Optimal Sampling Strategies for Therapeutic Drug Monitoring of First-Line Tuberculosis Drugs in Patients with Tuberculosis

Abstract

Background: The 24-h area under the concentration-time curve (AUC₂₄)/minimal inhibitory concentration ratio is the best predictive pharmacokinetic/pharmacodynamic (PK/PD) parameter of the efficacy of first-line anti-tuberculosis (TB) drugs. An optimal sampling strategy (OSS) is useful for accurately estimating AUC₂₄; however, OSS has not been developed in the fed state or in the early phase of treatment for first-line anti-TB drugs.

Methods: An OSS for the prediction of AUC₂₄ of isoniazid, rifampicin, ethambutol and pyrazinamide was developed for TB patients starting treatment. A prospective, randomized, crossover trial was performed during the first 3 days of treatment in which first-line anti-TB drugs were administered either intravenously or in fasting or fed conditions. The PK data were used to develop OSS with best subset selection multiple linear regression. The OSS was internally validated using a jackknife analysis and externally validated with other patients from different ethnicities and in a steady state of treatment.

Results: OSS using time points of 2, 4 and 8 h post-dose performed best. Bias was < 5% and imprecision was < 15% for all drugs except ethambutol in the fed condition. External validation showed that OSS_2-4-8 cannot be used for rifampicin in steady state conditions.

Conclusion: OSS at 2, 4 and 8 h post-dose enabled an accurate and precise prediction of AUC₂₄ values of first-line anti-TB drugs in this population.

Trial registration: ClinicalTrials.gov (NCT02121314).