Formulae recently proposed to estimate renal glomerular filtration rate improve the prediction of carboplatin clearance

Purpose While doses of carboplatin are mostly individualized according to the Calvert equation based on estimated Glomerular Filtration Rate (eGFR), there is still uncertainty regarding the best formula to predict GFR. Since Janowitz et al. recently proposed a new equation predicting GFR in cancer patients, we aimed to compare this equation to other carboplatin clearance (carboCL) predicting formulae. Methods The actual carboCL of 491 patients was compared to predicted carboCL according to the Calvert formula using several equations to predict GFR (Janowitz, Cockcroft-Gault, MDRD, CKD-EPI, CKD-EPI with cystatin C (CKD-EPI-cysC)); and according to two others that directly predict carboCL (Chatelut and Thomas). The formulae were compared on Mean Percentage Error (MPE), Mean Absolute Percentage Error (MAPE) and percentage of patients with a prediction error above 20% (P20). Results The MPE, MAPE and P20 were, respectively, within the ranges - 5.2 to + 5.9%; 14.0-21.2% and 23-46%. The MAPE and P20 of Calvert-CKD-EPI-cysC were the lowest. The performance of Calvert-CKD-EPI was better than that of other creatinine-based formulae although not significantly different from the Calvert-Janowitz formula. Among formulae based on creatinine only, Calvert-CKD-EPI and Calvert-Janowitz are the least influenced by patient characteristics. Conclusion Whereas CysC improves carboplatin CL prediction, the Calvert-CKD-EPI equation seems the most suitable creatinine-based formula to predict carboCL homogeneously in all subgroups of patients.