A Predictive Model for Progression of CKD to Kidney Failure Based on Routine Laboratory Tests.
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Article de revue
Este ítem está publicado en
American Journal of Kidney Diseases. 2022-02-01
Resumen en inglés
Stratification of chronic kidney disease (CKD) patients at risk for progressing to kidney failure requiring kidney replacement therapy (KFRT) is important for clinical decision-making and trial enrollment. Four independent ...Leer más >
Stratification of chronic kidney disease (CKD) patients at risk for progressing to kidney failure requiring kidney replacement therapy (KFRT) is important for clinical decision-making and trial enrollment. Four independent prospective observational cohort studies. The development cohort comprised 4,915 CKD patients, and 3 independent validation cohorts comprised a total of 3,063. Patients were observed for approximately 5 years. 22 demographic, anthropometric, and laboratory variables commonly assessed in CKD patients. Progression to KFRT. A least absolute shrinkage and selection operator (LASSO) Cox proportional hazards model was fit to select laboratory variables that best identified patients at high risk for KFRT. Model discrimination and calibration were assessed and compared against the 4-variable Tangri (T4) risk equation both in a resampling approach within the development cohort and in the validation cohorts using cause-specific concordance (C) statistics, net reclassification improvement, and calibration graphs. The newly derived 6-variable risk score (Z6) included serum creatinine, albumin, cystatin C, and urea, as well as hemoglobin and the urinary albumin-creatinine ratio. In the the resampling approach, Z6 achieved a median C statistic of 0.909 (95% CI, 0.868-0.937) at 2 years after the baseline visit, whereas the T4 achieved a median C statistic of 0.855 (95% CI, 0.799-0.915). In the 3 independent validation cohorts, the Z6C statistics were 0.894, 0.921, and 0.891, whereas the T4C statistics were 0.882, 0.913, and 0.862. The Z6 was both derived and tested only in White European cohorts. A new risk equation based on 6 routinely available laboratory tests facilitates identification of patients with CKD who are at high risk of progressing to KFRT.< Leer menos
Palabras clave en inglés
Chronic kidney disease (CKD)
CKD progression
end-stage kidney disease (ESKD)
German Chronic Kidney Disease study
kidney disease trajectory
kidney failure requiring kidney replacement therapy (KFRT)
kidney failure risk equation
machine learning
risk equation
Centros de investigación