Abstract
Recently, molecularly targeted agents and immunotherapy have been advanced for the treatment of relapse or refractory cancer patients, where disease progression-free survival or event-free survival is often a primary endpoint for the trial design. However, methods to evaluate two-stage single-arm phase II trials with a time-to-event endpoint are currently processed under an exponential distribution, which limits application of real trial designs. In this paper, we developed an optimal two-stage design, which is applied to the four commonly used parametric survival distributions. The proposed method has advantages compared with existing methods in that the choice of underlying survival model is more flexible and the power of the study is more adequately addressed. Therefore, the proposed two-stage design can be routinely used for single-arm phase II trial designs with a time-to-event endpoint as a complement to the commonly used Simon's two-stage design for the binary outcome.
Original language | English |
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Pages (from-to) | 214-229 |
Number of pages | 16 |
Journal | Pharmaceutical Statistics |
Volume | 19 |
Issue number | 3 |
DOIs | |
State | Published - May 1 2020 |
Bibliographical note
Publisher Copyright:© 2019 John Wiley & Sons, Ltd.
Funding
This research was supported by the Biostatistics and Bioinformatics Shared Resource Facility of the University of Kentucky Markey Cancer Center and National Cancer Institute (NCI) support grant P30CA177558. This research was supported by the Biostatistics and Bioinformatics Shared Resource Facility of the University of Kentucky Markey Cancer Center and National Cancer Institute (NCI) support grant P30CA177558.
Funders | Funder number |
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The Markey Biostatistics and Bioinformatics Shared Resource Facility | |
National Childhood Cancer Registry – National Cancer Institute | P30CA177558 |
University of Kentucky Markey Cancer Center |
Keywords
- one-sample log-rank test
- phase II trial
- sample size
- time-to-event
- two-stage design
ASJC Scopus subject areas
- Statistics and Probability
- Pharmacology
- Pharmacology (medical)