Adverse drug reactions & drug interactions in MDR-TB patients

The Adverse Effects of Tuberculosis Treatment: A Comprehensive Literature Review

Tuberculosis remains a significant public health challenge globally. The emergence of multidrug-resistant Mycobacterium tuberculosis strains presents one of the biggest hurdles in tuberculosis management. Both first- and second-line tuberculosis drugs are associated with common adverse reactions, which can lead to treatment interruptions and decreased adherence. In this article, we review the most commonly used drugs for the treatment of tuberculosis, focusing on the adverse reactions they may cause. We will examine the frequency and timeline of adverse drug reactions involving gastrointestinal, cardiac, neurological, nephrological, and cutaneous systems. Identifying patients at risk of developing those reactions is crucial for healthcare providers to implement monitoring strategies and manage complications effectively. In the review, we present the data about risk factors, management recommendations, and drug discontinuation rates as a result of side effects.

Adverse drug reactions and contributing factors in patients with drug-resistant tuberculosis: A 7-year retrospective cohort study in Addis Ababa, Ethiopia

Background

Drug-resistant tuberculosis poses a major global public health threat, with adverse drug reactions complicating treatment and contributing to mortality. In Ethiopia, although many patients with drug-resistant tuberculosis are receiving treatment, studies on adverse drug reactions and their contributing factors remain limited. This study aimed to assess the incidence of adverse drug reactions and contributing factors in patients on drug-resistant tuberculosis treatment in Addis Ababa, Ethiopia.

Methods

A facility-based, retrospective cohort study was conducted on patients with drug-resistant tuberculosis who were followed up in two major drug-resistant tuberculosis treatment sites, St. Peter's Specialized Hospital and the ALERT Comprehensive Specialized Hospital, in the years of 2017 to 2023. Records of the patients were reviewed throughout their treatment time. Information on any adverse drug reaction diagnosis, laboratory findings, clinical observations, type of second-line regimen, type and nature of the drug-resistant tuberculosis, presence of comorbidities such as Human Immune deficiency Virus, hypertension, diabetes mellitus, chronic obstructive pulmonary diseases, and asthma, and sociodemographic characteristics were abstracted from patients' charts and registries. The World Health Organization - Uppsala Monitoring Center (WHO-UMC) system was employed for standardized causality assessment of adverse drug reactions. Multivariate Cox regression analysis was employed to identify factors associated with adverse drug reactions. Survival among predictor variables was assessed using Kaplan-Meier (KM) curves. Adjusted hazard ratios (AHR) with their corresponding 95 % confidence intervals (CI) were estimated, and statistical significance was declared for a p-value < 0.05.

Result

A total of 292 patients with drug-resistant tuberculosis were included. The overall incidence of adverse drug reaction was 8.10 per 100 person-month (PM) (95 % CI: 7.02-9.36) during a total follow-up time of 2294 months. The most frequently reported adverse drug reactions were gastrointestinal disturbance (31.9 %), followed by peripheral neuropathy (21.9 %), and arthralgia (17.5 %). Factors associated with adverse drug reactions were hospitalization (AHR = 1.53, 95 % CI: 1.10-2. 13), baseline anemia (AHR = 1.58, 95 % CI: 1.16-2.17), the age group of 25-49 years (AHR = 1.53, 95 % CI: 1.05-2.21), and age greater than or equal to 50 years (AHR = 1.87, 95 % CI: 1.19-2.93). Good treatment outcome was observed in 76 % of cases.

Conclusion

In this study involving patients with drug resistant tuberculosis, over half of the participants encountered at least one adverse drug reactions. Patient admission, baseline anemia, and older age were identified as major factors associated with adverse drug reaction during multidrug resistant tuberculosis treatment. Particular emphasis should be placed on these susceptible groups to facilitate early prediction, prompt management, and the formulation of appropriate treatment regimens that address adverse drug reactions effectively.

The impact of maximum cross-sectional area of lesion on predicting the early therapeutic response of multidrug-resistant tuberculosis

BACKGROUND

Early evaluation of culture conversion after 6-month treatment of multidrug-resistant tuberculosis (MDR-TB) is vital for outcome prediction. This study aims to merge the maximum lesion cross-sectional area observed via computed tomography (CT) imaging during treatment to predict therapeutic response.

METHODS

We retrospectively involved MDR-TB patients who completed 6 months of treatment from two hospitals. Patients were categorized into culture conversation and no culture conversation groups based on sputum culture results. The data from the two hospitals were used as internal training and external testing cohorts, respectively. Logistic regression and random forest models were developed using the maximum lesion cross-sectional area and most important predictive features. The model performance was evaluated using the area under the curve (AUC), accuracy, sensitivity, specificity, and F1 score.

