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Early stopping in seamless phase I/ II clinical trials
Author(s) -
Khan Noor M.,
Alam M. Iftakhar
Publication year - 2020
Publication title -
pharmaceutical statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 38
eISSN - 1539-1612
pISSN - 1539-1604
DOI - 10.1002/pst.2084
Subject(s) - clinical trial , early stopping , maximum tolerated dose , sample size determination , confidence interval , medicine , phase (matter) , task (project management) , computer science , statistics , mathematics , machine learning , chemistry , management , organic chemistry , artificial neural network , economics
In recent years, seamless phase I/II clinical trials have drawn much attention, as they consider both toxicity and efficacy endpoints in finding an optimal dose (OD). Engaging an appropriate number of patients in a trial is a challenging task. This paper attempts a dynamic stopping rule to save resources in phase I/II trials. That is, the stopping rule aims to save patients from unnecessary toxic or subtherapeutic doses. We allow a trial to stop early when widths of the confidence intervals for the dose‐response parameters become narrower or when the sample size is equal to a predefined size, whichever comes first. The simulation study of dose‐response scenarios in various settings demonstrates that the proposed stopping rule can engage an appropriate number of patients. Therefore, we suggest its use in clinical trials.