A 4-Variable Model to Predict Cardio-Kidney Events and Mortality in Chronic Kidney Disease: The Chronic Renal Insufficiency Cohort (CRIC) Study.

Current prognostic models for chronic kidney disease (CKD) are complex and were designed to predict a single outcome. We aimed to develop and validate a simple and parsimonious prognostic model to predict cardio-kidney events and mortality. Patients from the CRIC Study (n = 3,718) were randomly divided into derivation (n = 2,478) and validation (n = 1,240) cohorts. Twenty-nine candidate variables were preselected. Multivariable Cox regression models were developed using stepwise selection for various cardio-kidney endpoints, namely, (i) the primary composite outcome of 50% decline in estimated glomerular filtration rate (eGFR) from baseline, end-stage renal disease, or cardiovascular (CV) mortality; (ii) hospitalization for heart failure (HHF) or CV mortality; (iii) 3-point major CV endpoints (3P-MACE); (iv) all-cause death. During a median follow-up of 9 years, the primary outcome occurred in 977 patients of the derivation cohort and 501 patients of the validation cohort. Log-transformed N-terminal pro-B-type natriuretic peptide (NT-proBNP), log-transformed high-sensitive cardiac troponin T (hs-cTnT), log-transformed albuminuria, and eGFR were the dominant predictors. The primary outcome risk score discriminated well (c-statistic = 0.83) with a proportion of events of 11.4% in the lowest tertile of risk and 91.5% in the highest tertile at 10 years. The risk model presented good discrimination for HHF or CV mortality, 3P-MACE, and all-cause death (c-statistics = 0.80, 0.75, and 0.75, respectively). The 4-variable risk model achieved similar c-statistics for all tested outcomes in the validation cohort. The discrimination of the 4-variable risk model was mostly superior to that of published models. The combination of NT-proBNP, hs-cTnT, albuminuria, and eGFR in a single 4-variable model provides a unique individual prognostic assessment of multiple cardio-kidney outcomes in CKD.

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