Ontology highlight
ABSTRACT:
SUBMITTER: Mark E
PROVIDER: S-EPMC6326487 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
Mark Ethan E Goldsman David D Gurbaxani Brian B Keskinocak Pinar P Sokol Joel J
PloS one 20190109 1
We used an ensemble of statistical methods to build a model that predicts kidney transplant survival and identifies important predictive variables. The proposed model achieved better performance, measured by Harrell's concordance index, than the Estimated Post Transplant Survival model used in the kidney allocation system in the U.S., and other models published recently in the literature. The model has a five-year concordance index of 0.724 (in comparison, the concordance index is 0.697 for the ...[more]