title: Methods for comparing center-specific survival outcomes using direct standardization.
abstract: The evaluation of center-specific outcomes is often through survival analysis methods. Such evaluations must account for differences in the distribution of patient characteristics across centers. In the context of censored event times, it is also important that the measure chosen to evaluate centers not be influenced by imbalances in the center-specific censoring distributions. The practice of using center indicators in a hazard regression model is often invalid, inconvenient, or undesirable to carry out. We propose a semiparametric version of the standardized rate ratio (SRR) useful for the evaluation of centers with respect to a right-censored event time. The SRR for center j can be interpreted as the ratio of the expected number of deaths in the total population (if the total population were in fact subject to the center j mortality hazard) to the observed number of events. The proposed measure is not affected by differences in center-specific covariate or censoring distributions. Asymptotic properties of the proposed estimators are derived, with finite-sample properties examined through simulation studies. The proposed methods are applied to national kidney transplant data.
authors.affiliation: Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI 48109-2029, U.S.A.
authors.forename: Kevin
authors.initials: K
authors.lastname: He
authors.forename: Douglas E
authors.initials: DE
authors.lastname: Schaubel
mesh_terms: D000465:Algorithms; D015982:Bias; D006801:Humans; D016030:Kidney Transplantation / Q000401:mortality; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000379:methods* / Q000706:statistics & numerical data; D016016:Proportional Hazards Models; D016019:Survival Analysis
keywords: Cox regression; center effect; standardized rate ratio; stratification; survival analysis