RESULTS

In the model without the maximum lesion cross-sectional area to predict culture conversion for MDR-TB after 6 months of treatment, logistic regression and random forest models achieved AUC values of 0.796 and 0.958, sensitivities of 0.725 and 0.993, and F1 scores of 0.803 and 0.957 in the training cohort, respectively. In the testing cohort, logistic regression and random forest models achieved AUC values of 0.889 and 0.855, respectively. Evaluating the maximum lesion cross-sectional area at baseline, 2 months, and 6 months, logistic regression and random forest models in the training cohort yielded AUC values of 0.819 and 0.998, sensitivities of 0.674 and 1.000, and F1 scores of 0.772 and 0.986. In the testing cohort, the AUC values were 0.869 and 0.920, sensitivities were 0.933 and 1.000, and F1 scores were 0.848 and 0.841, respectively.

CONCLUSIONS

The integration of maximum lesion cross-sectional area during treatment can improve the prediction of early treatment response in MDR-TB. When applied in a clinical setting, the random forest model is more suitable for guiding appropriate treatment plans quickly.

Drug-induced hypothyroidism in tuberculosis

INTRODUCTION

Adverse reactions to tuberculosis treatment can impact patient adherence and prognosis. Hypothyroidism is a frequent adverse reaction caused using ethionamide, prothionamide, and para-aminosalicylic acid and is often underdiagnosed.

AREAS COVERED

We searched Scielo, Scopus, and EMBASE databases, including 67 articles. Antitubercular drug-induced hypothyroidism has a prevalence of 17%. It occurs after 2 to 3 months of treatment and resolves within 4 to 6 weeks after discontinuation. It is postulated to result from the inhibition of thyroperoxidase function, blocking thyroid hormone synthesis. Symptoms are nonspecific, necessitating individualized thyroid-stimulating hormone measurement for detection. Specific guidelines for management are lacking, but initiation of treatment with levothyroxine, as is customary for primary hypothyroidism, is recommended. Discontinuation of antitubercular drugs is discouraged, as it may lead to unfavorable consequences.

EXPERT OPINION

Antitubercular drug-induced hypothyroidism is more common than previously thought, affecting one in six MDR-TB patients. Despite diagnostic and treatment recommendations, implementation is hindered in low-income countries due to the lack of certified laboratories. New drugs for tuberculosis treatment may affect thyroid function, requiring vigilant monitoring for complications, including hypothyroidism.

Study of adverse drug reactions during the treatment of drug resistant tuberculosis

BACKGROUND

Pharmacovigilance entails monitoring of patients for timely detection of ADR and reporting them so that more information about drug safety can be obtained. This may help in the future for dose modification or alteration of regimen. In NTEP, ADSm (Active Drug Safety monitoring) is part of pharmacovigilance. In this study we shall be studying ADRs to Anti TB drugs in DRTB.

METHODOLOGY

This study is observational, retrospective and record based, of patients admitted from 2021 to 2023 in the DOTS ward of Respiratory Medicine Department of a tertiary care hospital in Goa. Data such as age, sex, regimen, date of AKT initiation and adverse effects documented has been noted and compiled.

RESULTS

ADRs have been tabulated in the form of tables. Statistical analysis is done to find out the commonest ADR, time when they are likely to occur, which age and gender are most likely affected and if there are any other associated risk factors for ADRs.

CONCLUSION

This study will enable in future to better monitor patients with regard to particular adverse drug reaction, patient safety and if needed to alter the regimen as early as possible.

Deep learning and radiomics of longitudinal CT scans for early prediction of tuberculosis treatment outcomes

BACKGROUND

To predict tuberculosis (TB) treatment outcomes at an early stage, prevent poor outcomes ofdrug-resistant tuberculosis(DR-TB) and interrupt transmission.

METHODS

An internal cohort for model development consists of 204 bacteriologically-confirmed TB patients who completed anti-tuberculosis treatment, with one pretreatment and two follow-up CT images (612 scans). Three radiomics feature-based models (RM) with multiple classifiers of Bagging, Random forest and Gradient boosting and two deep-learning-based models (i.e., supervised deep-learning model, SDLM; weakly supervised deep-learning model, WSDLM) are developed independently. Prediction scores of RM and deep-learning models with respectively highest performance are fused to create new fusion models under different fusion strategies. An additional independent validation was conducted on the external cohort comprising 80 patients (160 scans).

