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Updated: Jun 18, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Nomogram for predicting risk of mild renal dysfunction among general residents from rural Northeast China
Shasha Yu1, Hongmei Yang1, Bo Wang1
1Department of Cardiology, First Hospital of China Medical University, Shenyang 110001, Liaoning Province, China.
Background And Objectives:
Cumulative evidence confirms that mild renal dysfunction (MRD) is correlated with many cardiovascular risk factors and increases cardiovascular morbidity and mortality. The purpose of this study was to establish an effective nomogram for predicting the risk of MRD in the rural population of Northeast China.
Methods:
We analyzed the reports of 4944 subjects from the Northeast China Rural Cardiovascular Health Study (NCRCHS). All the participants completed the questionnaires, anthropometric measurements, and blood tests during the baseline study (2012-2013) and the follow-up study during 2015-2017 (an average of 4.6 years). The Chronic Kidney Disease Epidemiology (CKD-EPI) equation was used to calculate the estimated glomerular filtration rate (eGFR), and eGFR in the range of 60-90 mL/min/1.73m2 was defined as MRD.
Results:
The study revealed that a total of 889 subjects (18.0%) had MRD. Multivariate logistic analysis showed that annual income, abdominal obesity, hypertension, hyperglycemia, and frequent tea consumption were the independent risk factors (P < 0.05) for MRD. Thereafter, a nomogram with an area under the receiver operating characteristic curve (AUC) of 0.705 was constructed to accurately predict MRD. The calibration plot also showed an excellent consistency between the probability of prediction and observation.
Conclusion:
We constructed a nomogram based on epidemiological data, which could provide an individual prediction of MRD with good accuracy.
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