Abstract

Chronic kidney Disease overall survival prediction model based on frailty index score: construction and validation using NHANES data.

Li, Ting (T);Lin, Zaoqiang (Z);Tang, Zeyong (Z);Feng, Liuchang (L);Lei, Nuo (N);Chen, Hui (H);Chen, Guozi (G);Tan, Qinxiang (Q);

 
     

Author information

Ren Fail.2025 Apr 21;47(1):2476740.doi:10.1080/0886022X.2025.2476740

Abstract

BACKGROUND: Frailty predicts poor outcomes in chronic kidney disease (CKD) patients. This study compared frailty's predictive power with other factors and aimed to develop a model for predicting overall survival (OS) in CKD patients.

METHODS: The study included 3,714 CKD participants from the National Health and Nutrition Examination Survey 2005-2018. The death data were updated to December 31, 2019. Lasso-Cox regression identified significant predictors among 42 factors, resulting in a prognostic nomogram using 11 key variables. Subsequent evaluation of the nomogram involved the C-index, the Areas Under Time-dependent Receiver Operating Characteristic Curves (AUC) and calibration curves.

RESULTS: Over a median follow-up of 5.92 years, 1,234 deaths occurred. The final predictors of OS in CKD patients included age, ethnicity, smoking status, estimated pulse wave velocity, body fat percentage, blood uric acid concentration, blood urea nitrogen concentration, and albumin concentration, neutrophil-to-lymphocyte ratio, urine albumin-to-creatinine ratio level, and frailty index (FI) score. The FI score was the strongest predictor with an HR of 76.54 (95% CI: 42.93, 136.46,  < 0.0001). In the training set, the AUC values were 80.11% for 1-year, 79.90% for 3-year, 79.53% for 5-year, and 81.34% for 10-year follow-ups. In the internal validation set, AUC values were 78.66%, 77.78%, 77.56%, and 79.54%, respectively. The nomogram's corrected C-index was 0.76 (95% CI: 0.75 - 0.78), and calibration curves showed satisfactory accuracy.

CONCLUSIONS: The FI score is a significant predictor of CKD OS. The developed nomogram based on the FI score is a promising tool for predicting the OS of CKD patients.

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