Fig 1.
Survival probabilities of different transplant cohorts.
The survival probabilities are calculated from the Kaplan-Meier estimate.
Fig 2.
Variable importance for recipients ages 50 and under based on Breiman-Cutler permutation importance.
Fig 3.
Variable importance for recipients ages 51 and older based on Breiman-Cutler permutation importance.
Fig 4.
Cox lasso variable selection for recipients ages 50 and under.
The top row represents the number of non-zero coefficients per Lasso penalty value, lambda. The vertical line L0 corresponds to the optimal penalty, which minimizes the PLD. The line Lσ corresponds to the largest penalty value corresponding to the PLD values within one standard deviation of the minimum PLD.
Table 1.
Variables in the proposed predictive model.
Table 2.
Performance of the proposed predictive model compared to other models.
Fig 5.
Predicted survival of the proposed model.
Trained on 100,000 observations and validated on 25,000 out-of-sample observations. The survival curves are separated into 5 groups based on the predicted 5-year survival in the out-of-sample data.
Fig 6.
Predicted survival of the proposed model for a ‘typical’ kidney transplant recipient.
Trained on 100,000 observations and validated on 25,000 out-of-sample observations. In the out-of-sample data, an observation is considered ‘typical’ if the values are within one standard deviation of the mean for recipient age, donor age, and cold ischemia time, and the most common values from the data for recipient diabetes, recipient dialysis status, recipient medical condition, and donor hypertension status.