Stopping rules for phase I clinical trials with dose expansion cohorts Journal Article


Authors: Devlin, S. M.; Iasonos, A.; O’Quigley, J.
Article Title: Stopping rules for phase I clinical trials with dose expansion cohorts
Abstract: Many clinical trials incorporate stopping rules to terminate early if the clinical question under study can be answered with a high degree of confidence. While common in later-stage trials, these rules are rarely implemented in dose escalation studies, due in part to the relatively smaller sample size of these designs. However, even with a small sample size, this paper shows that easily implementable stopping rules can terminate dose-escalation early with minimal loss to the accuracy of maximum tolerated dose estimation. These stopping rules are developed when the goal is to identify one or two dose levels, as the maximum tolerated dose and co-maximum tolerated dose. In oncology, this latter goal is frequently considered when the study includes dose-expansion cohorts, which are used to further estimate and compare the safety and efficacy of one or two dose levels. As study protocols do not typically halt accrual between escalation and expansion, early termination is of clinical importance as it either allows for additional patients to be treated as part of the dose expansion cohort to obtain more precise estimates of the study endpoints or allows for an overall reduction in the total sample size. © The Author(s) 2021.
Keywords: adult; controlled study; drug efficacy; drug safety; cohort analysis; oncology; maximum tolerated dose; phase i clinical trials; sample size; phase 1 clinical trial (topic); early termination; human; male; female; article; expansion cohorts; dynamic stopping rules
Journal Title: Statistical Methods in Medical Research
Volume: 31
Issue: 2
ISSN: 0962-2802
Publisher: Sage Publications  
Date Published: 2022-02-01
Start Page: 334
End Page: 347
Language: English
DOI: 10.1177/09622802211064996
PUBMED: 34951338
PROVIDER: scopus
PMCID: PMC9400040
DOI/URL:
Notes: Article -- Export Date: 1 March 2022 -- Source: Scopus
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  1. Alexia Elia Iasonos
    362 Iasonos
  2. Sean McCarthy Devlin
    601 Devlin