A Proportional Hazards Regression Model for the Subdistribution with Covariates-adjusted Censoring Weight for Competing Risks Data

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A Proportional Hazards Regression Model for the Subdistribution with Covariates-adjusted Censoring Weight for Competing Risks Data. / He, Peng; Eriksson, Frank; Scheike, Thomas H.; Zhang, Mei Jie.

In: Scandinavian Journal of Statistics, Vol. 43, No. 1, 03.2016, p. 103-122.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

He, P, Eriksson, F, Scheike, TH & Zhang, MJ 2016, 'A Proportional Hazards Regression Model for the Subdistribution with Covariates-adjusted Censoring Weight for Competing Risks Data', Scandinavian Journal of Statistics, vol. 43, no. 1, pp. 103-122. https://doi.org/10.1111/sjos.12167

APA

He, P., Eriksson, F., Scheike, T. H., & Zhang, M. J. (2016). A Proportional Hazards Regression Model for the Subdistribution with Covariates-adjusted Censoring Weight for Competing Risks Data. Scandinavian Journal of Statistics, 43(1), 103-122. https://doi.org/10.1111/sjos.12167

Vancouver

He P, Eriksson F, Scheike TH, Zhang MJ. A Proportional Hazards Regression Model for the Subdistribution with Covariates-adjusted Censoring Weight for Competing Risks Data. Scandinavian Journal of Statistics. 2016 Mar;43(1):103-122. https://doi.org/10.1111/sjos.12167

Author

He, Peng ; Eriksson, Frank ; Scheike, Thomas H. ; Zhang, Mei Jie. / A Proportional Hazards Regression Model for the Subdistribution with Covariates-adjusted Censoring Weight for Competing Risks Data. In: Scandinavian Journal of Statistics. 2016 ; Vol. 43, No. 1. pp. 103-122.

Bibtex

@article{a17e7d1ea0b443778ff2006bb6c0d250,
title = "A Proportional Hazards Regression Model for the Subdistribution with Covariates-adjusted Censoring Weight for Competing Risks Data",
abstract = "With competing risks data, one often needs to assess the treatment and covariate effects on the cumulative incidence function. Fine and Gray proposed a proportional hazards regression model for the subdistribution of a competing risk with the assumption that the censoring distribution and the covariates are independent. Covariate-dependent censoring sometimes occurs in medical studies. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with proper adjustments for covariate-dependent censoring. We consider a covariate-adjusted weight function by fitting the Cox model for the censoring distribution and using the predictive probability for each individual. Our simulation study shows that the covariate-adjusted weight estimator is basically unbiased when the censoring time depends on the covariates, and the covariate-adjusted weight approach works well for the variance estimator as well. We illustrate our methods with bone marrow transplant data from the Center for International Blood and Marrow Transplant Research. Here, cancer relapse and death in complete remission are two competing risks.",
keywords = "Competing risks, Cumulative incidence function, Inverse probability of censoring weight, Proportional hazards model, Subdistribution",
author = "Peng He and Frank Eriksson and Scheike, {Thomas H.} and Zhang, {Mei Jie}",
year = "2016",
month = "3",
doi = "10.1111/sjos.12167",
language = "English",
volume = "43",
pages = "103--122",
journal = "Scandinavian Journal of Statistics",
issn = "0303-6898",
publisher = "Wiley-Blackwell",
number = "1",

}

RIS

TY - JOUR

T1 - A Proportional Hazards Regression Model for the Subdistribution with Covariates-adjusted Censoring Weight for Competing Risks Data

AU - He, Peng

AU - Eriksson, Frank

AU - Scheike, Thomas H.

AU - Zhang, Mei Jie

PY - 2016/3

Y1 - 2016/3

N2 - With competing risks data, one often needs to assess the treatment and covariate effects on the cumulative incidence function. Fine and Gray proposed a proportional hazards regression model for the subdistribution of a competing risk with the assumption that the censoring distribution and the covariates are independent. Covariate-dependent censoring sometimes occurs in medical studies. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with proper adjustments for covariate-dependent censoring. We consider a covariate-adjusted weight function by fitting the Cox model for the censoring distribution and using the predictive probability for each individual. Our simulation study shows that the covariate-adjusted weight estimator is basically unbiased when the censoring time depends on the covariates, and the covariate-adjusted weight approach works well for the variance estimator as well. We illustrate our methods with bone marrow transplant data from the Center for International Blood and Marrow Transplant Research. Here, cancer relapse and death in complete remission are two competing risks.

AB - With competing risks data, one often needs to assess the treatment and covariate effects on the cumulative incidence function. Fine and Gray proposed a proportional hazards regression model for the subdistribution of a competing risk with the assumption that the censoring distribution and the covariates are independent. Covariate-dependent censoring sometimes occurs in medical studies. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with proper adjustments for covariate-dependent censoring. We consider a covariate-adjusted weight function by fitting the Cox model for the censoring distribution and using the predictive probability for each individual. Our simulation study shows that the covariate-adjusted weight estimator is basically unbiased when the censoring time depends on the covariates, and the covariate-adjusted weight approach works well for the variance estimator as well. We illustrate our methods with bone marrow transplant data from the Center for International Blood and Marrow Transplant Research. Here, cancer relapse and death in complete remission are two competing risks.

KW - Competing risks

KW - Cumulative incidence function

KW - Inverse probability of censoring weight

KW - Proportional hazards model

KW - Subdistribution

U2 - 10.1111/sjos.12167

DO - 10.1111/sjos.12167

M3 - Journal article

VL - 43

SP - 103

EP - 122

JO - Scandinavian Journal of Statistics

JF - Scandinavian Journal of Statistics

SN - 0303-6898

IS - 1

ER -

ID: 150981960