ArticleBiostatistics (Oxford, England)2018
Using Bayesian modeling in frequentist adaptive enrichment designs.
Article in Biostatistics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Challenges, opportunities, and innovative statistical designs for precision oncology trials.Annals of translational medicine · 2022Trial
- Biomarker-guided adaptive enrichment design with threshold detection for clinical trials with time-to-event outcome.Journal of biopharmaceutical statistics · 2025Article
- Latest Developments in "Adaptive Enrichment" Clinical Trial Designs in Oncology.Therapeutic innovation & regulatory science · 2024Review
- IBIS: identify biomarker-based subgroups with a Bayesian enrichment design for targeted combination therapy.BMC medical research methodology · 2023Article
- Point estimation for adaptive trial designs I: A methodological review.Statistics in medicine · 2023Review
- A two-stage adaptive clinical trial design with data-driven subgroup identification at interim analysis.Pharmaceutical statistics · 2022Article
- Bayesian group sequential enrichment designs based on adaptive regression of response and survival time on baseline biomarkers.Biometrics · 2022Article
- Enrichment Bayesian design for randomized clinical trials using categorical biomarkers and a binary outcome.BMC medical research methodology · 2022Article
- Adaptive Enrichment Designs in Clinical Trials.Annual review of statistics and its application · 2021Article
- Design and analysis of biomarker-integrated clinical trials with adaptive threshold detection and flexible patient enrichment.Journal of biopharmaceutical statistics · 2020Article
- A nonparametric Bayesian basket trial design.Biometrical journal. Biometrische Zeitschrift · 2019Article
- Bayesian Approaches to Subgroup Analysis and Related Adaptive Clinical Trial Designs.JCO precision oncology · 2019Review
- Auxiliary variable-enriched biomarker-stratified design.Statistics in medicine · 2018Article
- Point estimation following two-stage adaptive threshold enrichment clinical trials.Statistics in medicine · 2018Article
- Arguing for Adaptive Clinical Trials in Sepsis.Frontiers in immunology · 2018Review
- Inference for multimarker adaptive enrichment trials.Statistics in medicine · 2017Article
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2 authors.
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Abstract
Our increased understanding of the mechanistic heterogeneity of diseases has pushed the development of targeted therapeutics. We do not expect all patients with a given disease to benefit from a targeted drug; only those in the target population. That is, those with sufficient dysregulation in the biomolecular pathway targeted by treatment. However, due to complexity of the pathway, and/or technical issues with our characterizing assay, it is often hard to characterize the target population until well into large-scale clinical trials. This has stimulated the development of adaptive enrichment trials; clinical trials in which the target population is adaptively learned; and enrollment criteria are adaptively updated to reflect this growing understanding. This paper proposes a framework for group-sequential adaptive enrichment trials. Building on the work of Simon & Simon (2013). Adaptive enrichment designs for clinical trials. Biostatistics 14(4), 613-625), it includes a frequentist hypothesis test at the end of the trial. However, it uses Bayesian methods to optimize the decisions required during the trial (regarding how to restrict enrollment) and Bayesian methods to estimate effect size, and characterize the target population at the end of the trial. This joint frequentist/Bayesian design combines the power of Bayesian methods for decision making with the use of a formal hypothesis test at the end of the trial to preserve the studywise probability of a type I error.
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