Development of a risk prediction score and equation for chronic kidney disease: a retrospective cohort study

Chronic kidney disease (CKD) is a risk factor for end-stage renal disease and contributes to increased risk of cardiovascular disease morbidity and mortality. We aimed to develop a risk prediction score and equation for future CKD using health checkup data. This study included 58,423 Japanese participants aged 30-69 years, who were randomly assigned to derivation and validation cohorts at a ratio of 2:1. The predictors were anthropometric indices, life style, and blood sampling data. In derivation cohort, we performed multivariable logistic regression analysis and obtained the standardized beta coefficient of each factor that was significantly associated with new-onset CKD and assigned scores to each factor. We created a score and an equation to predict CKD after 5 years and applied them to validation cohort to assess their reproducibility. The risk score ranged 0-16, consisting of age, sex, hypertension, dyslipidemia, diabetes, hyperuricemia, and estimated glomerular filtration rate (eGFR), with area under the curve (AUC) of 0.78 for the derivation cohort and 0.79 for the validation cohort. The CKD incidence gradually and constantly increased as the score increased from ≤ 6 to ≥ 14. The equation consisted of the seven indices described above, with AUC of 0.88 for the derivation cohort and 0.89 for the validation cohort. We developed a risk score and equation to predict CKD incidence after 5 years in Japanese population under 70 years of age. These models had reasonably high predictivity, and their reproducibility was confirmed through internal validation.