Testing and estimating treatment effect in the presence of delayed onset of the effect for cancer immunotherapies
Document Type
Lecture
Publication Date
3-28-2024
Abstract
The standard log-rank test has been extended by adopting various weight functions. Cancer vaccine or immunotherapy trials have shown a delayed onset of effect for the experimental therapy. This is manifested as a delayed separation of the survival curves. We propose new weighted log-rank tests to account for such delay. We implement a numerical evaluation of the Schoenfeld approximation (NESA) for the mean of the test statistic. The NESA enables us to assess the power and to calculate the sample size for detecting such delayed treatment effect and also for a more general specification of the non-proportional hazards in a trial. Extensive simulation studies are conducted to compare the performance of the proposed tests with the standard log-rank test and to assess their robustness to model mis-specifications. Our tests outperform the Gρ,γ class in general and have performance close to the optimal test. We demonstrate our methods on two cancer immunotherapy trials.
Relational Format
presentation
Recommended Citation
Huang, Xiang, "Testing and estimating treatment effect in the presence of delayed onset of the effect for cancer immunotherapies" (2024). Probability & Statistics Seminar. 8.
https://egrove.olemiss.edu/math_statistics/8
