Development and validation of a general population renal risk score

Area of Science:

• Nephrology
• Epidemiology
• Biostatistics

Background:

• Progressive chronic kidney disease (CKD) poses a significant health burden.
• Accurate prediction scores are needed to identify at-risk individuals.
• The PREVEND study provides a robust dataset for developing such scores.

Purpose of the Study:

• To develop and validate a predictive "renal risk score" for progressive CKD.
• To identify key predictors of renal function decline in the general population.
• To create a clinically applicable tool for risk stratification.

Main Methods:

• Prospective, population-based cohort study (PREVEND).
• Inclusion of participants with serial estimated glomerular filtration rate (eGFR) measurements.
• Logistic regression and receiver operating characteristic (ROC) curve analysis for model development and validation.

Main Results:

• A prediction model incorporating baseline eGFR, age, urinary albumin excretion, systolic blood pressure, C-reactive protein, and hypertension was developed.
• The model demonstrated strong discriminative ability with an area under the ROC curve of 0.84 after internal validation.
• A clinical score chart was created, maintaining a high discriminative value (ROC AUC 0.83).

Conclusions:

• The developed renal risk score exhibits high internal validity.
• This score is a valuable tool for identifying individuals at increased risk of progressive CKD.
• The score facilitates early intervention and personalized management strategies for kidney disease.