Title | Quantifying the average of the time-varying hazard ratio via a class of transformations. |
Publication Type | Journal Article |
Year of Publication | 2015 |
Authors | Chen, Qingxia, Donglin Zeng, Joseph G. Ibrahim, Ming-Hui Chen, Zhiying Pan, and Xiaodong Xue |
Journal | Lifetime Data Anal |
Volume | 21 |
Issue | 2 |
Pagination | 259-79 |
Date Published | 2015 Apr |
ISSN | 1572-9249 |
Keywords | Bias, Biometry, Computer Simulation, Data Interpretation, Statistical, Genes, ras, Humans, Logistic Models, Prognosis, Proportional Hazards Models |
Abstract | The hazard ratio derived from the Cox model is a commonly used summary statistic to quantify a treatment effect with a time-to-event outcome. The proportional hazards assumption of the Cox model, however, is frequently violated in practice and many alternative models have been proposed in the statistical literature. Unfortunately, the regression coefficients obtained from different models are often not directly comparable. To overcome this problem, we propose a family of weighted hazard ratio measures that are based on the marginal survival curves or marginal hazard functions, and can be estimated using readily available output from various modeling approaches. The proposed transformation family includes the transformations considered by Schemper et al. (Statist Med 28:2473-2489, 2009) as special cases. In addition, we propose a novel estimate of the weighted hazard ratio based on the maximum departure from the null hypothesis within the transformation family, and develop a Kolmogorov[Formula: see text]Smirnov type of test statistic based on this estimate. Simulation studies show that when the hazard functions of two groups either converge or diverge, this new estimate yields a more powerful test than tests based on the individual transformations recommended in Schemper et al. (Statist Med 28:2473-2489, 2009), with a similar magnitude of power loss when the hazards cross. The proposed estimates and test statistics are applied to a colorectal cancer clinical trial. |
DOI | 10.1007/s10985-014-9301-0 |
Alternate Journal | Lifetime Data Anal |
Original Publication | Quantifying the average of the time-varying hazard ratio via a class of transformations. |
PubMed ID | 25073864 |
PubMed Central ID | PMC4312279 |
Grant List | UL1 TR000445 / TR / NCATS NIH HHS / United States R37 GM047845 / GM / NIGMS NIH HHS / United States R01 GM047845 / GM / NIGMS NIH HHS / United States R01 GM070335 / GM / NIGMS NIH HHS / United States UL1 RR024975 / RR / NCRR NIH HHS / United States P01 CA142538 / CA / NCI NIH HHS / United States R01 CA082659 / CA / NCI NIH HHS / United States R21 HL097334 / HL / NHLBI NIH HHS / United States |
Quantifying the average of the time-varying hazard ratio via a class of transformations.
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