Abstract
The current practice for designing single-arm Phase II trials with time-to-event endpoints is limited to using either a maximum likelihood estimate test under the exponential model or a naive approach based on dichotomizing the event time at a landmark time point. A trial designed under the exponential model may not be reliable, and the naive approach is inefficient. The modified one-sample log-rank test statistic proposed in this article fills the void. In general, the proposed test can be used to design single-arm Phase II survival trials under any parametric survival distribution. Simulation results showed that it preserves type I error well and provides adequate power for Phase II cancer trial designs with time-to-event endpoints.
Original language | English |
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Pages (from-to) | 644-656 |
Number of pages | 13 |
Journal | Journal of Biopharmaceutical Statistics |
Volume | 26 |
Issue number | 4 |
DOIs | |
State | Published - Jul 3 2016 |
Bibliographical note
Publisher Copyright:© 2016 Taylor & Francis.
Keywords
- Clinical trial design
- one-sample log-rank test
- sample size
- single-arm Phase II
- survival analysis
- time-to-event
ASJC Scopus subject areas
- Statistics and Probability
- Pharmacology
- Pharmacology (medical)