Can J Kidney Health Dis. 2026 Apr 10;13:20543581261437298. doi: 10.1177/20543581261437298. eCollection 2026.
ABSTRACT
BACKGROUND: A significant barrier to kidney transplantation is limited knowledge about its potential benefits. To help patients who are receiving maintenance dialysis make more informed treatment decisions, a risk calculator (iChoose Kidney) was developed in the United States to provide individualized survival estimates for dialysis versus kidney transplantation. This tool was externally validated in Ontario, Canada, and was found to accurately predict mortality (Ontario version of the tool "Dialysis vs. Kidney Transplant-Estimated Survival in Ontario Risk Calculator"). The United States risk calculator has been updated to include additional variables (e.g., dialysis modality).
OBJECTIVE: To externally validate the updated iChoose Kidney risk calculator in patients from Ontario, Canada, with kidney failure using more recent data, removing race (race in clinical algorithms may perpetuate racial bias in medicine) and using a refined cohort definition (i.e., restricting to patients with no recorded contraindications to transplant).
DESIGN: External validation study.
SETTING: Linked administrative health care databases from Ontario, Canada.
PATIENTS: 24 793 patients receiving maintenance dialysis and 5398 kidney transplant recipients from January 1, 2011, to August 31, 2021.
MEASUREMENTS: Three-year mortality.
METHODS: Model discrimination was evaluated using the C-statistic. Calibration was assessed by comparing the observed versus predicted mortality risks, and further assessed by using loess-smoothed calibration plots. To address over- or under-prediction (calibration-in-the-large), intercepts were adjusted using a correction factor. In our updated model, we used logistic regression to calculate mortality risk, incorporating the following variables: sex assigned at birth (male vs female), age (continuous), cardiovascular disease, hypertension, diabetes, time on dialysis (i.e., <6 months, 6 to 12 months, >1 to 2 years, >2 to 3 years, >3 to 5 years, >5 to 7 years, >7 to 10 years, >10 to 14 years, >14 years), and dialysis modality (peritoneal dialysis, home hemodialysis, in-center dialysis). In a post-hoc analysis, we used the simplified equations from our original Canadian external validation study of the iChoose Kidney tool (i.e., age, sex, hypertension, diabetes, cardiovascular disease, time on dialysis [<6 months, 6-12 months, >12 months]), with removal of the race variable as the only modification.
RESULTS: In the dialysis cohort, over a median follow-up of 2.5 years, 30.3% of patients died. In the kidney transplant recipient cohort, over a median follow-up of 2.9 years, 7.3% died. Our updated model had moderate discrimination (C-statistic for dialysis cohort: 0.67 [95% CI: 0.67, 0.68] and C-statistic for kidney transplant cohort: 0.76 [95% CI: 0.74, 0.79]). After recalibrating the intercepts, the observed and predicted mortality were similar between the dialysis cohort and the kidney transplant cohort. Similar results were found in a post-hoc analysis using the original model with the race variable removed.
LIMITATIONS: Mortality risk estimates assume that all treatment options are readily accessible to patients. However, the average waiting time for a deceased donor kidney transplant in Ontario can be several years.
CONCLUSIONS: After minor modifications, the iChoose Kidney risk calculator provides reliable survival estimates in patients with kidney failure from Ontario, Canada. Given the similarity in model performance between the updated model and the original model, with race removed, we will continue to use our original simplified model, but we will remove race. Our updated Dialysis vs. Kidney Transplant-Estimated Survival in Ontario Risk Calculator can continue to be a valuable tool for healthcare professionals to use with patients who are receiving maintenance dialysis to provide individualized survival estimates for dialysis versus transplantation, supporting informed decision-making about kidney transplantation.
PMID:41978769 | PMC:PMC13070169 | DOI:10.1177/20543581261437298