Risk factors for early TB treatment interruption among newly diagnosed patients in Malaysia

Characteristics, predictors and consequences of tuberculosis treatment interruption: A multicentre retrospective cohort study

OBJECTIVES

Treatment interruption is associated with poor tuberculosis (TB) treatment outcomes and increased drug resistance. To address the issue, we aimed to investigate the characteristics, predictors and consequences of treatment interruption.

METHODS

We conducted a retrospective cohort study by retrieving 4 years (2018-2021) of TB patients' records at 10 public health clinics in Sarawak, Malaysia. Adult patients (≥18 years) with drug-susceptible TB were selected. Treatment interruption was defined as ≥2 weeks of cumulative interruption during treatment. The Chi-square test, Mann-Whitney U test, Kaplan-Meier and Cox proportional hazards regression were used to analyse the data, with p < 0.05 being considered statistically significant.

RESULTS

Out of 2953 eligible patients, 475 (16.1%) experienced TB treatment interruption. Interruptions were most frequent during the intensive phase (46.9%, n = 223), with the greatest risk within the first 4 weeks of treatment. The median time to interruption was 2 weeks in the intensive phase and the cumulative interruption probability at the end of the intensive phase was 12.9%. Notably, treatment interruption occurred during both intensive and continuation phases for 144 patients (30.3%), while the remaining 108 (22.7%) experienced interruptions only during the continuation phase with a median time to interruption of 16 weeks. Three predictors were identified to increase the risk of treatment interruption: adverse drug reaction (aHR = 8.53, 95% Cl: 6.73-10.82), smoking (aHR = 2.67, 95% Cl: 2.03-3.53) and illicit drug use (aHR = 1.88, 95% Cl: 1.03-3.45). Conversely, underlying diabetes was associated with a reduced likelihood of treatment interruption (aHR = 0.72, 95% Cl: 0.58-0.90). Treatment interruption led to significant differences in treatment restarts (62.3% vs. 0.7%), changes in medications (47.8% vs. 4.9%), prolonged treatment duration (247 days [IQR = 105] vs. 194 days [IQR = 44.3]) and lower successful outcomes (86.5% vs. 99.9%).

CONCLUSION

Understanding the temporal characteristics, predictors and negative consequences of treatment interruption can guide the development of time-relevant approaches to mitigate the problem.

Predictors, mortality, and health outcomes of intensive phase non-adherence to a regimen in patients with drug-susceptible tuberculosis: a nationwide linkage database

OBJECTIVES

The clinical importance of adhering to the regimen in tuberculosis patients has been widely investigated, but most studies were conducted in controlled settings and in limited populations. We aimed to measure the level of real-world adherence during intensive phase and investigate the predictors and the risk of mortality and health outcomes of intensive phase non-adherence in tuberculosis patients.

STUDY DESIGN

We conducted a nationwide cohort study by linking the Korean National Tuberculosis Surveillance System and the National Health Information Database.

METHODS

We included all incident drug-susceptible tuberculosis patients who initiated the regimens recommended by the World Health Organization from 2013 to 2018. Adherence was measured using the proportion of days covered (poor [<50%], moderate [50%-79%], and high [≥80%]). We used logistic regression model to assess predictors and the Cox proportional hazard model to evaluate the risk of mortality and health outcomes with intensive phase non-adherence.

RESULTS

Of 46,818 patients, there were 8% and 11% with poor and moderate adherent groups, respectively. Age ≥45 years, insulin use, and history of renal failure were predictors of non-adherence. Compared with high adherent group, poor and moderate adherent groups were associated with a substantial risk of mortality (poor: hazard ratio, 2.14 [95% confidence interval, 1.95-2.34]; moderate: 1.76 [1.62-1.92]). Similar trends were observed for health outcomes. Stratified analyses showed a higher risk of mortality in patients with medical aid, low income, and history of renal failure, systematic corticosteroids, and immunomodulators.

CONCLUSIONS

Non-adherence during intensive phase increased mortality risk by twofold, underscoring targeted intervention for high-risk population, including advanced diabetes, and immunocompromised patients.

Risk factors for poor engagement with a smart pillbox adherence intervention among persons on tuberculosis treatment in Ethiopia

BACKGROUND

Non-adherence to tuberculosis treatment increases the risk of poor treatment outcomes. Digital adherence technologies (DATs), including the smart pillbox (EvriMED), aim to improve treatment adherence and are being widely evaluated. As part of the Adherence Support Coalition to End TB (ASCENT) project we analysed data from a cluster-randomised trial of DATs and differentiated care in Ethiopia to examine individual-factors for poor engagement with the smart pillbox.

METHODS

Data were obtained from a cohort of trial participants with drug-sensitive tuberculosis (DS-TB) whose treatment started between 1 December 2020 and 1 May 2022, and who were using the smart pillbox. Poor engagement with the pillbox was defined as (i) > 20% days with no digital confirmation and (ii) the count of days with no digital confirmation, and calculated over a two evaluation periods (56-days and 168-days). Logistic random effects regression was used to model > 20% days with no digital confirmation and negative binomial random effects regression to model counts of days with no digital confirmation, both accounting for clustering of individuals at the facility-level.

