Profiling Center-Specific Long Term Kidney Transplant Outcomes

• Activity Number: 188
• Type: Contributed
• Date/Time: Monday, August 1, 2011 : 10:30 AM to 12:20 PM
• Sponsor: ENAR
• Author(s): Kevin He*+ and Douglas E. Schaubel
• Companies: University of Michigan and University of Michigan
• Keywords: Center effect ; Direct standardization ; Laplace approximation ; Mean survival time ; Piece-wise exponential ; Log-normal frailty model

Abstract

Current measures of transplant center specific performance focus on short term outcomes, despite the fact that most graft losses occur in the long term. In this paper, we propose a method which combines a log-normal frailty model and piece-wise exponential baseline rate to compare the mean survival time across centers. The challenging part is that multi-center studies tend to generate heterogeneous samples (unequal covariate effects across centers). Laplace's approximation for integration is applied for maximum likelihood estimations. Direct and indirect standardization methods are applied to estimate the mean survival time. The proposed methods allow for valid estimation of mean survival time as oppose to the restricted mean lifetime and, within this context, robust profiling of long-term center specific outcomes. Asymptotic properties of proposed estimators are discussed. Finite-sample properties are examined through an extensive simulation study. The strengths and weaknesses of direct and indirect standardization are compared. The methods developed are applied to national kidney transplant data. The best (and worst) 10% of transplant centers in the Unites States are identified.