A Nomogram for End-Stage Renal Disease Prediction in Patients with Type 2 Diabetes Mellitus: A Nationwide Cohort Study in Korea.

Abstract

Backgruound: Despite the rising incidence of end-stage renal disease (ESRD) among individuals with type 2 diabetes mellitus (T2DM) in Korea, no predictive model or nomogram has been developed using a nationwide cohort. In this study, we developed a nomogram to predict the long-term risk of ESRD in patients with T2DM using a large-scale, population-based Korean database.

Methods: Using the Korean National Health Insurance Database, patients with T2DM who underwent health examinations between 2015 and 2016 were assigned as development (n=1,744,277) and validation (n=747,407) cohorts. New ESRD cases were identified using codes for renal replacement therapy. A Cox proportional hazards regression model was used to derive a risk-scoring system, and 13 variables were selected. A risk score nomogram was then created to estimate the risk of ESRD.

Results: In the development cohort, 8,631 patients with T2DM developed ESRD during a follow-up period of 4.8±0.9 years. After multivariable adjustment, significant predictors of ESRD included male sex, current smoking, physical inactivity, low income, low body mass index, hypertension, low-density lipoprotein cholesterol ≥160 mg/dL, chronic kidney disease, insulin use, and longer duration of T2DM. A final nomogram incorporating 13 variables was developed to estimate the individual probability of ESRD. The concordance index for ESRD prediction in the validation cohort was 0.906 (95% confidence interval, 0.9 to 0.912).

Conclusion: This 13-variable nomogram provides a simple tool for identifying patients with T2DM at high risk of ESRD and may aid in early intervention.