Development and Validation of Limited Sampling Strategies for Estimation of Cyclosporine Area Under the Concentration–Time Curve in Hematopoietic Stem Cell Transplant Patients

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The aim of this study was to develop and validate limited sampling strategies for accurately predicting 12-hour area under the concentration–time curve (AUC0–12 h) to provide a practical method for more precise therapeutic drug monitoring of cyclosporine A in stem cell transplant patients. Steady-state cyclosporine blood concentrations were measured within a dosing interval (12 hours post administration) in 35 allogeneic bone marrow transplant patients receiving 238 mg (±117 mg) twice-daily dose of cyclosporine. Limited sampling strategies were developed by multiple linear regression analysis of relationship between cyclosporine A full AUC0–12 h values and different combinations of preselected blood concentrations. Validation of the estimating equations was done by a bootstrap-like cross-validation method. Cross-validation results showed that cyclosporine AUC0–12 h could be estimated using either 2 or 3 samples within the first 4 hours after drug administration with good accuracy and precision (absolute prediction error of less than 6.2%). The number of estimated area under the drug concentration–time curves within 15% of observed values was greater than 26 (74%) for models used predose concentration with either c2h and c4h or both. Most of the previously reported single-sample models showed a systematic error in predicting AUC0–12 h. Although a statistically significant difference in precision of prediction was seen between 3-sample model using c0, c2h, and c4h and 2-sample models (c0, c2h or c0, and c4h), such a difference (2%) could not be of clinical importance. Other 2-sample estimating equations (models using c2h with either c6h or c10h) with the same degree of precision appear to be less feasible clinically. Cyclosporine AUC0–12 h in bone marrow transplant patients could be estimated using 2 or 3 samples within the first 4 hours after drug administration with good accuracy and precision.

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