Analytical approaches for transplant research.
It is highly desirable to base decisions designed to improve medical practice or organ allocation policies on the analyses of the most recent data available. Yet there is often a need to balance this desire with the added value of evaluating long-term outcomes (e.g. 5-year mortality rates), which requires the use of data from earlier years. This article explains the methods used by the Scientific Registry of Transplant Recipients in order to achieve these goals simultaneously. The analysis of waiting list and transplant outcomes depends strongly on statistical methods that can combine data from different cohorts of patients that have been followed for different lengths of time. A variety of statistical methods have been designed to address these goals, including the Kaplan-Meier estimator, Cox regression models, and Poisson regression. An in-depth description of the statistical methods used for calculating waiting times associated with the various types of organ transplants is provided. Risk of mortality and graft failure, adjusted analyses, cohort selection, and the many complicating factors surrounding the calculation of follow-up time for various outcomes analyses are also examined.
Wolfe
Robert A
RA
Scientific Registry of Transplant Recipients/University of Michigan, Ann Arbor, MI, USA. bobwolfe@umich.edu
Schaubel
Douglas E
DE
Webb
Randall L
RL
Dickinson
David M
DM
Ashby
Valarie B
VB
Dykstra
Dawn M
DM
Hulbert-Shearon
Tempie E
TE
McCullough
Keith P
KP
D015331:Cohort Studies; D006801:Humans; D018579:Patient Selection; D012106:Research / Q000639:trends*; D012107:Research Design; D014180:Transplantation / Q000379:methods* / Q000401:mortality / Q000706:statistics & numerical data; D017211:Treatment Failure; D016896:Treatment Outcome; D014850:Waiting Lists