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Efficient semiparametric estimation of short-term and long-term hazard ratios with right-censored data.
Biometrics 2013; 69(4):840-9B

Abstract

The proportional hazards assumption in the commonly used Cox model for censored failure time data is often violated in scientific studies. Yang and Prentice (2005) proposed a novel semiparametric two-sample model that includes the proportional hazards model and the proportional odds model as sub-models, and accommodates crossing survival curves. The model leaves the baseline hazard unspecified and the two model parameters can be interpreted as the short-term and long-term hazard ratios. Inference procedures were developed based on a pseudo score approach. Although extension to accommodate covariates was mentioned, no formal procedures have been provided or proved. Furthermore, the pseudo score approach may not be asymptotically efficient. We study the extension of the short-term and long-term hazard ratio model of Yang and Prentice (2005) to accommodate potentially time-dependent covariates. We develop efficient likelihood-based estimation and inference procedures. The nonparametric maximum likelihood estimators are shown to be consistent, asymptotically normal, and asymptotically efficient. Extensive simulation studies demonstrate that the proposed methods perform well in practical settings. The proposed method successfully captured the phenomenon of crossing hazards in a cancer clinical trial and identified a genetic marker with significant long-term effect missed by using the proportional hazards model on age-at-onset of alcoholism in a genetic study.

Authors+Show Affiliations

Department of Statistics, George Mason University, Fairfax, Virginia, U.S.A.No affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, N.I.H., Extramural

Language

eng

PubMed ID

24328712

Citation

Diao, Guoqing, et al. "Efficient Semiparametric Estimation of Short-term and Long-term Hazard Ratios With Right-censored Data." Biometrics, vol. 69, no. 4, 2013, pp. 840-9.
Diao G, Zeng D, Yang S. Efficient semiparametric estimation of short-term and long-term hazard ratios with right-censored data. Biometrics. 2013;69(4):840-9.
Diao, G., Zeng, D., & Yang, S. (2013). Efficient semiparametric estimation of short-term and long-term hazard ratios with right-censored data. Biometrics, 69(4), pp. 840-9. doi:10.1111/biom.12097.
Diao G, Zeng D, Yang S. Efficient Semiparametric Estimation of Short-term and Long-term Hazard Ratios With Right-censored Data. Biometrics. 2013;69(4):840-9. PubMed PMID: 24328712.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Efficient semiparametric estimation of short-term and long-term hazard ratios with right-censored data. AU - Diao,Guoqing, AU - Zeng,Donglin, AU - Yang,Song, Y1 - 2013/11/04/ PY - 2012/06/01/received PY - 2013/04/01/revised PY - 2013/07/01/accepted PY - 2013/12/17/entrez PY - 2013/12/18/pubmed PY - 2014/8/6/medline KW - Non-parametric likelihood KW - Proportional hazards model KW - Proportional odds model KW - Semiparametric efficiency KW - Semiparametric hazards rate model SP - 840 EP - 9 JF - Biometrics JO - Biometrics VL - 69 IS - 4 N2 - The proportional hazards assumption in the commonly used Cox model for censored failure time data is often violated in scientific studies. Yang and Prentice (2005) proposed a novel semiparametric two-sample model that includes the proportional hazards model and the proportional odds model as sub-models, and accommodates crossing survival curves. The model leaves the baseline hazard unspecified and the two model parameters can be interpreted as the short-term and long-term hazard ratios. Inference procedures were developed based on a pseudo score approach. Although extension to accommodate covariates was mentioned, no formal procedures have been provided or proved. Furthermore, the pseudo score approach may not be asymptotically efficient. We study the extension of the short-term and long-term hazard ratio model of Yang and Prentice (2005) to accommodate potentially time-dependent covariates. We develop efficient likelihood-based estimation and inference procedures. The nonparametric maximum likelihood estimators are shown to be consistent, asymptotically normal, and asymptotically efficient. Extensive simulation studies demonstrate that the proposed methods perform well in practical settings. The proposed method successfully captured the phenomenon of crossing hazards in a cancer clinical trial and identified a genetic marker with significant long-term effect missed by using the proportional hazards model on age-at-onset of alcoholism in a genetic study. SN - 1541-0420 UR - https://www.unboundmedicine.com/medline/citation/24328712/Efficient_semiparametric_estimation_of_short_term_and_long_term_hazard_ratios_with_right_censored_data_ L2 - https://doi.org/10.1111/biom.12097 DB - PRIME DP - Unbound Medicine ER -