Performance of different criteria in the multivariate Cox regression model
| LRT χ2 (p value) | Loss in χ2 | AIC | Changes in AIC | |
|---|---|---|---|---|
| Full model | 765.4 (<0.001) | – | 33 413.2 | – |
| Removing Milan | 759.9 (<0.001) | −5.5 | 33 416.6 | 3.4 |
| Removing Valencia | 765.4 (<0.001) | 5.5 | 33 411.2 | −5.4 |
| Removing UCSF | 764.7 (<0.001) | −0.7 | 33 411.8 | 0.6 |
| Removing CUN | 761.3 (<0.001) | −3.4 | 33 415.3 | 3.5 |
| Removing Hangzhou | 303.6 (<0.001) | −154.7 | 33 570.0 | 154.7 |
A multivariate Cox model was built comprising all five sets of criteria as covariates. By reducing a certain set of criteria individually from the whole model, its independent contribution was evaluated in regards to the changes in LRT χ2 and AIC value.
AIC, Akaike information criterion; CUN, University Clinic of Navarra; LRT, likelihood ratio test; UCSF, University of California, San Francisco.