Validation of the Klinrisk chronic kidney disease progression model in the FIDELITY population.

Abstract

Chronic kidney disease (CKD) affects >800 million individuals worldwide and is often underrecognized. Early detection, identification and treatment can delay disease progression. Klinrisk is a proprietary CKD progression risk prediction model based on common laboratory data to predict CKD progression. We aimed to externally validate the Klinrisk model for prediction of CKD progression in FIDELITY (a prespecified pooled analysis of two finerenone phase III trials in patients with CKD and type 2 diabetes). In addition, we sought to identify evidence of an interaction between treatment and risk. The validation cohort included all participants in FIDELITY up to 4years. The primary and secondary composite outcomes included a ≥40% decrease in estimated glomerular filtration rate (eGFR) or kidney failure, and a ≥57% decrease in eGFR or kidney failure. Prediction discrimination was calculated using area under the receiver operating characteristic curve (AUC). Calibration plots were calculated by decile comparing observed with predicted risk. At time horizons of 2 and 4years, 993 and 1795 patients experienced a primary outcome event, respectively. The model predicted the primary outcome accurately with an AUC of 0.81 for 2years and 0.86 for 4years. Calibration was appropriate at both 2 and 4years, with Brier scores of 0.067 and 0.115, respectively. No evidence of interaction between treatment and risk was identified for the primary composite outcome (P=.31). Our findings demonstrate the accuracy and utility of a laboratory-based prediction model for early identification of patients at the highest risk of CKD progression.