The Impact of Alcohol Consumption on Tuberculosis Treatment Outcomes

Not Applicable

Completed

Conditions: Alcohol Consumption
Tuberculosis
Treatment Adverse Effect

Interventions: Behavioral: DOT Adherence Monitoring

Registration Number: NCT02840877

Lead Sponsor: Boston Medical Center

Brief Summary: After HIV/AIDS, tuberculosis (TB) remains the second leading cause of death due to an infectious disease globally. Retrospective studies from many countries, including the United States and South Africa, have consistently reported that in addition to having a higher burden of TB disease, patients with problem alcohol use have worse TB treatment outcomes. This prospective study will attempt to clarify both behavioral and biologic causal mechanisms underlying the deleterious effects of problem alcohol use on TB treatment response.

Detailed Description: A major knowledge gap is the degree to which poor treatment outcomes in alcohol-abusing patients are due to noncompliance alone. Problem alcohol use impacts on retention in care and adherence to daily TB treatment. Poor medication adherence and increased default from TB care have been documented for patients consuming alcohol regularly in several countries. Yet there has been no research to identify reasons (beyond adherence) for these poorer outcomes among patients with problem alcohol use. A key barrier to understanding the persistent biologic effect of alcohol on TB disease is inadequate data on adherence, including detailed data on daily adherence (or number of missed doses of medication). Research combining better approaches to alcohol ascertainment and adherence monitoring is needed to advance understanding of the pathways by which alcohol use and TB disease interact.

Aim 1: To (i) examine the associations between problem alcohol use and TB treatment outcomes, and (ii) demonstrate that these associations persist independent of adherence to TB treatment.

Aim 2: To evaluate the effect of problem alcohol use on the pharmacokinetics (PK)/pharmacodynamics (PD) of TB drugs.

Aim 3: We will use existing samples and data and continue to collect samples and data to (A) evaluate Mtb diversity in host, its dynamics overtime and in a specific set of drug resistance, drug tolerance, virulence and immune regulator genes, for evidence of directional and diversifying selection. We will (B) also evaluate how Mtb diversity and genes under selection associate with time-to culture conversion (three consecutive weeks of negative growth) and negative treatment outcomes, adherence, HIV, diabetes mellitus (DM), and substance use. We will (C) leverage MIC and sequence data from TRUST. We will combine these with a large public Mtb MIC and WGS dataset enriched for high-level antibiotic resistance generated by studies that include the NIAID funded Harvard TB Centers of Excellence for Translational Research (CETR). We will train an in silico MIC predictor and probe interactions between mutations and the Mtb lineage on a genome-wide scale. The current TRUST investigators, as well as Dr. Maha Farhat, Harvard Medical School will oversee this aim.

Aim 4: A) To compare rates of dysglycemia (both hyperglycemia and hypoglycemia) in people living with HIV (PLWH) and HIV-uninfected persons receiving TB treatment in order to assess changes in blood glucose levels from study enrollment by HIV status and how alcohol use mediates the relationship; and B) to assess the role stress, inflammation and alcohol consumption play in relation to blood sugar levels in PLWH and HIV-uninfected individuals and to assess epigenetic modifications at DNA sites known to be involved in TB risk and neutrophil, monocyte, T and B cell function.

Culture-positive, pulmonary TB patients will be recruited in Worcester, South Africa, and followed over an 18-month period. Patients will complete an interviewer-administered questionnaire on their alcohol use and other health-related behaviors, and their recent alcohol use will be confirmed using a biomarker (phosphatidylethanol). Chest radiographs, sputum smears and culture, and blood samples will be collected to compare the biology of treatment response in patients with and without problem alcohol use. During the 6-month treatment period, smart mobile-phone technology will be used to document daily drug adherence by trained community workers. Serial measures of alcohol intake and serial sputa isolates will be collected to assess treatment response and TB drug side effects will be recorded. In addition, intensive PK/PD studies of isoniazid, rifampin, ethambutol, and pyrazinamide will be performed in 200 HIV-seronegative patients. The full cohort will be followed for 12 months post-treatment to examine long-term TB outcomes, including relapse and death.

Recruitment & Eligibility

Status: COMPLETED

Sex: All

Target Recruitment: 303

Inclusion Criteria

at least 15 years old
initiating TB treatment in South Africa
expect to remain in the local area for the next 2 years
agree to comply with all study requirements, including provision of contact information and attendance at all study appointments
provide written, informed consent to participate in the study if ≥18 years of age or written assent and parental consent if <18 years.

Exclusion Criteria

they have multidrug-resistant (MDR) TB (RIF resistance will be known at screening from Xpert MTB/RIF)
they have a contra-indication to start on standard 4-drug therapy
they are pregnant at study enrollment
they are HIV seropositive for aim 2 only

Study & Design

Study Type: INTERVENTIONAL

Study Design: SINGLE_GROUP

Arm && Interventions

Group	Intervention	Description
DOT Adherence Monitoring	DOT Adherence Monitoring	Daily adherence monitoring by study-employed directly observed therapy (DOT) worker on weekdays throughout the course of TB therapy

Primary Outcome Measures

Name	Time	Method
Time to Culture Conversion	12 weeks	Time to sterilization/culture conversion during the first twelve weeks of treatment in patients with problem alcohol use compared to those without
Area Under Curve (AUC)	4 weeks	Individual patient steady state 24-hour area under curve (AUC) of isoniazid, rifampin, pyrazinamide, and ethambutol
Cmax	4 weeks	Peak concentrations (Cmax) of isoniazid, rifampin, pyrazinamide, and ethambutol in patients with problem alcohol use compared to those without

Secondary Outcome Measures

Name	Time	Method
Side Effects to TB Drugs	6 months	Nember and percentage of patients who develop side effects to the TB drugs in patients with problem alcohol use compared to those without
Poor Treatment Outcome	18 months	Number and percent of participants that had favorable (defined as cured, treatment completed) and unfavorable (defined as treatmentfailure, death, relapse) TB outcomes. The 'other' category is defined as the treatment defaulted, was extended, participant moved or was transferred).