Predicting long-term graft survival in adult kidney transplant recipients

doi:10.4103/1319-2442.98112

Home

Instructions

Users online: 66


ORIGINAL ARTICLE


Year : 2012 \| Volume : 23 \| Issue : 4 \| Page : 693-700

Predicting long-term graft survival in adult kidney transplant recipients Brett W Pinsky¹, Krista L Lentine¹, Patrick R Ercole¹, Paolo R Salvalaggio², Thomas E Burroughs¹, Mark A Schnitzler¹ ¹ Center for Outcomes Research, Saint Louis University School of Medicine, St. Louis, MO, USA ² Division of Transplant Surgery, University of Washington, Seattle, WA, USA Correspondence Address: Brett W Pinsky Center for Outcomes Research, Saint Louis University School of Medicine, St. Louis, MO, 63368 USA DOI: 10.4103/1319-2442.98112

The ability to accurately predict a population's long-term survival has important implications for quantifying the benefits of transplantation. To identify a model that can accurately predict a kidney transplant population's long-term graft survival, we retrospectively studied the United Network of Organ Sharing data from 13,111 kidney-only transplants completed in 1988- 1989. Nineteen-year death-censored graft survival (DCGS) projections were calculated and compared with the population's actual graft survival. The projection curves were created using a two-part estimation model that (1) fits a Kaplan-Meier survival curve immediately after transplant (Part A) and (2) uses truncated observational data to model a survival function for long-term projection (Part B). Projection curves were examined using varying amounts of time to fit both parts of the model. The accuracy of the projection curve was determined by examining whether predicted survival fell within the 95% confidence interval for the 19-year Kaplan-Meier survival, and the sample size needed to detect the difference in projected versus observed survival in a clinical trial. The 19-year DCGS was 40.7% (39.8-41.6%). Excellent predictability (41.3%) can be achieved when Part A is fit for three years and Part B is projected using two additional years of data. Using less than five total years of data tended to overestimate the population's long-term survival, accurate prediction of long-term DCGS is possible, but requires attention to the quantity data used in the projection method.



[FULL TEXT] [PDF]*