Analytical methods and database design: implications for transplant researchers, 2005.
Understanding how transplant data are collected is crucial to understanding how the data can be used. The collection and use of Organ Procurement and Transplantation Network/Scientific Registry of Transplant Recipients (OPTN/SRTR) data continues to evolve, leading to improvements in data quality, timeliness and scope while reducing the data collection burden. Additional ascertainment of outcomes completes and validates existing data, although caveats remain for researchers. We also consider analytical issues related to cohort choice, timing of data submission, and transplant center variations in follow-up data. All of these points should be carefully considered when choosing cohorts and data sources for analysis. The second part of the article describes some of the statistical methods for outcome analysis employed by the SRTR. Issues of cohort and follow-up period selection lead into a discussion of outcome definitions, event ascertainment, censoring and covariate adjustment. We describe methods for computing unadjusted mortality rates and survival probabilities, and estimating covariate effects through regression modeling. The article concludes with a description of simulated allocation modeling, developed by the SRTR for comparing outcomes of proposed changes to national organ allocation policies.
Levine
G N
GN
Scientific Registry of Transplant Recipients, University Renal Research and Education Association, Ann Arbor, MI, USA. glevine@urrea.org
McCullough
K P
KP
Rodgers
A M
AM
Dickinson
D M
DM
Ashby
V B
VB
Schaubel
D E
DE
D003625:Data Collection; D016208:Databases, Factual; D006801:Humans; D016377:Organ Transplantation / Q000379:methods*; D018579:Patient Selection; D012984:Software; D013997:Time Factors; D009927:Tissue and Organ Procurement / Q000379:methods* / Q000706:statistics & numerical data; D019737:Transplants; D014850:Waiting Lists