| 摘要 |
Described are methods of predicting graft survival based on pre-transplant variables. A logistic regression (LM) and/or a tree-based model (TBM) are used to identify predictors of graft survival and to generate prediction algorithms. Both the logistic regression model and the tree-based model may be used in clinical practice for long term prediction of graft survival based on pre-transplant variables. The invention is also directed to computer software, which includes a logistic regression model and/or a tree-based model to select pre-transplant variables and generate a graft survival algorithm and to calculate a graft survival probability, and for selecting appropriate organ donors and recipients to optimize the graft survival probability.
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