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Activity Number:
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53
- New Developments in Survival Analysis
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Type:
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Contributed
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Date/Time:
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Sunday, August 8, 2021 : 3:30 PM to 5:20 PM
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Sponsor:
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Biometrics Section
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Abstract #318296
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Title:
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CauchyCP: A Powerful Test Under Nonproportional Hazards Using Cauchy Combination of Change-Point Cox Regressions
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Author(s):
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Hong Zhang* and qing li and Devan V Mehrotra and Judong Shen
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Companies:
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Merck & Co., Inc. and Merck & co., Inc. and Merck & Co., Inc. and Merck & Co. Inc.
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Keywords:
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Survival analysis;
Non-proportional hazard;
Cox regression;
Change-point;
Clinical trials
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Abstract:
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Non-proportional hazards data are routinely encountered in randomized clinical trials. In such cases, classic Cox proportional hazards model can suffer from severe power loss, with difficulty in interpretation of the estimated hazard ratio since the treatment effect varies over time. We propose CauchyCP, an omnibus test of change-point Cox regression models, to overcome both challenges while detecting signals of non-proportional hazards patterns. Extensive simulation studies demonstrate that, compared to existing treatment comparison tests under non-proportional hazards, the proposed CauchyCP test 1) controls the type I error better at small ? levels (< 0.01); 2) increases the power of detecting time-varying effects; and 3) is more computationally efficient. The superior performance of CauchyCP is further illustrated using retrospective analyses of two randomized clinical trial datasets and a pharmacogenetic biomarker study dataset. The R package CauchyCP is publicly available on CRAN.
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Authors who are presenting talks have a * after their name.
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