A two-step approach for analyzing time to event data under non-proportional hazards
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866911776266780672 |
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| author | Brugger, Jonas Friede, Tim Klinglmüller, Florian Posch, Martin Ristl, Robin König, Franz |
| author_facet | Brugger, Jonas Friede, Tim Klinglmüller, Florian Posch, Martin Ristl, Robin König, Franz |
| contents | The log-rank test and the Cox proportional hazards model are commonly used to compare time-to-event data in clinical trials, as they are most powerful under proportional hazards. But there is a loss of power if this assumption is violated, which is the case for some new oncology drugs like immunotherapies. We consider a two-stage test procedure, in which the weighting of the log-rank test statistic depends on a pre-test of the proportional hazards assumption. I.e., depending on the pre-test either the log-rank or an alternative test is used to compare the survival probabilities. We show that if naively implemented this can lead to a substantial inflation of the type-I error rate. To address this, we embed the two-stage test in a permutation test framework to keep the nominal level alpha. We compare the operating characteristics of the two-stage test with the log-rank test and other tests by clinical trial simulations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_08336 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A two-step approach for analyzing time to event data under non-proportional hazards Brugger, Jonas Friede, Tim Klinglmüller, Florian Posch, Martin Ristl, Robin König, Franz Methodology The log-rank test and the Cox proportional hazards model are commonly used to compare time-to-event data in clinical trials, as they are most powerful under proportional hazards. But there is a loss of power if this assumption is violated, which is the case for some new oncology drugs like immunotherapies. We consider a two-stage test procedure, in which the weighting of the log-rank test statistic depends on a pre-test of the proportional hazards assumption. I.e., depending on the pre-test either the log-rank or an alternative test is used to compare the survival probabilities. We show that if naively implemented this can lead to a substantial inflation of the type-I error rate. To address this, we embed the two-stage test in a permutation test framework to keep the nominal level alpha. We compare the operating characteristics of the two-stage test with the log-rank test and other tests by clinical trial simulations. |
| title | A two-step approach for analyzing time to event data under non-proportional hazards |
| topic | Methodology |
| url | https://arxiv.org/abs/2402.08336 |