Multi-stage adaptive enrichment trial design with subgroup estimation

Autor:	Neha Joshi, Crystal T. Nguyen, Anastasia Ivanova
Rok vydání:	2020
Předmět:	Pharmacology Statistics and Probability Estimation Clinical Trials as Topic Function (mathematics) Article Regression Normal-inverse Gaussian distribution Multi stage Tree (data structure) Research Design Sample size determination Sample Size Statistics Humans Pharmacology (medical) Treatment effect Mathematics
Zdroj:	J Biopharm Stat
ISSN:	1520-5711 1054-3406
DOI:	10.1080/10543406.2020.1832109
Popis:	We consider the problem of estimating the best subgroup and testing for treatment effect in a clinical trial. We define the best subgroup as the subgroup that maximizes a utility function that reflects the trade-off between the subgroup size and the treatment effect. For moderate effect sizes and sample sizes, simpler methods for subgroup estimation worked better than more complex tree- based regression approaches. We propose a three-stage design with a weighted inverse normal combination test to test the hypothesis of no treatment effect across the three stages.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f8b069e0d04bbdc54ce8f044408686ee https://doi.org/10.1080/10543406.2020.1832109 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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