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Comparison of methods to estimate glomerular filtration rate in paediatric oncology patients
Author(s) -
LlanosPaez Carolina C,
Staatz Christine,
Lawson Rachael,
Hennig Stefanie
Publication year - 2018
Publication title -
journal of paediatrics and child health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.631
H-Index - 76
eISSN - 1440-1754
pISSN - 1034-4810
DOI - 10.1111/jpc.13752
Subject(s) - medicine , renal function , creatinine , urology , univariate analysis , estimating equations , population , statistics , multivariate analysis , mathematics , maximum likelihood , environmental health
Aims Glomerular filtration rate ( GFR ) is estimated daily in paediatric oncology patients; however, few equations, particularly ones that do not include serum creatinine, have been evaluated in this population. We aimed to compare the predictive performance of different equations available to estimate GFR in paediatric oncology patients. Methods GFR was measured ( mGFR ) in paediatric oncology patients based on a chromium 51‐labeled ethylene diamine tetraacetic acid excretion test. GFR was estimated ( eGFR ) in these same patients using equations identified from the literature. mGFR and eGFR values were compared, and the predictive performance of various eGFR equations was assessed in terms of their bias, precision and accuracy. Results In total, 124 mGFR values ranging from 7 to 146 mL /min were available for analysis from 73 children. Twenty‐two equations were identified from the literature. The Flanders metadata equation displayed the lowest absolute bias (mean error of 0.9 mL /min) and the greatest precision (root mean square error of 13.1 mL /min). The univariate Schwartz equation predicted the highest percentage (81.5%) of eGFR values within 30% of mGFR values, and the Rhodin fat‐free mass equation predicted the highest percentage (37.1%) of eGFR values within 10% of mGFR values. Conclusions A number of equations were identified that could be used to estimate renal function in paediatric oncology patients; however, none was found to be highly accurate. The Flanders metadata equation and univariate Schwartz performed the best in this study, and we would suggest that these two equations may be used cautiously in paediatric oncology patients for clinical decision making, understanding their limitations.