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INTRODUCTION
One of the biggest causes of death worldwide and a major contributor to ill health is still Tuberculosis (TB). TB surpassed HIV/AIDS as the leading infectious cause of death before the COVID-19 pandemic. The main way that Mycobacterium tuberculosis, the bacterium that causes TB, is spread is by inhaling droplets from coughing or other activities. Long treatment periods, unpleasant drug side effects, drug resistance, the need for multiple medications, restricted access to healthcare services, low socioeconomic status, low levels of education, and the social stigma associated with the disease have all made it difficult to control TB effectively in developing countries. TB is a health and social burden since its incidence often reflects the general level of social welfare and living conditions in a society (Hershkovitz et al., 2015; Sakula, 1982; World Health Organization, 2021).
Globally, TB incidence rose by 4.5% from 2020 to 2021, increasing from 10.1 million to 10.6 million cases. The incidence rate (new cases per 100,000 people annually) grew by 3.6% during the same period. In India, the Global TB Report 2021 estimated the incidence of all forms of TB in 2020 to be 188 per 100,000 people (range: 129-257 per 100,000) (World Health Organization, 2022).
India’s fight against TB has evolved through various programs. The National TB Control Program (NTCP), initiated in 1962, was replaced by the Revised National Tuberculosis Control Program (RNTCP) from 1997 to 2019. On January 1, 2020, the National Tuberculosis Elimination Program (NTEP) succeeded the RNTCP as India’s primary TB control initiative (Ashok, 2020). Throughout this evolution, various drugs have been introduced and withdrawn to improve treatment efficacy. Patients have a high chance of overcoming TB with effective, continuous anti-tuberculous treatment (Mason, 1986; Pablos-Méndez et al., 1997). Adherence to prescribed treatment regimens is crucial for curing patients, preventing the spread of infection, and minimizing the emergence of drug resistance. However, adherence can be challenging due to the length of treatment (often six months or more), the need for combination therapy, and potential unpleasant side effects. When prescription costs are not covered by public health systems, they can pose significant barriers to adherence (Addington, 1979). Additionally, patients often experience rapid symptom relief, which may obscure the need for prolonged treatment.
Several factors contribute to non-adherence to anti-tuberculosis drugs, including adverse effects such as nausea, vomiting, abdominal discomfort, diarrhea, loose stools, headaches, mood changes, and skin rashes. Ineffective management of ADRs, the long-term commitment required for treatment involving multiple tablets, and additional social or psychological factors also play a role (Gugssa Boru et al., 2017; Mekonnen and Azagew, 2018; Tesfahuneygn et al., 2015; Tola et al., 2015). Discontinuation of TB treatment due to ADRs or inadequate management is a critical concern. Irregular, incomplete, or inadequate TB treatment has several consequences, such as the spread of disease to other body parts, relapse of TB symptoms, increased drug resistance, treatment failure, heightened risk of infection among close contacts, and even death (Imperial et al., 2018; Lee et al., 2016; Subbaraman et al., 2021; Temesgen et al., 2021; Waitt and Squire, 2011).
ADRs are unwanted or adverse reactions that are considered to be related to a medicine and occur after using a drug or combination of drugs. Several anti-tuberculosis drugs are required to treat TB, and these drugs can have mild to severe side effects. Early detection and management of ADRs are essential for effective TB treatment. The patient’s tolerance to anti-TB medications is important, particularly since NTEP 2020 recommends dosing changes based on new weight bands. This study uniquely investigates ADRs to anti-tuberculosis treatment in a real-world programmatic setting of Tamil Nadu, India, incorporating both patient and provider perspectives. It offers novel insights into the pattern, severity, and health system responses to ADRs, which are rarely examined comprehensively in routine TB control programs. In light of this, the aim of this research is to examine the frequency and contributing factors of ADRs to medications during TB treatment in these patients.
MATERIALS AND METHODS
This prospective study was conducted over a one-year period from January 2022 to December 2022. The primary objective was to identify ADRs during the intensive and continuation phases of TB treatment, while secondary objectives included identifying factors associated with ADRs by comparing their incidence with variables such as age, sex, weight, alcoholism, diabetes, and comorbidities.
