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- Title
Group sequential monitoring based on the weighted log-rank test statistic with the Fleming-Harrington class of weights in cancer vaccine studies.
- Authors
Hasegawa, Takahiro
- Abstract
In recent years, immunological science has evolved, and cancer vaccines are now approved and available for treating existing cancers. Because cancer vaccines require time to elicit an immune response, a delayed treatment effect is expected and is actually observed in drug approval studies. Accordingly, we propose the evaluation of survival endpoints by weighted log-rank tests with the Fleming-Harrington class of weights. We consider group sequential monitoring, which allows early efficacy stopping, and determine a semiparametric information fraction for the Fleming-Harrington family of weights, which is necessary for the error spending function. Moreover, we give a flexible survival model in cancer vaccine studies that considers not only the delayed treatment effect but also the long-term survivors. In a Monte Carlo simulation study, we illustrate that when the primary analysis is a weighted log-rank test emphasizing the late differences, the proposed information fraction can be a useful alternative to the surrogate information fraction, which is proportional to the number of events. Copyright © 2016 John Wiley & Sons, Ltd.
- Subjects
GROUP sequential design; LOG-rank test; TREATMENT effectiveness; IMMUNOLOGY; CANCER vaccines; DRUG approval; MONTE Carlo method
- Publication
Pharmaceutical Statistics, 2016, Vol 15, Issue 5, p412
- ISSN
1539-1604
- Publication type
Article
- DOI
10.1002/pst.1760