TY - JOUR
T1 - Displaying survival of patient groups defined by covariate paths
T2 - Extensions of the Kaplan-Meier estimator
AU - Jay, Melissa
AU - Betensky, Rebecca A.
N1 - Funding Information:
We are grateful to Dr. Bella Vakulenko‐Lagun and to the members of Harvard's Biostatistics Cancer Working Group for their helpful suggestions and feedback on this research. This research was supported by the National Science Foundation Graduate Research Fellowship under Grant No. 000390183 (MJ) and NIH Training Grant in Quantitative Sciences for Cancer Research under Grant No. T32CA009337 (MJ) and R01NS094610 (RAB). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
Publisher Copyright:
© 2021 John Wiley & Sons, Ltd.
PY - 2021/4/15
Y1 - 2021/4/15
N2 - Extensions of the Kaplan-Meier estimator have been developed to illustrate the relationship between a time-varying covariate of interest and survival. In particular, Snapinn et al and Xu et al developed estimators to display survival for patients who always have a certain value of a time-varying covariate. These estimators properly handle time-varying covariates, but their clinical interpretation is limited. It is of greater clinical interest to display survival for patients whose covariates lie along certain defined paths. In this article, we propose extensions of Snapinn et al and Xu et al's estimators, providing crude and covariate-adjusted estimates of the survival function for patients defined by covariate paths. We also derive analytical variance estimators. We demonstrate the utility of these estimators with medical examples and a simulation study.
AB - Extensions of the Kaplan-Meier estimator have been developed to illustrate the relationship between a time-varying covariate of interest and survival. In particular, Snapinn et al and Xu et al developed estimators to display survival for patients who always have a certain value of a time-varying covariate. These estimators properly handle time-varying covariates, but their clinical interpretation is limited. It is of greater clinical interest to display survival for patients whose covariates lie along certain defined paths. In this article, we propose extensions of Snapinn et al and Xu et al's estimators, providing crude and covariate-adjusted estimates of the survival function for patients defined by covariate paths. We also derive analytical variance estimators. We demonstrate the utility of these estimators with medical examples and a simulation study.
KW - survival distribution
KW - time-dependent covariates
KW - time-varying covariates
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U2 - 10.1002/sim.8888
DO - 10.1002/sim.8888
M3 - Article
C2 - 33530128
AN - SCOPUS:85100145456
VL - 40
SP - 2024
EP - 2036
JO - Statistics in Medicine
JF - Statistics in Medicine
SN - 0277-6715
IS - 8
ER -