Study Setting
The Department of Respiratory Medicine at a tertiary care facility that was prepared to treat TB cases in a comprehensive manner served as the study's location. Convenient sampling was used to find subjects once certain inclusion and exclusion criteria were applied. In addition to patients with TB and comorbidities such diabetes, hypertension, thyroid issues, liver and renal problems, epilepsy, and Chronic Obstructive Pulmonary Disease (COPD), the inclusion criteria included all newly diagnosed adult patients with pulmonary or extrapulmonary TB. Patients under the age of eighteen, those who were in default, those who were mentally ill, those who were severely ill, those who had significant hemodynamic instability, uncontrolled comorbidities, severe liver problems, chronic kidney illnesses, and TB patients who were also HIV-positive were all excluded.
The sample size consisted of all subjects meeting the inclusion criteria during the study period. Ethical considerations were strictly adhered to, with approval obtained from the Institutional Ethical Committee before the commencement of the study. Informed written consent was obtained from all participants, ensuring their voluntary participation. The study declared no external funding or conflicts of interest.
Data Collection
The study's methodology was carefully planned to guarantee thorough data gathering and tracking. Patients were first chosen in accordance with the inclusion and exclusion criteria. Before being included, each patient received a thorough explanation of the study's design and gave their informed consent. The patient's medical history and basic statistics were recorded using a questionnaire.
Baseline evaluations, which included taking the patient's height, weight, and vital signs, were carried out before to starting anti-TB treatment. Complete blood counts, blood sugar levels, liver function tests (base levels of bilirubin and transaminases), renal function tests (urea and creatinine), and uric acid levels were all part of the laboratory examinations. Throughout the course of therapy, these baseline evaluations were essential for tracking any possible negative drug reactions.
Patients received recurring follow-ups after being included in order to evaluate and record any negative medication effects. At every follow-up session, the questionnaire was modified to record fresh information and monitor the development of any side effects. Any ADRs were quickly found and handled as per clinical guidelines.
The study had no funding and did not involve any extra research or therapies beyond what is typically done in clinical settings. Budgetary constraints made that the study stayed economical while upholding strict guidelines for data collection and analysis.
Statistical Analysis
Statistical methods were employed to analyze the collected data comprehensively. Descriptive statistics were used to summarize numerical variables such as age, represented through mean, Standard Deviation (SD), median, and mode. Histograms were utilized where necessary to visualize data distributions. Categorical variables like gender were presented in frequencies and percentages, with pie charts and bar diagrams used for graphical representation. Data entry was performed using MS Excel, and analysis was conducted using SPSS software version 16.
Inferential statistics and Logistic regression were applied to identify significant associations within the data. Categorical variables were analyzed using chi-square tests to determine significance. On Univariate analysis, independent variables showing a p-value of less than 0.2 were taken for multivariable regression analysis, where results with p-values less than 0.05 were considered statistically significant, ensuring the robustness of the study's findings.
RESULTS
The study involved 203 newly diagnosed TB patients who visited the Department of Respiratory Medicine. Table 1 presents the demographic and clinical characteristics of the 203 TB patients included in the study. The mean age was 48.68 years (SD ±10.3). Gender distribution was nearly equal, with 104 males (51%) and 99 females (49%). The majority of patients (91, 44.83%) belonged to the 35-49 kg weight band, followed by 70 (34.48%) in the 50-64 kg category, 23 (11.33%) in the 65-75 kg category, and 17 (8.37%) weighing more than 75 kg. Pulmonary TB was more common, affecting 163 patients (80.3%), while 40 (19.7%) had extrapulmonary TB. GeneXpert was positive in 111 patients (54.68%), and 39 (19.21%) had a positive sputum AFB test. Comorbidities were prevalent, with diabetes in 46 patients (22.7%), COPD/asthma in 15 (7.4%), and hypertension in 8 (3.9%). Alcohol consumption was reported by 36 patients (17.7%).
