Assessment of hair TB drug levels among tuberculosis patients: A study to monitor exposure, adherence and treatment outcomes
Background: Tuberculosis is still a major problem in Uganda. Therapeutic drug monitoring for tuberculosis (TB) improves treatment outcomes and mitigates emergency of drug resistance. Despite availability of drugs, poor adherence and sub-optimal drug levels are major barriers to successful treatment outcomes, especially in sub-Saharan Africa countries. Limitations to adherence may be overcome by directly observed therapy (DOT), but this is mostly feasible for inpatients yet majority of TB patients especially in Uganda are treated as outpatients with self administered treatment (SAT)
Assessments of plasma drug levels can shade light on adherence and exposure but require daily phlebotomy for each dose, a cold chain and represent a small window of exposure. Hair assays of antiretroviral (ARV) drugs are the strongest independent predictor of virologic response in HIV-infected patients. There is a linear relationship between ARV dose and hair concentration. This hair drug level relationship can be extrapolated to anti-TB drugs to monitor adherence and treatment outcomes.
Aim: To assess the correlation between hair / plasma drug levels of ERHZ and TB treatment outcomes
Methods: This will be a mixed design of cross-sectional and cohort studies of confirmed TB patients both HIV infected and uninfected being treated with the standard TB regimen (2ERHZ/4RH).Each specific objective will be answered through a sub study.
Sub-study 1: Acceptability of hair harvest as a method of TB therapeutic drug monitoring.
Sub-study 2: Correlation between hair drug levels, plasma exposures, DOT/SAT and adherence.
Sub-study 3: correlation between hair/ plasma drug levels of ERHZ, sputum culture conversion and adverse drug reactions.
Sub-study 4:Correlation between HIV infection, hair and plasma drug levels in TB patients taking ERHZ.
Expected results: Correlation between TB hair drug levels,adherence and treatment outcomes could be observed. We might identify the best methods for monitoring; exposure and adherence that can replace the logistically challenging DOT.
Conclusion: There is an intuitive need for tools that can monitor treatment adherence and exposure, identifying individuals at highest risk of TB poor treatment outcomes who may need further intervention.