RESULTS

For RM scheme, 16 optimal radiomics features are finally selected using longitudinal scans. The AUCs of RM for Bagging, Random forest and Gradient boosting were 0.789, 0.773 and 0.764 in the internal cohort and 0.840, 0.834 and 0.816 in the external cohort, respectively. For deep learning-based scheme, AUCs of SDLM and WSDLM were 0.767 and 0.661 in the internal cohort, and 0.823 and 0.651 in the external. The fusion model yields AUCs from 0.767 to 0.802 in the internal cohort, and from 0.831 to 0.857 in the external cohort.

CONCLUSIONS

Fusion of radiomics features and deep-learning model may have the potential to predict early failure outcome of DR-TB, which may be combined to help prevent poor TB treatment outcomes.

Adverse drug reactions and associated factors in multidrug-resistant tuberculosis: A retrospective review of patient medical records at Mbarara Regional Referral Hospital, Uganda

Objectives

The World Health Organization pragmatic guidelines recommend shorter duration drug regimens with newer, more efficacious agents for treatment of multidrug-resistant tuberculosis. However, adverse drug reactions associated with the use of newer, second-line agents may pose a major barrier to adequate management of multidrug-resistant tuberculosis. We therefore sought to investigate the prevalence and factors associated with adverse drug reactions among patients with multidrug-resistant tuberculosis.

Methods

We retrospectively reviewed patient medical records at the tuberculosis treatment unit of Mbarara Regional Referral Hospital, between January 2013 and December 2020. Medical records were included in the study, if the patients were aged ⩾18 years, tested sputum positive for multidrug-resistant tuberculosis, with adequate pharmacovigilance data documented. We assessed all documented health-related patient complaints, deranged laboratory values, and clinician suspected adverse drug reactions for scientific/clinical plausibility. Adverse drug reactions were confirmed using published and manufacturer drug references materials. A multidisciplinary clinician team was involved to decide whether to exclude or include a suspected adverse drug reaction.

Results

About 6 in 10 (67.4%; 120/178) patients experienced at least one adverse drug reactions during treatment, of which 18.3%, 14.6%, and 11.4% of adverse drug reactions affected the endocrine/metabolic, otic, and musculoskeletal body systems, respectively. Majority of the adverse drug reactions were probable and had a moderate severity. There was an upward trend in adverse drug reaction incidence between 2015 and 2019. Adverse drug reaction occurrence was associated with previous adverse drug reaction history (adjusted odds ratio = 2.85 (1.08, 7.53 at 95% confidence interval)); however, patients who were underweight (adjusted odds ratio = 0.34 (0.16, 0.69 at 95% confidence interval)) and those treated with bedaquiline-based drug regimens (adjusted odds ratio = 0.2 (0.07, 0.59 at 95% confidence interval)) were less likely to experience an adverse drug reaction.

Conclusion

Majority of patients with multidrug-resistant tuberculosis experience at least adverse drug reaction during the course of treatment. The newer standard shorter duration drug regimens (9-12 months) may be associated with intolerable adverse drug reactions that hamper effective management of multidrug-resistant tuberculosis. There is need for more studies to assess the clinical adverse drug reaction burden associated with the implementation of shorter duration regimens.

Designing New Magic Bullets to Penetrate the Mycobacterial Shield: An Arduous Quest for Promising Therapeutic Candidates

Mycobacterium spp. intimidated mankind since time immemorial. The triumph over this organism was anticipated with the introduction of potent antimicrobials in the mid-20th century. However, the emergence of drug resistance in mycobacteria, Mycobacterium tuberculosis, in particular, caused great concern for the treatment. With the enemy growing stronger, there is an immediate need to equip the therapeutic arsenal with novel and potent chemotherapeutic agents. The task seems intricating as our understanding of the dynamic nature of the mycobacteria requires intense experimentation and research. Targeting the mycobacterial cell envelope appears promising, but its versatility allows it to escape the lethal effect of the molecules acting on it. The unique ability of hiding (inactivity during latency) also assists the bacterium to survive in a drug-rich environment. The drug delivery systems also require upgradation to allow better bioavailability and tolerance in patients. Although the resistance to the novel drugs is inevitable, our commitment to the research in this area will ensure the discovery of effective weapons against this formidable opponent.

Frequency and Management of Adverse Drug Reactions Among Drug-Resistant Tuberculosis Patients: Analysis From a Prospective Study

Drug-resistant tuberculosis (DR-TB) management is often linked with a higher rate of adverse drug reactions (ADRs) needing effective and timely management of these ADRs, which, if left untreated, may result in a higher rate of loss to follow-up of drug-resistant patients.

