Limited sampling models for CPT-11, SN-38, and SN-38 glucuronide

Purpose: We developed limited sampling models (LSMs) for predicting the are a under the curve (AUC) of irinotecan (CPT-11) and its metabolites SN-38 an d SN-38 glucuronide (SN-38G). Patients and methods: Regression models were developed based on data from a phase I clinical trial involving 34 patients with advanced solid tumor malignancies who received CPT-11 as a 90-min inf usion on an every 3-week dosing schedule. Multiple stepwise regression proc edures were supplemented by all possible subsets regression analysis. Alter native clinically based and empirically derived LSMs were determined via mo del validation assessment including bootstrap simulation testing. Results: The best LSMs for CPT-11 AUC included concentrations recorded at the end of infusion and 4 h later with an option to include a blood draw at 7.5 h fro m infusion start. For SN-38 and SN-38G AUC, optimal LSMs included the addit ional metabolite concentration at 48 h after infusion. The LSMs were able t o predict most patient AUC values to within 10% of the true value. Conclusi on: CPT-11 AUC can be modeled with acceptable accuracy using only two or th ree plasma concentration time-points. A variety of LSM alternatives provide d comparable accuracy in predicting AUC. Given the wide variety of LSM alte rnatives, clinical considerations and patient burden become more important performance parameters than statistical considerations for the choice of ti me-points in constructing LSMs.