Distribution-free inference on contrasts of arbitrary summary measures of survival.

Statistics in Medicine
Kyle D RudserScott S Emerson

Abstract

We present an approach for inference on contrasts of clinically meaningful functionals of a survivor distribution (e.g., restricted mean, quantiles) that can avoid strong parametric or semiparametric assumptions on the underlying structure of the data. In this multistage approach, we first use an adaptive predictive model to estimate conditional survival distributions based on covariates. We then estimate nonparametrically one or more functionals of survival from the covariate-specific survival curves and evaluated contrasts of those functionals. We find that the use of an adaptive nonparametric tree-based predictive model leads to minimal loss in precision when semiparametric assumptions hold and provides marked improvement in accuracy when those assumptions are invalid. Therefore, this work as a whole supports the use of survival summaries appropriate to a given medical application, whether that be, for example, the median or 75th percentile in some settings or perhaps a restricted mean in others. The approach is also compared with the Mayo R score for primary biliary cirrhosis prognosis.

References

Jul 1, 1989·Hepatology : Official Journal of the American Association for the Study of Liver Diseases·E R DicksonA Langworthy
May 1, 1995·Journal of Clinical Epidemiology·A CiampiZ Lou
Aug 23, 2003·Biostatistics·R Xu, J O'Quigley
Jul 1, 1996·International Journal of Obstetric Anesthesia·A RhodesD G Cohen
May 28, 2009·Statistics in Medicine·Michael SchemperGeorg Heinze

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Citations

Aug 27, 2013·Biostatistics·Andrew WeyKyle Rudser
Sep 9, 2017·Biometrics·Chi Hyun LeeYu Shen
Jul 25, 2018·American Journal of Transplantation : Official Journal of the American Society of Transplantation and the American Society of Transplant Surgeons·Andrew WeyJon J Snyder
Aug 27, 2016·Current Hematologic Malignancy Reports·Zachary A K Frosch, Gregory A Abel
Mar 5, 2016·Statistics in Medicine·Andrew WeyKyle Rudser

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