Beyond Bonferroni: new multiple contrast tests for time-to-event data under non-proportional hazards.

ABSTRACT: When comparing multiple groups in clinical trials, we are not only interested in whether there is a difference between any groups but rather where the difference is. Such research questions lead to testing multiple individual hypotheses. To control the familywise error rate (FWER), we must apply some corrections or introduce tests that control the FWER by design. In the case of time-to-event data, a Bonferroni-corrected log-rank test is commonly used. This approach has two significant drawbacks: (i) it loses power when the proportional hazards assumption is violated and (ii) the correction generally leads to a lower power, especially when the test statistics are not independent. We propose two new tests based on combined weighted log-rank tests. One is a simple multiple contrast test of we

SUBMITTER: Dormuth I 

PROVIDER: S-EPMC12804333 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature