nie, Lei
Hobbs, Brian
author_sort Kaizer, Alexander
collection PubMed
description This article discusses and compares statistical designs of basket trial, from both frequentist and Bayesian perspectives. Baskets trials are used in oncology to study interventions that are developed to target a specific feature (often genetic alteration or immune phenotype) that is observed across multiple tissue types and/or tumor histologies. Patient heterogeneity has become pivotal to the development of non-cytotoxic treatment strategies. Treatment targets are often rare and exist among several histologies, making prospective clinical inquiry challenging for individual tumor types. More generally, basket trials are a type of master protocol often used for label expansion. Master protocol is used to refer to designs that accommodates multiple targets, multiple treatments, or both within one overarching protocol. For the purpose of making sequential decisions about treatment futility, Simon’s two-stage design is often embedded within master protocols. In basket trials, this frequentist design is often applied to independent evaluations of tumor histologies and/or indications. In the tumor agnostic setting, rarer indications may fail to reach the sample size needed for even the first evaluation for futility. With recent innovations in Bayesian methods, it is possible to evaluate for futility with smaller sample sizes, even for rarer indications. Novel Bayesian methodology for a sequential basket trial design based on predictive probability is introduced. The Bayesian predictive probability designs allow interim analyses with any desired frequency, including continual assessments after each patient observed. The sequential design is compared with and without Bayesian methods for sharing information among a collection of discrete, and potentially non-exchangeable tumor types. Bayesian designs are compared with Simon’s two-stage minimax design.
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spelling pubmed-93453612022-08-03 Bayesian and frequentist approaches to sequential monitoring for futility in oncology basket trials: A comparison of Simon’s two-stage design and Bayesian predictive probability monitoring with information sharing across baskets Kaizer, Alexander Zabor, Emily Nie, Lei Hobbs, Brian PLoS One Research Article This article discusses and compares statistical designs of basket trial, from both frequentist and Bayesian perspectives. Baskets trials are used in oncology to study interventions that are developed to target a specific feature (often genetic alteration or immune phenotype) that is observed across multiple tissue types and/or tumor histologies. Patient heterogeneity has become pivotal to the development of non-cytotoxic treatment strategies. Treatment targets are often rare and exist among several histologies, making prospective clinical inquiry challenging for individual tumor types. More generally, basket trials are a type of master protocol often used for label expansion. Master protocol is used to refer to designs that accommodates multiple targets, multiple treatments, or both within one overarching protocol. For the purpose of making sequential decisions about treatment futility, Simon’s two-stage design is often embedded within master protocols. In basket trials, this frequentist design is often applied to independent evaluations of tumor histologies and/or indications. In the tumor agnostic setting, rarer indications may fail to reach the sample size needed for even the first evaluation for futility. With recent innovations in Bayesian methods, it is possible to evaluate for futility with smaller sample sizes, even for rarer indications. Novel Bayesian methodology for a sequential basket trial design based on predictive probability is introduced. The Bayesian predictive probability designs allow interim analyses with any desired frequency, including continual assessments after each patient observed. The sequential design is compared with and without Bayesian methods for sharing information among a collection of discrete, and potentially non-exchangeable tumor types. Bayesian designs are compared with Simon’s two-stage minimax design. Public Library of Science 2022-08-02 /pmc/articles/PMC9345361/ /pubmed/35917296 http://dx.doi.org/10.1371/journal.pone.0272367 Text en https://creativecommons.org/publicdomain/zero/1.0/This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Kaizer, Alexander
Zabor, Emily
Nie, Lei
Hobbs, Brian
Bayesian and frequentist approaches to sequential monitoring for futility in oncology basket trials: A comparison of Simon’s two-stage design and Bayesian predictive probability monitoring with information sharing across baskets
title Bayesian and frequentist approaches to sequential monitoring for futility in oncology basket trials: A comparison of Simon’s two-stage design and Bayesian predictive probability monitoring with information sharing across baskets
title_full Bayesian and frequentist approaches to sequential monitoring for futility in oncology basket trials: A comparison of Simon’s two-stage design and Bayesian predictive probability monitoring with information sharing across baskets
title_fullStr Bayesian and frequentist approaches to sequential monitoring for futility in oncology basket trials: A comparison of Simon’s two-stage design and Bayesian predictive probability monitoring with information sharing across baskets
title_full_unstemmed Bayesian and frequentist approaches to sequential monitoring for futility in oncology basket trials: A comparison of Simon’s two-stage design and Bayesian predictive probability monitoring with information sharing across baskets
title_short Bayesian and frequentist approaches to sequential monitoring for futility in oncology basket trials: A comparison of Simon’s two-stage design and Bayesian predictive probability monitoring with information sharing across baskets
title_sort bayesian and frequentist approaches to sequential monitoring for futility in oncology basket trials: a comparison of simon’s two-stage design and bayesian predictive probability monitoring with information sharing across baskets
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9345361/
https://www.ncbi.nlm.nih.gov/pubmed/35917296
http://dx.doi.org/10.1371/journal.pone.0272367
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