Table 2. Comparisons among ToPs/R, regression methods, and machine learning benchmarks for pre-transplantation survival prediction using C-index and AUC (at horizons of 3-months, 1-year, 3-years, and 10-years).
| Methods | AUC (Mean ± Std) | C-index (Mean ± Std) | |||
|---|---|---|---|---|---|
| 3-month | 1-year | 3-year | 10-year | ||
| ToPs/R | .685 ± .003 | .667 ± .005 | .652 ± .009 | .663 ± .005 | .603 ± .003 |
| Cox | .624 ± .005 | .623 ± .008 | .614 ± .006 | .612 ± .006 | .534 ± .004 |
| Linear P | .671 ± .004 | .653 ± .002 | .633 ± .006 | .653 ± .009 | .584 ± .003 |
| Logit R | .672 ± .004 | .651 ± .006 | .635 ± .007 | .650 ± .009 | .582 ± .004 |
| AdaBoost | .633 ± .004 | .640 ± .008 | .624 ± .007 | .628 ± .009 | .577 ± .004 |
| DeepBoost | .635 ± .004 | .645 ± .004 | .626 ± .006 | .620 ± .016 | .578 ± .004 |
| LogitBoost | .674 ± .006 | .654 ± .008 | .641 ± .009 | .647 ± .006 | .584 ± .004 |
| XGBoost | .614 ± .005 | .596 ± .007 | .593 ± .007 | .582 ± .010 | .550 ± .004 |
| DT | .664 ± .005 | .646 ± .005 | .618 ± .007 | .610 ± .007 | .574 ± .003 |
| RF | .660 ± .004 | .642 ± .004 | .611 ± .007 | .618 ± .009 | .571 ± .003 |
| NN | .637 ± .004 | .641 ± .005 | .629 ± .006 | .622 ± .010 | .580 ± .003 |