Development of a Predictive Tool for Maintenance Dialysis Initiation: A Retrospective Cohort Analysis of 589,284...

Maintenance dialysis initiation is rare in early-stage chronic kidney disease (CKD), making accurate risk stratification difficult. We sought to build a simple prediction score based on routine health checkup data.

Retrospective cohort study.

Adults (≥40 years) attending government-mandated health checkups in Shizuoka Prefecture, Japan, 2012-2020 (N = 589,284).

Baseline demographics, vital signs, laboratory indices, medication use, and lifestyle factors routinely recorded at health checks.

Time from first health checkup to initiation of maintenance dialysis, ascertained from procedure codes; death treated as a competing risk.

Two-thirds of participants were randomly assigned to a training cohort (n = 392,856; events = 335) and one-third to a test cohort (n = 196,428; events = 179). Cause-specific Cox models generated hazard ratios that were converted to integer scores (maximum 31). Discrimination was evaluated with Harrell's c-index and calibration with performed with cumulative incidence curves.

During a median follow-up of 5.9 years, 514 participants (0.09%) initiated dialysis. Independent predictors included male sex, body mass index <18.5 kg/m², higher systolic blood pressure, hemoglobin A1c ≥8 %, lower estimated glomerular filtration rate, proteinuria, aspartate aminotransferase ≥50 IU/L, use of antihypertensive or antidiabetic drugs, and habitual smoking. The score showed excellent discrimination in both training (c-index, 0.916; 95% confidence interval [CI], 0.898-0.934) and test (c-index, 0.916; 95% CI, 0.889-0.943) cohorts. High-risk individuals (score ≥16; 0.3% of the cohort) had a 5-year dialysis incidence of 4.6%, yet 95% remained dialysis-free, underscoring the challenge of predicting this rare outcome.

CKD onset predated cohort entry, prescription data were not analyzed for causal effects, and external validation is pending.

Our model, leveraging routine health checkup data, accurately identifies persons at elevated risk for future dialysis despite low event rates.