RESULTS

Among 1262 participants, 10.8% (133/1262) over 56-days and 15.8% (200/1262) over 168-days had > 20% days with no digital confirmation. The odds of poor engagement was less among participants in the higher stratum of socio-economic position (SEP) over 56-days. Overall, 4,689/67,315 expected doses over 56-days and 18,042/199,133 expected doses over 168-days were not digitally confirmed. Compared to participants in the poorest SEP stratum, participants in the wealthiest stratum had lower rates of days not digitally confirmed over 168-days (adjusted rate ratio [RRa]:0.79; 95% confidence interval [CI]: 0.65, 0.96). In both evaluation periods (56-days and 168-days), HIV-positive status (RRa:1.29; 95%CI: 1.02, 1.63 and RRa:1.28; 95%CI: 1.07, 1.53), single/living independent (RRa:1.31; 95%CI: 1.03, 1.67 and RRa:1.38; 95%CI: 1.16, 1.64) and separated/widowed (RRa:1.40; 95%CI: 1.04, 1.90 and RRa:1.26; 95%CI: 1.00, 1.58) had higher rates of counts of days with no digital confirmation.

CONCLUSION

Poorest SEP stratum, HIV-positive status, single/living independent and separated/ widowed were associated with poor engagement with smart pillbox among people with DS-TB in Ethiopia. Differentiated care for these sub-groups may reduce risk of non-adherence to TB treatment.

Silicosis as a predictor of tuberculosis mortality and treatment failure and need for incorporation in differentiated TB care models in India

BACKGROUND

Differentiated tuberculosis (TB) care is an approach to improve treatment outcomes by tailoring TB management to the particular needs of patient groups based on their risk profile and comorbidities. In silicosis-prone areas, the coexistence of TB and silicosis may exacerbate treatment outcomes. The objective of the study was to determine predictors of TB-related mortality, treatment failure, and loss to follow-up in a silicosis-prone region of western India.

METHODS

A retrospective cohort was conducted among 2748 people with TB registered between January 2006 and February 2022 in Khambhat, a silicosis-prone block in western India. Death, treatment failure, and loss to follow up were the outcome variables. The significant predictors of each outcome variable were determined using multivariable logistic regression and reported as adjusted odds ratios (aOR) with 95% confidence intervals (CIs).

RESULTS

In the cohort of 2,748 people with TB, 5% presented with silicosis, 11% succumbed to the disease, 5% were lost to follow-up during treatment, and 2% encountered treatment failure upon completion of therapy. On multivariable logistic regression, concomitant silicosis [aOR 2.3 (95% CI 1.5-3.5)], advancing age [aOR 1.03 (95% CI 1.02-1.04)], male gender [aOR 1.4 (95% 1.1-1.9)], human immunodeficiency virus (HIV) positive [aOR 2.2 (95% 1.02-4.6)], and previous TB treatment [aOR 1.5 (95% CI 1.1-1.9)] significantly predicted mortality among people with TB. Concomitant silicosis [aOR 3 (95% CI 1.4-6.5)], previous TB treatment [aOR 3 (95% CI 2-6)], and multi-drug resistant TB [aOR 18 (95% CI 8-41)] were the significant predictors of treatment failure on adjusted analysis. Advancing age [aOR 1.012 (1.001-1.023)], diabetes [aOR 0.6 (0.4-0.8)], and multi-drug resistance [aOR 6 (95% CI 3-12)] significantly predicted loss to follow-up after adjusting for confounders.

CONCLUSIONS

Controlling silicosis might decrease TB mortality and treatment failure in silicosis-prone regions. The coexistence of HIV and silicosis may point to an increase in TB deaths in silicosis-prone areas. Silicosis should now be acknowledged as a major comorbidity of TB and should be included as one of the key risk factors in the differentiated TB care approach. Primary care physicians should have a high clinical suspicion for silicosis among individuals diagnosed with TB in silicosis-prone blocks.

Treatment of Tuberculosis and the Drug Interactions Associated With HIV-TB Co-Infection Treatment

Tuberculosis (TB) is a communicable disease that is a major source of illness, one of the ten causes of mortality worldwide, and the largest cause of death from a single infectious agent Mycobacterium tuberculosis. HIV infection and TB are a fatal combination, with each speeding up the progression of the other. Barriers to integrated treatment as well as safety concerns on the co-management of HIV- TB co-infection do exist. Many HIV TB co-infected people require concomitant anti-retroviral therapy (ART) and anti-TB medication, which increases survival but also introduces certain management issues, such as drug interactions, combined drug toxicities, and TB immune reconstitution inflammatory syndrome which has been reviewed here. In spite of considerable pharmacokinetic interactions between antiretrovirals and antitubercular drugs, when the pharmacological characteristics of drugs are known and appropriate combination regimens, dosing, and timing of initiation are used, adequate clinical response of both infections can be achieved with an acceptable safety profile. To avoid undesirable drug interactions and side effects in patients, anti TB treatment and ART must be closely monitored. To reduce TB-related mortality among HIV-TB co-infected patients, ART and ATT (Anti Tuberculosis Treatment) outcomes must improve. Clinical practise should prioritise strategies to promote adherence, such as reducing treatment duration, monitoring and treating adverse events, and improving treatment success rates, to reduce the mortality risk of HIV-TB co-infection.