| Characteristics | Frequency | Percentage (%) |
|---|---|---|
| Age (years) Mean (SD) | Mean: 48.68 (10.3) | |
| Gender | ||
| Male | 104 | 51% |
| Female | 99 | 49% |
| Weight Group | ||
| 25 - 34 kg | 2 | 0.99% |
| 35 - 49 kg | 91 | 44.83% |
| 50 - 64 kg | 70 | 34.48% |
| 65 - 75 kg | 23 | 11.33% |
| > 75 kg | 17 | 8.37% |
| Alcohol consumption | ||
| Yes | 36 | 17.73% |
| No | 167 | 82.27% |
| No of Tablets (FDC) in Initiation | ||
| 3 tablets | 43 | 21.18% |
| 4 tablets | 111 | 54.68% |
| 5 tablets | 36 | 17.73% |
| 6 tablets | 12 | 5.91% |
| 7 tablets | 1 | 0.49% |
| TB Type | ||
| Pulmonary | 163 | 80.30% |
| Extrapulmonary | 40 | 19.70% |
| Sputum AFB | ||
| Positive | 39 | 19.21% |
| Negative | 164 | 80.79% |
| Gene Expert | ||
| Positive | 111 | 54.68% |
| Negative | 92 | 45.32% |
| Comorbidities | ||
| Diabetes | 46 | 22.7% |
| Hypertension | 8 | 3.9% |
| COPD/Asthma | 15 | 7.4% |
| CAD | 3 | 1.5% |
| CVA | 4 | 2.0% |
Table 2 summarizes the incidence and types of Adverse Drug Reactions (ADRs) among 203 TB patients. A total of 113 patients (55.67%) experienced ADRs, while 90 (44.33%) had no reported reactions. Gastrointestinal (GI) side effects were the most common, affecting 65 patients (32.02%). Itching was reported in 38 patients (18.72%), Liver Function Test (LFT) abnormalities in 25 (12.32%), joint pain in 6 (2.96%), rashes in 5 (2.46%), and peripheral neuropathy in 3 (1.48%). No cases of visual symptoms, ototoxicity, or nephrotoxicity were observed. When analyzed by gender, ADRs were reported in 56 males (53.84%) and 57 females (57.57%), indicating a slightly higher prevalence among females. Figure 1 presents the distribution of Adverse Drug Reactions (ADRs) among tuberculosis patients, showing both frequency and percentage.
| Adverse Drug Reactions (ADR) | Frequency | Percentage (%) |
|---|---|---|
| Yes | 113 | 55.67% |
| No | 90 | 44.33% |
| ADR Profile | ||
| GI Side Effects | 65 | 32.02% |
| LFT Deranged | 25 | 12.32% |
| Rashes | 5 | 2.46% |
| Itching | 38 | 18.72% |
| Peripheral Neuropathy | 3 | 1.48% |
| Joint Pain | 6 | 2.96% |
| Visual Symptoms | 0 | 0.00% |
| Ototoxicity | 0 | 0.00% |
| Nephrotoxicity | 0 | 0.00% |
| ADR by Gender | ||
| Males (with ADR) | 56 | 53.84% |
| Females (with ADR) | 57 | 57.57% |
Table 3 examines the association between weight bands and ADR occurrence. The highest ADR incidence was observed in the 35-49 kg weight group, with 63 out of 91 patients (69.23%) experiencing ADRs (p=0.001). In the 25-34 kg category, 1 out of 2 patients (50%) reported ADRs, while the 50-64 kg group had 32 out of 70 patients (45.71%) affected. In the 65-75 kg weight category, 9 out of 23 patients (39.13%) had ADRs, and in the >75 kg group, 8 out of 17 patients (47.05%) reported ADRs. These findings indicate that patients in the 35-49 kg weight range are at the highest risk of developing ADRs, potentially due to variations in drug metabolism and weight-based dosing strategies.
| Weight Group | Adverse Drug Reactions | Total | Fisher exact p value | |
|---|---|---|---|---|
| Yes | No | |||
| 25 - 34 kg | 1 (50%) | 1 (50%) | 2 (100%) | 0.001 |
| 35 - 49 kg | 63 (69.23%) | 28 (30.76%) | 91 (100%) | |
| 50 - 64 kg | 32 (45.71%) | 38 (54.28%) | 70 (100%) | |
| 65 - 75 kg | 9 (39.13%) | 14 (60.86%) | 23 (100%) | |
| > 75 kg | 8 (47.05%) | 9 (52.94%) | 17 (100%) | |
| Total | 113 (55.66%) | 90 (44.33%) | 203 (100%) |
Table 4 presents the univariate and multivariable analysis of independent variables associated with Adverse Drug Reactions (ADR) among the study population (n=203). In the univariate analysis, significant associations (p<0.2) were observed for age, weight group, sputum AFB positivity, and comorbidities, which were included in the multivariable model. The adjusted analysis revealed that patients aged older had a 5% higher risk of ADR per year increase (AOR: 1.05, p=0.02). Those in the 35-49 kg weight group had 2.75 times higher odds of ADR (AOR: 2.75, p=0.04) compared to the >75 kg group. Sputum AFB-positive patients had 2.38 times higher odds of ADR (AOR: 2.38, p=0.02), and Alcohol with AOR=3.25, p-value=0.006 indicating both as significant risk factor. Additionally, patients with comorbidities had twice the odds of developing ADR (AOR: 2.05, p=0.02) compared to those without comorbidities. Gender and other weight categories did not show statistically significant associations. These findings suggest that older age, lower body weight, sputum AFB positivity, and comorbidities are key predictors of ADR among tuberculosis patients.
| Variable | ADR Present (n=113) | ADR Absent (n=90) | Unadjusted OR (95% CI) | p-value (Univariate) | Adjusted OR (95% CI) | p-value (Multivariable) |
|---|---|---|---|---|---|---|
| Age (Mean±SD) | 50.2±9.8 | 46.7±10.5 | 1.32 (0.76 - 1.97) | 0.54 | - | - |
| Gender | ||||||
| Male | 59 (56.73%) | 45 (43.27%) | 1.10 (0.64 - 1.88) | 0.52 | - | - |
| Female | 54 (54.54%) | 45 (45.45%) | Ref | - | - | |
| Alcohol Consumption | ||||||
| Yes | 28 (77.78%) | 8 (22.22%) | 3.61 (1.54 - 8.47) | 0.003 | 3.25 (1.38 - 7.65) | 0.006 |
| No (Reference) | 85 (50.90%) | 82 (49.10%) | Reference | Reference | ||
| Weight Group (kg) | ||||||
| 25 - 34 | 1 (50%) | 1 (50%) | 1.50 (0.40 - 5.64) | 0.55 | 1.40 (0.35 - 5.42) | 0.6 |
| 35 - 49 | 63 (69.23%) | 28 (30.76%) | 2.81 (1.15 - 6.89) | 0.03 | 2.75 (1.10 - 6.86) | 0.04 |
| 50 - 64 | 32 (45.71%) | 38 (54.28%) | 1.89 (0.83 - 4.34) | 0.12 | 1.85 (0.79 - 4.30) | 0.15 |
| 65 - 75 | 9 (39.13%) | 14 (60.86%) | 1.35 (0.49 - 3.72) | 0.56 | 1.32 (0.46 - 3.74) | 0.6 |
| > 75 | 8 (47.05%) | 9 (52.94%) | Ref | Ref | ||
| Sputum AFB | ||||||
| Positive | 30 (76.92%) | 9 (23.07%) | 2.41 (1.02 - 5.68) | 0.04 | 2.38 (1.01 - 5.62) | 0.02 |
| Negative | 83 (50.61%) | 81 (49.39%) | Ref | Ref | ||
| Comorbidities | ||||||
| Yes | 62 (66.67%) | 31 (33.33%) | 2.10 (1.11 - 3.98) | 0.01 | 2.05 (1.08 - 3.90) | 0.02 |
| No | 51 (45.13%) | 62 (54.87%) | Ref | Ref |
DISCUSSION
The present study aimed to evaluate the incidence and nature of ADRs among newly diagnosed TB patients across different weight bands, as per NTEP 2020 guidelines. Our findings contribute to the growing body of evidence on the variability of treatment responses in TB patients, emphasizing the role of weight-based drug dosing and comorbidities in influencing ADR profiles.
Demographic and Comorbidity Profiles
The study population comprised 203 patients, with a mean age of 48.68 (±10.95) years and a nearly equal gender distribution (51.2% male, 48.8% female). This contrasts with earlier studies such as (Lee et al., 2016) which reported a higher mean age (55.86 years) and a male predominance (62.4%). Similarly (Temesgen et al., 2021) and an Indonesian cohort documented younger cohorts (mean ages 36.5 and 45.8 years, respectively) with higher male representation (68.4% and 70.3%). These discrepancies may reflect regional epidemiological variations, differences in inclusion criteria (e.g., age ranges, study settings), or shifts in TB demographics over time. Notably, a study from Maharashtra by Mate et al. (2022) reported a female predominance (53.6%), aligning more closely with our gender distribution and suggesting potential sociocultural or healthcare-seeking behavior influences.
Comorbidities were prevalent in our cohort, with diabetes (22.7%) and alcoholism (17.7%) emerging as significant contributors to ADR risk. Hypertension (3.9%), COPD/asthma (7.4%), and cardiovascular conditions (CAD 1.5%; CVA 2%) were less common among the patients.
Adverse Drug Reactions: Incidence and Spectrum
Among the 113 patients (55.7%) experiencing ADRs, Gastrointestinal (GI) disturbances (32%) were the most frequent, followed by itching (18.7%), abnormal liver function tests (LFTs, 12.3%), and joint pain (3%). Notably, no visual symptoms or life-threatening reactions were reported. This aligns with (Mate et al., 2022), who found GI issues (67.9%) and joint pain (37.6%) to be predominant ADRs, though cutaneous reactions (16.6%) were more frequent in their cohort. In contrast, (Fei et al., 2018) reported higher rates of hepatotoxicity (7.1%) and cutaneous reactions (21%), while (Kurniawati et al., 2012) observed skin reactions (7.8%) as the most common. These variations may stem from differences in drug regimens (e.g., fixed-dose combinations vs. individual drug dosing), genetic predispositions, or differences in ADR monitoring protocols.
A critical finding in our study was the higher ADR incidence in the 35-49 kg weight band (69.23%) compared to the 25-34 kg band (50%) and the 65-75 kg band (39.13%). This contrasts with NTEP’s one-size-fits-all approach to weight-based dosing, suggesting that intermediate weight bands may experience suboptimal drug exposure or heightened sensitivity. For instance, patients in lower weight bands might receive relatively higher mg/kg doses, increasing toxicity risk, while those in higher bands may face under-dosing and reduced efficacy. Pharmacokinetic studies are warranted to explore this relationship further.
Management and Outcomes of ADRs
Management strategies for ADRs varied by reaction type. In our study, 89.2% of GI-related ADR cases continued on the Fixed-Dose Combination (FDC) therapy without interruption, whereas 60% of hepatotoxicity cases and all patients with severe joint pain required treatment discontinuation or regimen change. Itching was managed conservatively in 86.8% of cases (most patients continued therapy), and peripheral neuropathy was managed without stopping treatment in all affected patients. These management decisions reflect the severity and reversibility of specific reactions. For example, hepatotoxicity often necessitates regimen modification or drug cessation, while mild GI symptoms may resolve with supportive care. Comparatively, (Damasceno et al., 2013) reported that 65.8% of ADRs were managed without intervention, while 24.4% of patients discontinued treatment-higher than our cohort’s 10.8% discontinuation rate for GI issues. This difference highlights the need for standardized protocols to balance ADR mitigation with maintaining treatment adherence.
Temporal Patterns and Severity
ADRs in our study exhibited distinct temporal trends. GI symptoms typically arose early in treatment (mean onset 2-15 days), LFT abnormalities peaked at approximately 20 days, and rashes tended to manifest later (20-40 days into therapy). Peripheral neuropathy and joint pain generally emerged around 30 days and between 4-8 weeks, respectively. These patterns align with findings by Sinha et al., 2013 where GI disturbances (53.5%) and hepatotoxicity (15.5%) predominated within the first two months of treatment. Similarly, Vieira and Gomes (2008) noted that 58.4% of ADRs occurred during the initial phase of treatment. These timelines underscore the importance of vigilant monitoring during the intensive treatment phase, particularly for hepatotoxicity, which often necessitates prompt regimen adjustments.
In terms of severity, most ADRs in our cohort were mild to moderate, consistent with observations by Mate et al., (2022) and Athira et al., (2015). However, all rash cases in our study required hospitalization (severity level 4), in contrast to findings by Tan et al., (2007), where 97% of cutaneous reactions were managed without hospital admission. This discrepancy may reflect differences in the types of skin reactions encountered (e.g., exfoliative dermatitis vs. urticarial rash) or differing thresholds for hospitalization in different healthcare settings.
Risk Factors
We observed no significant gender disparity in overall ADR incidence, a finding that conflicts with Fei et al., (2018), who reported higher ADR rates in female patients. However, our results align with those of Gupta et al., (2011) and Damasceno et al., (2013), suggesting that gender may not be a uniform predictor of ADR risk across all populations. Comorbid conditions like diabetes and alcoholism emerged as significant contributors to ADR occurrence in our study, corroborating Gupta et al.’s (2011) emphasis on diabetes (around 20% prevalence in their cohort) and substance abuse as factors amplifying TB risk.
Patients in the 35-49 kg weight group had the highest odds of ADR, possibly due to altered drug distribution and increased drug toxicity in individuals with lower body weight. Sputum AFB-positive patients were also more likely to experience ADRs, which could be linked to higher mycobacterial loads requiring more intensive treatment regimens and thus greater drug exposure. Additionally, patients with comorbidities or alcohol use had roughly twice the risk of ADRs, likely due to impaired organ function and potential interactions between anti-TB drugs and medications for chronic conditions. These findings underscore the need for close monitoring of high-risk patients-particularly older individuals, underweight patients, and those with comorbidities-to minimize ADR-related complications and improve treatment adherence, similar to the recommendations by Resende & Santos-Neto, 2015.
Implications for NTEP Guidelines
The higher ADR burden in the 35-49 kg band challenges the one-size-fits-all approach of weight-based dosing. Tailored dosing strategies, therapeutic drug monitoring, or adjunctive therapies (e.g., hepatoprotectants) may mitigate risks. Additionally, integrating comorbidity management into TB care-particularly for diabetes-could improve outcomes.
Limitations
This study had several limitations. First, the sample size was limited to 203 participants from a single institution, potentially affecting the generalizability of the findings. Second, the study's reliance on patient self-reporting for some ADRs may have introduced reporting bias. Additionally, the study did not account for potential confounding factors such as nutritional status or genetic predisposition to ADRs.
Recommendations
Future studies should consider larger, multi-center cohorts to enhance the generalizability of findings. Incorporating genetic and nutritional assessments could provide deeper insights into the factors influencing ADRs. Moreover, implementing standardized ADR monitoring protocols could improve early detection and management, ultimately enhancing treatment adherence and outcomes in TB patients.
CONCLUSION
This study underscores the complex interplay of weight, comorbidities, and Adverse Drug Reactions (ADRs) in Tuberculosis (TB) treatment. While Gastrointestinal (GI) and hepatic reactions are prevalent, their incidence and management differ across weight categories, requiring personalized approaches. Effectively addressing ADRs can reduce treatment discontinuation, minimize the risk of drug resistance, and ultimately enhance patient outcomes. Future research should emphasize broader, multi-center studies to validate these findings and develop comprehensive strategies for ADR management in TB care.