Applicability of a Single Time Point Strategy for the Prediction of Area Under the Concentration Curve of Linezolid in Patients: Superiority of C(trough)- over C(max)-Derived Linear Regression Models

BACKGROUND AND OBJECTIVES: Linezolid, a oxazolidinone, was the first in class to be approved for the treatment of bacterial infections arising from both susceptible and resistant strains of Gram-positive bacteria. Since overt exposure of linezolid may precipitate serious toxicity issues, therapeutic drug monitoring (TDM) may be required in certain situations, especially in patients who are prescribed other co-medications. METHODS: Using appropriate oral pharmacokinetic data (single dose and steady state) for linezolid, both maximum plasma drug concentration (C(max)) versus area under the plasma concentration–time curve (AUC) and minimum plasma drug concentration (C(min)) versus AUC relationship was established by linear regression models. The predictions of the AUC values were performed using published mean/median C(max) or C(min) data and appropriate regression lines. The quotient of observed and predicted values rendered fold difference calculation. The mean absolute error (MAE), root mean square error (RMSE), correlation coefficient (r), and the goodness of the AUC fold prediction were used to evaluate the two models. RESULTS: The C(max) versus AUC and trough plasma concentration (C(trough)) versus AUC models displayed excellent correlation, with r values of >0.9760. However, linezolid AUC values were predicted to be within the narrower boundary of 0.76 to 1.5-fold by a higher percentage by the C(trough) (78.3 %) versus C(max) model (48.2 %). The C(trough) model showed superior correlation of predicted versus observed values and RMSE (r = 0.9031; 28.54 %, respectively) compared with the C(max) model (r = 0.5824; 61.34 %, respectively). CONCLUSIONS: A single time point strategy of using C(trough) level is possible as a prospective tool to measure the AUC of linezolid in the patient population.