Understanding the impact of pandemics on long-term medication adherence: directly observed therapy in a tuberculosis treatment cohort pre- and post-COVID-19 lockdowns.

BACKGROUND: The COVID-19 pandemic negatively impacted tuberculosis (TB) treatment services, including directly observed therapy (DOT) programs used to promote medication adherence. We compared DOT adherence embedded in a research study before and after COVID-19 lockdowns in South Africa. METHODS: We analyzed data from 263 observational study participants undergoing drug susceptible (DS)-TB DOT between May 2017 to March 2022. Participants enrolled before October 2019 were considered 'pre-COVID-19' and those enrolled after September 2020 were considered 'post-COVID-19 lockdown groups. Negative binomial regression models were used to compare DOT non-adherence rates between the two lockdown groups. We then conducted a sensitivity analysis which only included participants enrolled in the immediate period following the first COVID-19 lockdown. RESULTS: DOT non-adherence rate was higher in the post-COVID-19 lockdown group (aIRR = 1.42, 95% CI = 1.04-1.96; p = 0.028) compared to pre-COVID-19 lockdown period, adjusting for age, sex, employment status, household hunger, depression risk, and smoked substance use. DOT non-adherence was highest immediately following the initial lockdown (aIRR = 1.74, 95% CI = 1.17-2.67; p = 0.006). CONCLUSION: The COVID-19 lockdowns adversely effected adherence to TB DOT in the period after lockdowns were lifted. The change in DOT adherence persisted even after adjusting for socioeconomic and behavioral variables. We need a better understanding of what treatment adherence barriers were exacerbated by COVID-19 lockdowns to improve outcomes in post-pandemic times. TRIAL REGISTRATION: ClinicalTrials.gov Registration Number: NCT02840877. Registered on 19 July 2016.

The impact of alcohol and illicit substance use on the pharmacokinetics of first-line TB drugs.

BACKGROUND: In South Africa, an estimated 11% of the population have high alcohol use, a major risk factor for TB. Alcohol and other substance use are also associated with poor treatment response, with a potential mechanism being altered TB drug pharmacokinetics. OBJECTIVES: To investigate the impact of alcohol and illicit substance use on the pharmacokinetics of first-line TB drugs in participants with pulmonary TB. METHODS: We prospectively enrolled participants ≥15 years old, without HIV, and initiating drug-susceptible TB treatment in Worcester, South Africa. Alcohol use was measured via self-report and blood biomarkers. Other illicit substances were captured through a urine drug test. Plasma samples were drawn 1 month into treatment pre-dose, and 1.5, 3, 5 and 8 h post-dose. Non-linear mixed-effects modelling was used to describe the pharmacokinetics of rifampicin, isoniazid, pyrazinamide and ethambutol. Alcohol and drug use were tested as covariates. RESULTS: The study included 104 participants, of whom 70% were male, with a median age of 37 years (IQR 27-48). Alcohol use was high, with 42% and 28% of participants having moderate and high alcohol use, respectively. Rifampicin and isoniazid had slightly lower pharmacokinetics compared with previous reports, whereas pyrazinamide and ethambutol were consistent. No significant alcohol use effect was detected, other than 13% higher ethambutol clearance in participants with high alcohol use. Methaqualone use reduced rifampicin bioavailability by 19%. CONCLUSION: No clinically relevant effect of alcohol use was observed on the pharmacokinetics of first-line TB drugs, suggesting that poor treatment outcome is unlikely due to pharmacokinetic alterations. That methaqualone reduced rifampicin means dose adjustment may be beneficial.

Methods for handling missing data in serially sampled sputum specimens for mycobacterial culture conversion calculation.

BACKGROUND: The occurrence and timing of mycobacterial culture conversion is used as a proxy for tuberculosis treatment response. When researchers serially sample sputum during tuberculosis studies, contamination or missed visits leads to missing data points. Traditionally, this is managed by ignoring missing data or simple carry-forward techniques. Statistically advanced multiple imputation methods potentially decrease bias and retain sample size and statistical power. METHODS: We analyzed data from 261 participants who provided weekly sputa for the first 12 weeks of tuberculosis treatment. We compared methods for handling missing data points in a longitudinal study with a time-to-event outcome. Our primary outcome was time to culture conversion, defined as two consecutive weeks with no Mycobacterium tuberculosis growth. Methods used to address missing data included: 1) available case analysis, 2) last observation carried forward, and 3) multiple imputation by fully conditional specification. For each method, we calculated the proportion culture converted and used survival analysis to estimate Kaplan-Meier curves, hazard ratios, and restricted mean survival times. We compared methods based on point estimates, confidence intervals, and conclusions to specific research questions. RESULTS: The three missing data methods lead to differences in the number of participants achieving conversion; 78 (32.8%) participants converted with available case analysis, 154 (64.7%) converted with last observation carried forward, and 184 (77.1%) converted with multiple imputation. Multiple imputation resulted in smaller point estimates than simple approaches with narrower confidence intervals. The adjusted hazard ratio for smear negative participants was 3.4 (95% CI 2.3, 5.1) using multiple imputation compared to 5.2 (95% CI 3.1, 8.7) using last observation carried forward and 5.0 (95% CI 2.4, 10.6) using available case analysis. CONCLUSION: We showed that accounting for missing sputum data through multiple imputation, a statistically valid approach under certain conditions, can lead to different conclusions than naïve methods. Careful consideration for how to handle missing data must be taken and be pre-specified prior to analysis. We used data from a TB study to demonstrate these concepts, however, the methods we described are broadly applicable to longitudinal missing data. We provide valuable statistical guidance and code for researchers to appropriately handle missing data in longitudinal studies.

Alcohol and Tobacco Use in a Tuberculosis Treatment Cohort during South Africa's COVID-19 Sales Bans: A Case Series.

BACKGROUND: South Africa temporarily banned alcohol and tobacco sales for about 20 weeks during the COVID-19 lockdown. We described changes in alcohol and tobacco consumption after implementation of these restrictions among a small number of participants in a tuberculosis treatment cohort. METHOD: The timeline follow-back procedure and Fägerstrom test for nicotine dependence was used to collect monthly alcohol and tobacco use information. We report changes in heavy drinking days (HDD), average amount of absolute alcohol (AA) consumed per drinking day, and cigarettes smoked daily during the alcohol and tobacco ban compared to use prior to the ban. RESULTS: Of the 61 participants for whom we have pre-ban and within-ban alcohol use information, 17 (27.9%) reported within-ban alcohol use. On average, participants reported one less HDD per fortnight (interquartile range (IQR): -4, 1), but their amount of AA consumed increased by 37.4 g per drinking occasion (IQR: -65.9 g, 71.0 g). Of 53 participants who reported pre-ban tobacco use, 17 (32.1%) stopped smoking during the ban. The number of participants smoking >10 cigarettes per day decreased from 8 to 1. CONCLUSIONS: From these observations, we hypothesize that policies restricting alcohol and tobacco availability seem to enable some individuals to reduce their consumption. However, these appear to have little effect on the volume of AA consumed among individuals with more harmful patterns of drinking in the absence of additional behavior change interventions.