Low Antituberculosis Drug Concentrations in HIV-Tuberculosis-Coinfected Adults with Low Body Weight: Is It Time To Update Dosing Guidelines?

Abstract

Antituberculosis drugs display large pharmacokinetic variability, which may be influenced by several factors, including body size, genetic differences, and drug-drug interactions. We set out to determine these factors, quantify their effect, and determine the dose adjustments necessary for optimal drug concentrations. HIV-infected Ugandan adults with pulmonary tuberculosis treated according to international weight-based dosing guidelines underwent pharmacokinetic sampling (1, 2, and 4 h after drug intake) 2, 8, and 24 weeks after treatment initiation. Between May 2013 and November 2015, we enrolled 268 patients (148 males) with a median weight of 53.5 (interquartile range [IQR], 47.5 to 59.0) kg and a median age of 35 (IQR, 29 to 40) years. Population pharmacokinetic modeling was used to interpret the data and revealed that patients weighing <55 kg achieved lower concentrations than those in higher weight bands for all drugs in the regimen. The models predicted that this imbalance could be solved with a dose increment of one fixed-dose combination (FDC) tablet for the weight bands of 30 to 37 and 38 to 54 kg. Additionally, the concomitant use of efavirenz increased isoniazid clearance by 24.1%, while bioavailability and absorption of rifampin and isoniazid varied up to 30% in patients on different formulations. Current dosing guidelines lead to lower drug exposure in patients in the lower weight bands. Simply adding one FDC tablet to current weight band-based dosing would address these differences in exposure and possibly improve outcomes. Lower isoniazid exposures due to efavirenz deserve further attention, as does the quality of currently used drug formulations of anti-TB drugs. (This study has been registered at ClinicalTrials.gov under identifier NCT01782950.).

Keywords: Monolix; antitubercular drugs; pharmacokinetics; pharmacometrics.

Copyright © 2019 American Society for Microbiology.

Figures

FIG 1

Visual prediction check for rifampin, isoniazid, ethambutol, and pyrazinamide. The dots represent the original data, and the middle line is the 50th percentile, while the upper and lower lines are the 5th and 95th percentiles of the original data. The shaded areas are the corresponding 95% confidence intervals for the same percentiles, as predicted by the model. The blue dots represent all observations above the limit of quantification, while the red ones represent the observation points that were below the limit of quantification (BLQ), as resimulated by the model.

FIG 2

Comparison of simulated exposures using the current dosing strategy versus the suggested dose increment. Shown are box plots of simulated AUC0–24 values using the final models for rifampin, isoniazid, pyrazinamide, and ethambutol stratified by weight band. The orange boxes represent the exposure achieved with the currently WHO-recommended dose, while the green ones represent the adjusted dose. The box represents median (central line) and interquartile ranges (box boundaries), while the whiskers are the 2.5th and 97.5th percentiles.

FIG 3

Isoniazid exposure across weight bands stratified by NAT2 rs1799930 genotype and efavirenz coadministration. Shown are box plots of simulated isoniazid AUC0–24 values using the final model. The panels show the values stratified by NAT2 rs1799930 genotype (left to right) and efavirenz coadministration (top to bottom). The orange boxes represent the exposure achieved with the currently WHO-recommended dose, while the green ones represent the adjusted dose. The box represents median (central line) and interquartile ranges (box boundaries), while the whiskers are the 2.5th and 97.5th percentiles.