Evaluation of LSSs
First, the regression equation was calculated from individual busulfan concentrations at each sampling point and the actual AUC0–∞ obtained from the pharmacokinetic modeling software. Second, the predicted AUC0–∞ was calculated from the regression equation and individual busulfan concentrations. Finally, the relationship between the predicted AUC0–∞and actual AUC0–∞ was evaluated using Pearson’s correlation coefficient (r2 ). LSSs using two or three busulfan sampling points were developed by multiple regression analysis. The precision of the predictive performance of busulfan AUCs was assessed by calculating the mean absolute percentage error (MAPE). Additionally, subgroup analysis was conducted based on body weight (<9, 9–16, 16–23, 23–34, and >34 kg). To verify the utility of LSSs in the present study, the predicted AUC0–∞ was calculated using the developed LSS and its predictive performance was evaluated in seven patients in a cohort separate from the first cohort that was used to develop the LSS. All statistical analyses were performed using SPSS Statistics ver.23 (SPSS IBM Japan, Tokyo, Japan).