Evidence map›Paper›PMID 41220217›Full record

ArticleEndocrinology and metabolism (Seoul, Korea)2026

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

Inha Jung, Bong-Seong Kim, So Young Park, Da Young Lee, Ji Hee Yu, Ji A Seo, Kyung-Do Han, Nan Hee Kim

Abstract read
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Article in Endocrinology and metabolism (Seoul, Korea), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Inha JungDivision of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea.
Bong-Seong KimDepartment of Statistics and Actuarial Science, Soongsil University, Seoul, Korea.
So Young ParkDivision of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea.
Da Young LeeDivision of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea.
Ji Hee YuDivision of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea.
Ji A SeoDivision of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea.
Kyung-Do HanDepartment of Statistics and Actuarial Science, Soongsil University, Seoul, Korea.
Nan Hee KimDivision of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea. nhkendo@gmail.com.

Funding

Korea Health Industry Development InstituteKorea University Ansan Hospital O2515231Ministry of Health and Welfare H123C0679Ministry of Science and ICTNational IT Industry Promotion Agency S0252-21-1001National Research Foundation of Korea 2019M3E5D3073102National Research Foundation of Korea 2023R1A2C2003479
6 · The paper itself

Abstract

backgruoundDespite 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.

methodsUsing 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.

resultsIn 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).

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

Indexed as

Diabetes Mellitus, Type 2Diabetic NephropathiesKidney Failure, ChronicNomogramsAdultAgedCohort StudiesFemaleFollow-Up StudiesHumansIncidenceMaleMiddle AgedPrognosisRepublic of KoreaRisk AssessmentDiabetes mellitus, type 2Kidney failure, chronicNomogramsRisk assessmentRisk prediction model

Identifiers

PMID41220217
PMCPMC13172632

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