title: Cyclosporine monitoring in patients with renal transplants: two- or three-point methods that estimate area under the curve are superior to trough levels in predicting drug exposure.
abstract: The recent introduction of a cyclosporine microemulsion demonstrating less pharmacokinetic variability than the conventional formulation offers the potential for accurately and precisely predicting area under the curve (AUC) with a limited-sampling monitoring strategy. This was studied based on the pharmacokinetic profiles from 55 stable patients with renal transplants who were observed on two occasions at steady state on both formulations. Multiple linear regression analyses were performed on a training dataset from 27 patients, in which combinations of cyclosporine concentrations drawn from 0 to 4 hours postdose were regressed against the full AUC over the dosing interval. Predictor regression equations used concentration combinations ranging from one-point (concentrations at 0, 1, 2, 3, or 4 hours) through five-points (all five concentrations 0 to 4 hours). The predictive performance of these equations was then assessed in the training group with data from a subsequent profiling occasion and in the remaining 28 patients who constituted an independent test group. Prediction bias (mean prediction error) and prediction precision (absolute prediction error) were quantified and compared between formulations. Correlations between predicted and actual AUC were consistently stronger for the microemulsion, suggesting the possibility of more accurate and precise predictions of exposure than from the conventional formulation. For both formulations, the one-point predictors rendered the lowest prediction precision, and predictive performance improved considerably when multiple-point predictors were used. Significantly higher precision and lower variability were observed with the microemulsion for most predictors in the both training and test groups. For the microemulsion, two-point (C0 + C1 or C0 + C2) and three-point (C0 + C1 + C2) predictors yielded relatively unbiased and precise exposure predictions, inasmuch as mean absolute prediction error was less than 10% and 5%, respectively. Hence, a two- or three-point method may provide a clinically important improvement over the use of trough levels in monitoring cyclosporine therapy in patients with renal transplants.
authors.affiliation: Faculty of Pharmaceutical Sciences, University of British Columbia, British Columbia Children's & Women's Hospitals, Vancouver, Canada.
authors.forename: D R
authors.initials: DR
authors.lastname: Primmett
authors.forename: M
authors.initials: M
authors.lastname: Levine
authors.forename: J M
authors.initials: JM
authors.lastname: Kovarik
authors.forename: E A
authors.initials: EA
authors.lastname: Mueller
authors.forename: P A
authors.initials: PA
authors.lastname: Keown
mesh_terms: D019540:Area Under Curve; D016572:Cyclosporine / Q000008:administration & dosage / Q000097:blood / Q000493:pharmacokinetics*; D004334:Drug Administration Schedule; D004339:Drug Compounding; D016903:Drug Monitoring / Q000379:methods* / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D007166:Immunosuppressive Agents / Q000008:administration & dosage / Q000097:blood / Q000493:pharmacokinetics*; D016030:Kidney Transplantation; D016014:Linear Models; D008297:Male; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity
chemical_list: D007166:Immunosuppressive Agents; D016572:Cyclosporine