Development of iChoose Kidney Risk Estimates
Translation of Risk Estimates into a Shared Decision Making Tool
We used the following equation to translate model coefficients for 1-year and 3-year mortality estimates into an individualized, estimated risk of mortality represents the sum of the individual's risk factors (risk score) and is the estimated Y-intercept (or baseline risk).
For example, 3-year mortality risk for a dialysis patient is derived from the formula below,
-2.8457 (Baseline risk) + 0.0067(Sex) + 0.0388(Age) + -0.2990(Black race) + -0.6111(Other Race) + -.05253(Hispanic ethnicity) + 0.4737(Cardiovascular disease)+-0.4696(Hypertension) + 0.0169(Diabetes) + 0.3619(Low albumin)
and 3-year mortality among transplant patients is derived from the formula below,
-5.4292 (Baseline risk) + -0.0475(Sex) + 0.0382(Age) + -0.0261(Black race) + -0.508 (Other race) + -0.4034(Hispanic ethnicity) + 0.3369(Cardiovascular disease)+-0.2(Hypertension) + 0.4013 (Diabetes) + 0.2102(Low albumin) + 0.136 (6-12 months on dialysis) + 0.4906 (>12 months on dialysis)
where Baseline risk=1; Sex=1 for Male, Sex=2 for Female; 1=yes and 0=no for Black race, Other race, Hispanic ethnicity, Cardiovascular disease, Hypertension, Diabetes, and Low albumin, 6-12 months on dialysis, and >12 months on dialysis
In this case, a 41 year old African American male with a history of diabetes and hypertension who has been on dialysis for 8 months has a risk of dying over the next year of 5.3% on dialysis and 0.9% with a kidney transplant (relative risk of dying on dialysis vs. transplant is 5.9). This patient’s three year risk of dying on dialysis is 11.9%, and 2.7% with a transplant (Relative Risk=4.4). Risk of dying within the next three years with a deceased donor transplant (3.4%) is 2.1 times higher than risk of dying with a living donor transplant (1.6%).
Prediction Model Discrimination and Performance
We performed external validation of the risk prediction models for dialysis and transplantation at 3 years using the validation cohorts from USRDS. The discriminatory ability of the model for 3-year mortality was moderate for dialysis (c-statistic = 0.7047 [95% CI: 0.7029-0.7065] and for transplant (c-statistic = 0.7015 [95% CI: 0.6875-0.7155]). The c-statistic was 0.6640 (95% CI: 0.6458-0.6822) for deceased donor (DD) transplant and 0.7209 (95% CI: 0.6954-0.7463) for living donor (LD) transplant. The c-statistics were similar among the derivation and validation datasets, indicating that the predictive models were generalizable among the U.S. ESRD patients and kidney transplant recipients.