Validation of standardized creatinine and cystatin C GFR estimating equations in a large multicentre European cohort of children
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Background: Most validations of paediatric glomerular filtration rate (GFR) estimating equations using standardized creatinine (CR) and cystatin C (CYS) assays have comprised relatively small cohorts, which makes accuracy across subgroups of GFR, age, body mass index (BMI) and gender uncertain. To overcome this, a large cohort of children referred for GFR determination has been established from several European medical centres. Methods: Three thousand four hundred eight measurements of GFR (mGFR) using plasma clearance of exogenous substances were performed in 2218 children aged 2–17 years. Validated equations included Schwartz-2009CR/2012CR/CYS/CR+CYS, FASCR/CYS/CR+CYS, LMRCR, Schwartz-LyonCR, BergCYS, CAPACYS, CKD-EPICYS, AndersenCR+CYS and arithmetic means of the best single-marker equations in explorative analysis. Five metrics were used to compare the performance of the GFR equations: bias, precision and three accuracy measures including the percentage of GFR estimates (eGFR) within ± 10% (P10) and ± 30% (P30) of mGFR. Results: Three of the cystatin C equations, BergCYS, CAPACYS and CKD-EPICYS, exhibited low bias and generally satisfactory accuracy across all levels of mGFR; CKD-EPICYS had more stable performance across gender than the two other equations. Among creatinine equations, Schwartz-LyonCR had the best performance but was inaccurate at mGFR < 30 mL/min/1.73 m2 and in underweight patients. Arithmetic means of the best creatinine and cystatin C equations above improved bias compared to the existing composite creatinine+cystatin C equations. Conclusions: The present study strongly suggests that cystatin C should be the primary biomarker of choice when estimating GFR in children with decreased GFR. Arithmetic means of well-performing single-marker equations improve accuracy further at most mGFR levels and have practical advantages compared to composite equations.
|Research areas and keywords||
Subject classification (UKÄ) – MANDATORY
|Publication status||Published - 2019 Feb 4|