Study objective: The study was aimed at prospectively identifying the nature, frequency, suspected drugs, and management approaches for ADRs along with risk factors of ADRs occurrence among DR-TB patients at Nishtar Medical University, Hospital, Multan, Pakistan.

Materials and Methods: The prospective study included all the DR-TB patients enrolled for treatment from January 2016 to May 2017 at the study site. Patients were evaluated for the treatment-induced ADRs as per standard criteria of the National Tuberculosis Program, Pakistan. Multivariate logistic regression was used to assess the independent variables associated with the occurrence of ADRs.

Results: Out of 271 DR-TB patients included in the final analysis, it was observed that 55 patients (20.3%) experienced at least three ADRs. A total of 50 (18.5%) patients experienced zero adverse effects, while 15 (5.5%), 33 (12.2%), and 53 (19.6%) patients experienced one, two, and four ADRs, respectively. Gastrointestinal disturbances (66.7%), nervous system disorders (59.4%), and electrolyte disturbances (55.7%) remained the highest reported ADRs during therapy, followed by arthralgia (49.1%), ototoxicity (24%), pruritic reactions/rash (12.9%), dyspnoea (12.5%), and tinnitus (8.8%). Pulmonary cavitation at the baseline visit (p-value 0.001, OR 3.419; 95% CI (1.694–6.902) was significantly associated with the occurrence of ADRs among DR-TB patients.

Conclusion: The frequency of ADRs was high among the study cohort; however, these were managed effectively. Patients with recognized risk factors for ADRs occurrence need continuous clinical management efforts.

Clinical standards for the dosing and management of TB drugs

BACKGROUND: Optimal drug dosing is important to ensure adequate response to treatment, prevent development of drug resistance and reduce drug toxicity. The aim of these clinical standards is to provide guidance on 'best practice´ for dosing and management of TB drugs.METHODS: A panel of 57 global experts in the fields of microbiology, pharmacology and TB care were identified; 51 participated in a Delphi process. A 5-point Likert scale was used to score draft standards. The final document represents the broad consensus and was approved by all participants.RESULTS: Six clinical standards were defined: Standard 1, defining the most appropriate initial dose for TB treatment; Standard 2, identifying patients who may be at risk of sub-optimal drug exposure; Standard 3, identifying patients at risk of developing drug-related toxicity and how best to manage this risk; Standard 4, identifying patients who can benefit from therapeutic drug monitoring (TDM); Standard 5, highlighting education and counselling that should be provided to people initiating TB treatment; and Standard 6, providing essential education for healthcare professionals. In addition, consensus research priorities were identified.CONCLUSION: This is the first consensus-based Clinical Standards for the dosing and management of TB drugs to guide clinicians and programme managers in planning and implementation of locally appropriate measures for optimal person-centred treatment to improve patient care.

Adverse effects induced by second-line antituberculosis drugs: an update based on last WHO treatment recommendations for drug-resistant tuberculosis

Introduction: Tuberculosis (TB), a common condition worldwide, is still among the main infectious diseases with high mortality rates, both in adults and infants. Drug-resistant tuberculosis (DR-TB) drugs, revised by the World Health Organization (WHO) in 2018, are a prolonged and complex therapy associated with many adverse drug effects (ADEs).

Aim: To systematically review the ADEs of second-line anti-TB drugs reported in multicentric studies published after the latest WHO guidelines, compared with those from clinical trials published before 2018.

Material and methods: A PubMed search, using keywords (TB OR DR-TB) AND (adverse effects) AND “second-line anti-TB drugs”, resulted in 56 studies. Only two studies, published after the last update of WHO guidelines in 2018, reported ADEs.

Results: A total of 223 participants were included in the two selected studies. The use of multidrug regimens has been associated with an increased incidence of ADEs: 42 ADEs were recorded in 30 patients (26.3%) in the first study, while all patients had at least one ADE that occurred or worsened during treatment; and 19 (17%) had severe ADEs in the second study. However, both studies had a good favourable outcome rate (90% and 79.8%, respectively). Gastrointestinal disturbances, hepatotoxicity, headache and dizziness are the most common ADEs induced by a majority of second-line DR-TB treatments. A special attention should be given in the case of association of drugs determining QT interval (QT) prolongation on electrocardiogram, or psychiatric disorders.

Conclusions: Proper strategies about ADE management have to be planned for timely detection of the possible ADEs that can be induced by second-line anti-TB therapy.