Statistical issues for design and analysis of single-arm multi-stage phase II cancer clinical trials.

TitleStatistical issues for design and analysis of single-arm multi-stage phase II cancer clinical trials.
Publication TypeJournal Article
Year of Publication2015
AuthorsJung, Sin-Ho
JournalContemp Clin Trials
Volume42
Pagination9-17
Date Published2015 May
ISSN1559-2030
KeywordsClinical Trials, Phase II as Topic, Data Interpretation, Statistical, Humans, Models, Statistical, Neoplasms, Prospective Studies, Research Design, Sample Size
Abstract

BACKGROUND: Phase II trials have been very widely conducted and published every year for cancer clinical research. In spite of the fast progress in design and analysis methods, single-arm two-stage design is still the most popular for phase II cancer clinical trials. Because of their small sample sizes, statistical methods based on large sample approximation are not appropriate for design and analysis of phase II trials.METHODS: As a prospective clinical research, the analysis method of a phase II trial is predetermined at the design stage and it is analyzed during and at the end of the trial as planned by the design. The analysis method of a trial should be matched with the design method. For two-stage single arm phase II trials, Simon's method has been the standards for choosing an optimal design, but the resulting data have been analyzed and published ignoring the two-stage design aspect with small sample sizes.CONCLUSIONS: In this article, we review analysis methods that exactly get along with the exact two-stage design method. We also discuss some statistical methods to improve the existing design and analysis methods for single-arm two-stage phase II trials.

DOI10.1016/j.cct.2015.02.007
Alternate JournalContemp Clin Trials
Original PublicationStatistical issues for design and analysis of single-arm multi-stage phase II cancer clinical trials.
PubMed ID25749311
PubMed Central IDPMC4450127
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States
CA142538-01 / CA / NCI NIH HHS / United States
Project: