Quality of life and social correlates among drug sensitive and MDR-TB patients [TBN 060]

WHAT

This comparative study assessed quality of life (QOL) among patients with multidrug-resistant tuberculosis (MDR-TB) compared with drug-sensitive tuberculosis patients in Chitradurga district, India. The study included 40 MDR-TB patients and 80 age- and gender-matched drug-sensitive TB patients, with a case-to-control ratio of 1:2. MDR-TB cases were defined as patients resistant to isoniazid and rifampicin confirmed using CBNAAT testing, while controls were patients sensitive to first-line anti-TB drugs.

The results showed significant differences in socioeconomic and educational status between the two groups (P < 0.05), suggesting that MDR-TB patients were more likely to have socioeconomic disadvantages. However, no significant differences were found in lifestyle factors such as alcohol consumption or smoking between MDR-TB and drug-sensitive TB patients (P > 0.05).

Overall quality of life and health satisfaction were significantly lower among MDR-TB patients compared with drug-sensitive TB patients. The mean QOL score was 3.33 ± 1.199, and the mean health satisfaction score was 3.28 ± 1.190. Drug-sensitive TB patients reported significantly better QOL and health satisfaction than MDR-TB patients (P < 0.05), indicating a greater burden of disease among MDR-TB patients.

Across all four WHOQOL-BREF domains—physical, psychological, social relationships, and environmental—drug-sensitive TB patients had higher scores than MDR-TB patients. The psychological domain was the most affected domain in both groups. Among MDR-TB patients, the physical domain had the highest scores, while among drug-sensitive TB patients, the environmental domain scored highest.

Comparative analysis demonstrated that psychological wellbeing was significantly poorer among MDR-TB patients compared with drug-sensitive TB patients (P < 0.05). These findings suggest that MDR-TB has a substantial negative impact on mental health and overall quality of life, beyond the physical burden of disease.

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HOW

This study used a comparative cross-sectional design conducted in the Department of Community Medicine at Basaveshwara Medical College and Hospital, Chitradurga, India, from 2018 to 2019. MDR-TB patients resistant to isoniazid and rifampicin, with or without resistance to other drugs, were identified using CBNAAT testing and included as cases.

A total of 40 MDR-TB patients were identified from district records. For the control group, 80 drug-sensitive TB patients were selected using age and gender matching in a 1:2 case-to-control ratio. Controls were randomly selected from TB patients registered at the District Tuberculosis Centre (DTC). Written informed consent was obtained from all participants prior to data collection.

Quality of life was assessed using the WHOQOL-BREF questionnaire, which contains 26 items measuring four domains: physical health, psychological health, social relationships, and environmental wellbeing. Additional sociodemographic information, including education, occupation, marital status, and lifestyle factors, was also collected.

The questionnaire was interviewer-administered to minimize misunderstanding and ensure consistent data collection. Responses were recorded without influence from family members or accompanying health workers to reduce response bias.

Source: Hamsaveni, G., Amrutha, A.M., Sidenur, B., Mangasuli, V. and Vijeth, S.B., 2024. Assessment of quality of life and social correlates among drug sensitive and multidrug-resistant tuberculosis patients. Journal of Association of Pulmonologist of Tamil Nadu, 7(3), pp.100-104.

Second-Line Anti-TB Drugs Susceptibility Pattern in MDR-TB Patients in Bandung, Indonesia [TBN 059]

WHAT

This cross-sectional descriptive study examined resistance patterns to second-line anti-tuberculosis drugs among drug-resistant tuberculosis (DR-TB) patients treated at Dr. Hasan Sadikin General Hospital, Bandung, Indonesia. A total of 134 patient records were retrieved, but after excluding duplicate entries and incomplete data, 82 patients were included in the final analysis. The median age of participants was 42 years (range 27–51 years), and most patients were female (53.7%). Over half of the patients (52.4%) were classified as new or primary MDR-TB cases, followed by relapse cases (29.3%).

Drug susceptibility testing showed that resistance to high-dose isoniazid was the most common, affecting 43.9% of patients. Resistance to fluoroquinolones was also observed, with 14.6% showing resistance to low-dose moxifloxacin and an equal proportion (14.6%) resistant to low-dose levofloxacin. Among patients resistant to low-dose moxifloxacin, a subset also demonstrated cross-resistance to other fluoroquinolones, indicating potential limitations in second-line treatment options.

Testing using the Mycobacteria Growth Indicator Tube (MGIT) further confirmed resistance patterns, showing high-dose isoniazid resistance as the most frequent, followed by low-dose levofloxacin resistance (9.8%). These findings highlight that resistance extended beyond first-line therapy and affected important second-line drugs used in MDR-TB management.

Most patients were of productive working age, suggesting a substantial potential socioeconomic burden of MDR-TB. Additionally, the high proportion of primary MDR-TB cases indicates ongoing transmission of drug-resistant strains rather than resistance developing solely from prior treatment failure.

Overall, the study identified considerable resistance to both high-dose isoniazid and fluoroquinolones among MDR-TB patients. These findings emphasize the importance of drug susceptibility testing to guide individualized treatment regimens and prevent treatment failure.

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HOW

This study used a descriptive cross-sectional design based on secondary data obtained from the Tuberculosis Information System (SITB) at the MDR clinic of Dr. Hasan Sadikin General Hospital in Bandung, West Java, Indonesia. The study period covered patients registered between December 2021 and June 2022. Total sampling was applied to include all eligible patients during the study period.

Inclusion criteria were patients aged 18 years or older diagnosed with drug-resistant tuberculosis and treated at the MDR clinic. Patients with incomplete records or missing data were excluded. From 134 retrieved records, 7 duplicate entries and 45 incomplete records were excluded, resulting in 82 patients included in the final analysis.

Collected variables included demographic characteristics (age and gender), history of previous anti-tuberculosis treatment, and second-line drug susceptibility test results. Previous treatment history included categories such as new cases, relapse, treatment failure, loss to follow-up, TB-HIV co-infection, and exposure to MDR-TB contacts.

Drug resistance patterns were assessed using two laboratory methods: Line Probe Assay (LPA) and Mycobacteria Growth Indicator Tube (MGIT). These tests evaluated resistance to second-line anti-tuberculosis drugs including moxifloxacin (low-dose and high-dose), levofloxacin, and high-dose isoniazid. 

Source: Suwandi, S.N., Kulsum, I.D. and Andriyoko, B., 2024. Second-Line Anti-Tuberculosis Drugs Susceptibility Pattern in Multidrug-resistant Tuberculosis Patients at Dr. Hasan Sadikin General Hospital, Bandung, Indonesia. Althea Medical Journal, 11(2), pp.100-105.

Prospective cohort study on TB incidence and risk factors in the elderly population of eastern China [TBN 058]

WHAT

This large cohort study evaluated the incidence and risk factors for active tuberculosis (TB) among elderly individuals aged ≥65 years in Zhenjiang City, Jiangsu Province, China. A total of 39,122 older adults were included after excluding 10 individuals with existing TB at baseline. Participants underwent annual free public health screening in 2016, which included demographic surveys, lifestyle assessment, laboratory testing, and clinical examinations.

At baseline, 46.1% of participants were male. Nutritional status showed that 3.9% were underweight, 47.6% normal weight, 37.5% overweight, and 10.9% obese. Smoking was reported in 16.2% of participants, with 7.2% former smokers. Alcohol consumption was reported by 15.9%, and 12.2% had diabetes. Approximately one-fifth reported regular exercise, while 0.9% had symptoms suggestive of TB. Notably, 65.2% of participants had abnormal findings during physical examinations.

After more than seven years of follow-up, 246 individuals developed active TB, corresponding to an incidence rate of 92.21 per 100,000 person-years (95% CI 81.2–104.3). Among these cases, 51.2% were bacteriologically confirmed, and 4.1% were diagnosed with tuberculous pleurisy. The incidence was substantially higher among males (140.2 per 100,000 person-years) compared with females (51.4 per 100,000 person-years).

Nutritional status was strongly associated with TB risk. Underweight individuals had the highest incidence rate (390.3 per 100,000 person-years), whereas obese individuals had the lowest incidence (34.1 per 100,000 person-years). Former smokers also showed markedly higher TB risk, with incidence rates nearly four times higher than never-smokers and three times higher than current smokers.

In multivariable analysis, increasing age remained associated with higher TB risk (adjusted hazard ratio [AHR] 1.03 per year increase, 95% CI 1.01–1.04). Male sex was associated with significantly increased risk (HR 2.73, 95% CI 2.08–3.58). Compared with obese individuals, those with normal BMI had nearly three times higher TB risk (AHR 2.87, 95% CI 1.51–5.46), and underweight individuals had nearly ten times higher risk (AHR 9.89, 95% CI 4.92–19.85). Former smoking was also associated with increased risk (AHR 1.35, 95% CI 1.12–1.64).

Population attributable fraction (PAF) analysis showed that normal BMI contributed the largest proportion of TB risk (47.1%), followed by male sex (43.0%), underweight BMI (25.7%), and smoking cessation (1.6%). These findings suggest that demographic and nutritional factors play a major role in TB risk among older adults.

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HOW

This study used a population-based cohort design based on annual public health screening services provided to elderly individuals aged ≥65 years in Zhenjiang City, China, between January and December 2016. These government-sponsored screenings included demographic surveys, lifestyle questionnaires, clinical examinations, and laboratory testing such as blood glucose, lipid profiles, electrocardiogram, complete blood count, urinalysis, and abdominal ultrasound.

Individuals with symptoms suggestive of TB—including persistent cough, hemoptysis, unexplained weight loss, fever, night sweats, chest pain, or lymph node swelling—underwent additional chest X-ray screening. Active TB cases were identified by linking participants to the Tuberculosis Management Information System using identification numbers. Diagnoses were verified through consultation with physicians at designated TB hospitals.

TB cases were classified as bacteriologically confirmed or clinically diagnosed. Bacteriological diagnosis included sputum smear, culture, GeneXpert testing, or pathological confirmation. Clinical diagnosis required negative bacteriological testing but compatible chest X-ray findings and clinical symptoms or supportive immunologic tests such as tuberculin skin test or interferon-gamma release assay.

Baseline variables included BMI, smoking status, alcohol use, diabetes, physical activity, and abnormal physical examination findings. BMI was categorized as underweight, normal, overweight, and obese according to Chinese guidelines. Diabetes control was classified using fasting plasma glucose levels, and abnormal physical examination referred to any abnormal clinical findings during screening.

Participants were followed for more than seven years to identify incident TB cases. Incidence rates were calculated per 100,000 person-years. Risk factors were evaluated using both univariate and multivariable Cox proportional hazards models. Population attributable fractions were calculated to estimate the contribution of key risk factors to TB incidence.

Source: Jiang, H., Chen, X., Lv, J., Dai, B., Liu, Q., Ding, X., Pan, J., Ding, H., Lu, W., Zhu, L. and Lu, P., 2024. Prospective cohort study on tuberculosis incidence and risk factors in the elderly population of eastern China. Heliyon, 10(3).

Association of ambient temperature with tuberculosis incidence in Japan [TBN 057]

WHAT

This ecological study examined the association between ambient temperature and tuberculosis (TB) incidence across Japan from 2007 to 2019 using national surveillance data. A total of 335,060 newly confirmed TB cases were reported across all 47 prefectures during the study period. TB diagnosis was based on clinical symptoms (e.g., cough, sputum, fever, chest pain) combined with laboratory confirmation, including sputum smear, culture, nucleic acid testing, tuberculin skin tests, interferon-gamma release assays, radiography, or clinical judgment.

The analysis found a nonlinear relationship between temperature and TB incidence. The minimum risk temperature (MMT) was identified at 4.45°C, corresponding to the 10th percentile of mean temperature. Compared with this reference, high temperatures were associated with significantly increased TB risk. Specifically, at the 99th percentile (30.1°C), the relative risk (RR) of TB incidence was 1.52 (95% CI 1.04–2.23), indicating a 52% higher risk at extreme heat levels.

Cold temperature effects were smaller and short-term. At −1.2°C (1st percentile), the relative risk was 1.03 (95% CI 1.01–1.06), with the highest effect observed at lag 0 weeks, declining thereafter. In contrast, heat exposure demonstrated delayed effects, with increased TB risk observed at mid-term lag periods ranging from 2 to 26 weeks. These findings suggest that heat exposure may influence TB incidence over longer time frames compared with cold exposure.

Considerable regional variation was observed across prefectures. For example, the minimum risk temperature was 19.4°C (80th percentile) in Hokkaido, while in Okinawa it was 14.8°C (1st percentile), suggesting differences in population adaptation to local climates. These findings indicate that climate-related TB risk may depend on regional environmental conditions and population acclimatization.

Sensitivity analyses demonstrated that the association between temperature and TB incidence remained generally stable across different model specifications, including variations in degrees of freedom, lag periods, and autocorrelation adjustments. Heat-related effects were consistent across sensitivity analyses, whereas cold-related effects were less stable. Overall, results suggest that higher ambient temperatures are associated with increased TB incidence, with delayed and nonlinear effects.

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HOW

This study used an ecological time-series design based on national surveillance data from Japan’s National Epidemiological Surveillance of Infectious Diseases system. Weekly counts of newly confirmed TB cases from 2007 to 2019 were collected for all 47 Japanese prefectures. Meteorological data—including mean temperature, minimum temperature, maximum temperature, and relative humidity—were obtained from monitoring stations located in each prefecture’s capital city. Diurnal temperature range (DTR) was calculated as the difference between daily maximum and minimum temperatures, and weekly averages were computed for analysis.

A two-stage meta-analysis framework was applied. In the first stage, generalized linear models with quasi-Poisson distribution and log link function were used to estimate prefecture-specific associations between temperature and TB incidence. To capture nonlinear and delayed effects, the study used distributed lag nonlinear models (DLNM) with natural cubic B-splines. Lag periods of up to 26 weeks were examined to evaluate delayed temperature effects on TB incidence.

Seasonality and long-term trends were controlled using natural cubic spline functions for week number and year. Additionally, autoregressive terms with 1- and 2-week lags were included to account for transmission dynamics and temporal autocorrelation. The minimum risk temperature (MMT) was identified from cumulative exposure-response curves, and relative risks for extreme cold and heat were calculated using the MMT as the reference.

In the second stage, mixed-effects meta-analysis was performed to pool prefecture-specific estimates and obtain national-level results. Meteorological variables such as mean temperature, diurnal temperature range, and relative humidity were included as meta-predictors to account for between-prefecture heterogeneity. Residual heterogeneity was assessed using Cochran’s Q-test and I-square statistics, and best linear unbiased predictions (BLUPs) were generated for prefecture-specific estimates.

Multiple sensitivity analyses were conducted to test robustness. These included varying degrees of freedom for seasonal adjustment, extending lag periods from 26 to 52 weeks, removing or adding autocorrelation terms, and replacing spline models with Fourier (trigonometric) terms. The findings remained largely consistent across models, supporting the robustness of the observed association between temperature and TB incidence.

Source: Wagatsuma, K., 2024. Association of ambient temperature with tuberculosis incidence in Japan: An ecological study. IJID regions, 12, p.100384.

Health-related quality of life among adults newly diagnosed with pulmonary TB in Lagos, Nigeria [TBN 056]

WHAT

This prospective cohort study examined changes in health-related quality of life (HRQOL) among patients with pulmonary tuberculosis (PTB) during six months of standard treatment in Lagos State, Nigeria. A total of 210 newly diagnosed PTB patients aged 15–70 years were recruited, with 194 (92.4%) completing the six-month follow-up. Most participants were male (63.3%), under 45 years of age (79.1%), and had low income, with 81.9% earning ≤45,000 Naira monthly. Nearly half (44.7%) were unemployed, and 10% reported losing employment due to illness, highlighting the socioeconomic burden associated with TB.

Clinical symptoms at baseline were common and included cough (80.5%), anorexia (68.6%), weight loss, breathlessness, fever, and chest pain. These symptoms progressively improved during treatment, although approximately one in five participants still reported cough at six months. About 80.5% of patients had bacteriologically confirmed PTB, and roughly one-fifth were HIV-positive. Nutritional status also improved over time, with underweight prevalence decreasing from 27.6% at baseline to 12.7% at six months.

Across the six-month treatment period, HRQOL scores improved significantly in all four WHOQOL-BREF domains: physical, psychological, social, and environmental. At baseline, the lowest score was observed in the environmental domain (45.27 ± 14.59), while the social domain had the highest score (50.98 ± 17.37), which remained the highest at treatment completion. Repeated-measures ANOVA demonstrated statistically significant improvements across all domains, with partial eta squared values ranging from 0.178 to 0.295, indicating moderate to large effect sizes.

The most substantial improvements in HRQOL occurred during the first two months of treatment, particularly in overall satisfaction with health, physical health, and psychological domains. Improvements between months two and six were smaller, suggesting that the intensive treatment phase contributed most to quality-of-life gains. Notably, although social domain scores were consistently highest, they showed the smallest magnitude of improvement across the treatment period.

General satisfaction with health improved substantially during treatment, increasing from 13.5% at baseline to 55.7% at six months. Effect size analysis showed large improvements between baseline and six-month measurements across most domains, while changes between the second and sixth months were smaller. A statistically significant linear trend across time points indicated steady improvement in HRQOL during treatment.

Multivariable analysis identified key factors influencing HRQOL improvement. Employment status was positively associated with better HRQOL across all domains. Persistent symptoms were negatively associated with quality of life, while improvement in body mass index (BMI) was linked to better physical, psychological, and social outcomes. Delayed presentation negatively affected social domain scores but showed a positive association with environmental domain changes. Overall, clinical recovery, improved nutrition, and socioeconomic stability were important determinants of HRQOL improvement.

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HOW

This study used a prospective cohort design conducted in publicly owned TB-DOTS centers across Lagos State, Nigeria, to ensure consistent treatment guidelines and facility characteristics. Participants were recruited immediately after diagnosis and followed for six months, with assessments conducted at baseline, after the two-month intensive treatment phase, and within two weeks after completing treatment. The overall study duration was 15 months.

Eligibility criteria included individuals aged 15 years or older who were newly diagnosed with pulmonary tuberculosis and had received less than four weeks of prior TB treatment. Patients with severe illness, pre-existing chronic respiratory diseases such as asthma or COPD, or prior TB treatment were excluded. Facilities were selected based on their capacity to diagnose and treat TB and HIV and at least two years of TB service provision.

A two-stage sampling method was applied. First, one local government area from each of three senatorial districts in Lagos State was selected using simple random sampling. Then, one eligible TB treatment facility was randomly selected within each district. Patients were consecutively recruited at each facility until the required sample size was reached.

Data collection used interviewer-administered questionnaires capturing socio-demographic characteristics, clinical history, employment status, and symptoms. Height and weight were measured, and body mass index (BMI) calculated. All participants were offered HIV counseling and testing. Sputum microscopy results were extracted from patient records during follow-up visits.

Health-related quality of life was assessed using the WHOQOL-BREF instrument, which evaluates four domains: physical, psychological, social relationships, and environmental wellbeing. The instrument includes 26 items scored on a Likert scale from 1 to 5, with higher scores indicating better quality of life. Both English and Yoruba versions were used, with translation and back-translation procedures conducted to ensure accuracy.

The WHOQOL-BREF demonstrated strong reliability and validity in this study. Cronbach’s alpha exceeded 0.80 across all domains, indicating high internal consistency. Convergent validity was assessed using Pearson correlation coefficients between domain scores and global quality-of-life items, with values ranging from 0.433 to 0.801, indicating moderate to strong correlations. Statistical analysis included repeated-measures ANOVA, effect size estimation, and multivariable regression to identify predictors of HRQOL change.

Source: Adebayo, B.I., Adejumo, O.A. and Odusanya, O.O., 2024. Health-related quality of life among adults newly diagnosed with pulmonary tuberculosis in Lagos State, Nigeria: A prospective study. Quality of life research, 33(1), pp.157-168.

Tuberculosis survivors and the risk of cardiovascular disease in Korea [TBN 055]

WHAT

This nationwide population-based study examined the association between prior pulmonary tuberculosis (TB) and 10-year atherosclerotic cardiovascular disease (ASCVD) risk among Korean adults. Using data from the Korea National Health and Nutrition Examination Survey (KNHANES), the analysis included 69,331 participants after excluding individuals with missing weight variables or ASCVD data. Among the final sample, 3,101 participants (approximately 4%) were classified as post-TB survivors, while 66,230 participants (96%) had no history of TB and served as the control group.

Baseline characteristics showed that individuals with prior TB differed substantially from those without TB. The post-TB group was older on average (53.73 vs. 45.35 years), had a higher proportion of men (60.20% vs. 49.53%), and included more underweight individuals (6.58% vs. 4.33%). They were also more likely to be smokers (53.84% vs. 44.60%), less likely to be unmarried (10.01% vs. 23.01%), had lower household income (25.88% vs. 30.55% high income), and had lower educational attainment (P < 0.001 for all comparisons).

Comorbidity burden was also higher among post-TB survivors. Compared with controls, the post-TB group had higher prevalence of asthma (5.75% vs. 2.76%), stroke (2.33% vs. 1.46%), chronic obstructive pulmonary disease (2.41% vs. 0.33%), diabetes mellitus (14.04% vs. 10.32%), hypertension (35.16% vs. 26.48%), cardiovascular disease (5.11% vs. 3.11%), liver cirrhosis (0.64% vs. 0.22%), and cancer history (4.46% vs. 2.96%) (P < 0.001 for all). Depression was also more common in the post-TB group (4.66% vs. 3.65%, P = 0.012), while dyslipidemia was slightly higher but not statistically significant (53.69% vs. 51.89%, P = 0.105).

When comparing cardiovascular risk, post-TB survivors demonstrated significantly higher 10-year ASCVD risk. The proportion of participants classified in the high-risk category was markedly greater in the post-TB group compared with controls (40.46% vs. 24.00%, P < 0.001). Logistic regression analysis further showed that prior TB was associated with increased cardiovascular risk. Compared with controls, post-TB survivors had higher odds of intermediate ASCVD risk (OR 1.14, 95% CI 1.04–1.23) and substantially higher odds of high ASCVD risk (OR 1.69, 95% CI 1.59–1.78).

Among individuals with TB, several factors were independently associated with cardiovascular disease in multivariable analysis. Increasing age (adjusted OR [aOR] 1.10, 95% CI 1.07–1.12), current smoking (aOR 2.63, 95% CI 1.34–5.14), high family income (aOR 2.48, 95% CI 1.33–4.62), diabetes mellitus (aOR 1.97, 95% CI 1.23–3.14), and depression (aOR 2.06, 95% CI 1.03–4.10) were significantly associated with increased cardiovascular disease risk among post-TB survivors. These findings suggest that individuals with prior TB represent a population with elevated cardiovascular risk and multiple contributing risk factors.

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HOW

This study used data from the Korea National Health and Nutrition Examination Survey (KNHANES), a nationwide population-based surveillance system conducted by the Korea Disease Control and Prevention Agency since 1998. The analysis included five survey cycles: KNHANES IV (2007–2009), V (2010–2012), VI (2013–2015), VII (2016–2018), and VIII (2019). Participants were selected using a stratified multistage sampling design to ensure national representativeness.

During the 13-year study period, 105,732 individuals without age restrictions were initially enrolled. Participants with missing weight data or missing 10-year ASCVD risk values (n = 36,401) were excluded, leaving 69,331 participants in the final analytic sample. Participants were categorized into two groups based on prior TB diagnosis. Previous pulmonary TB was defined as either a physician-diagnosed history of pulmonary TB or formal chest radiograph interpretation indicating prior TB.

The primary outcome was 10-year ASCVD risk, calculated using the American Heart Association risk equations. This risk model incorporates multiple variables, including age, sex, race, cholesterol levels, blood pressure, medication use, diabetes status, and smoking history. ASCVD risk was categorized into four groups: low risk (0–4.9%), borderline risk (5.0–7.4%), intermediate risk (7.5–20%), and high risk (>20%).

Demographic, socioeconomic, and clinical variables were obtained from the KNHANES database. These included age, sex, waist circumference, body mass index (BMI), smoking status, alcohol consumption, marital status, income, and educational level. BMI was categorized using Asian-specific criteria: underweight (<18.5 kg/m²), normal (18.5–22.9 kg/m²), overweight (23.0–24.9 kg/m²), and obese (≥25.0–29.9 kg/m²). Heavy alcohol consumption was defined as more than 30 g/day.

Comorbidities were defined primarily using physician-reported diagnoses. Diabetes mellitus was defined as fasting glucose ≥126 mg/dL, use of antidiabetic medications, or physician diagnosis. Hypertension was defined as physician diagnosis, antihypertensive medication use, systolic blood pressure ≥140 mmHg, or diastolic blood pressure ≥90 mmHg. Dyslipidemia was defined by physician diagnosis, lipid-lowering medication use, total cholesterol ≥240 mg/dL, or fasting triglycerides ≥200 mg/dL.

Source: Yang, J., Kim, S.H., Sim, J.K., Gu, S., Seok, J.W., Bae, D.H., Cho, J.Y., Lee, K.M., Choe, K.H., Lee, H. and Yang, B., 2024. Tuberculosis survivors and the risk of cardiovascular disease: analysis using a nationwide survey in Korea. Frontiers in Cardiovascular Medicine, 11, p.1364337.

LTBI among Household Contacts of Drug-sensitive Pulmonary TB Patients in Medan, Indonesia [TBN 054]

WHAT

This study examined the prevalence of latent tuberculosis infection (LTBI) among household contacts of pulmonary tuberculosis (TB) patients in Medan, Indonesia. Among 102 household contacts of 62 drug-sensitive pulmonary TB index cases, 30 individuals (29.41%) were diagnosed with LTBI, 60 individuals (58.82%) tested negative, and 12 individuals were diagnosed with active pulmonary TB and excluded from the LTBI analysis. Thus, the final analytic sample included 90 household contacts.

The study also evaluated potential risk factors associated with LTBI, including age, sex, occupation, educational level, nutritional status, comorbidities, smoking behavior, alcohol consumption, and duration of household contact. The majority of participants were female (76.6%), with the most common age group among LTBI cases being 46–55 years, while the non-LTBI group was most commonly aged 26–35 years. Most participants had senior high school education, did not smoke, did not consume alcohol, and reported no comorbidities. Contact duration of ≥5 hours per day was common in both groups.

Bivariate analysis demonstrated that none of the assessed variables were significantly associated with LTBI. Specifically, age, gender, educational level, occupation, nutritional status, comorbidities, smoking, alcohol consumption, and contact duration showed no statistically significant relationship with LTBI occurrence (p > 0.05). These findings suggest that LTBI among household contacts may occur regardless of commonly measured demographic, behavioral, or clinical risk factors.

Overall, the study found a relatively high prevalence of LTBI among household contacts of pulmonary TB patients. The authors concluded that these findings highlight the importance of strengthening contact investigation programs and expanding TB preventive treatment among household contacts, particularly in high-burden urban settings such as Medan.

HOW

This study used a cross-sectional design conducted in Medan, an urban city and the capital of North Sumatra, Indonesia, with a population of approximately 2.47 million people. Pulmonary TB index cases were identified from hospitals, clinics, and community health centers (Puskesmas). Eligible index cases were pulmonary TB patients with sputum positive for Mycobacterium tuberculosis and rifampicin-sensitive results confirmed using the Xpert MTB/RIF test. Verification of index cases was performed using the Indonesian Tuberculosis Information System (SITB).

Household contacts aged 15 years and older who lived in the same household as pulmonary drug-sensitive TB patients and consented to participate were recruited using consecutive sampling between October 1 and December 5, 2023. Family members of extrapulmonary TB patients and individuals diagnosed with active TB during contact investigation were excluded. The minimum sample size calculated using the Lemeshow formula was 99 participants, and 102 household contacts were ultimately enrolled.

Data collection included structured interviews, anthropometric measurements, Interferon-Gamma Release Assay (IGRA) testing, chest X-ray examination, and sputum testing when clinically indicated. Interviews collected demographic information, education, occupation, smoking behavior, alcohol consumption, comorbidities, and duration of contact with the index case. Nutritional status was assessed using body mass index derived from height and weight measurements.

LTBI was defined as a positive QuantiFERON-TB Gold Plus (QFT-Plus) IGRA result with a normal chest X-ray and absence of TB symptoms. Participants with abnormal chest X-ray findings or symptoms suggestive of TB underwent sputum examination using Xpert MTB/RIF testing. Individuals diagnosed with active TB, either microbiologically confirmed or clinically diagnosed, were excluded from the LTBI analysis.

Source: Sinaga, B.Y.M., Siregar, J., Sormin, D.E., Sundari, R. and Samodra, Y.L., 2025. Latent Tuberculosis Infection among Household Contacts of Drug-sensitive Pulmonary Tuberculosis Patients: A Cross-sectional Study from Medan, Indonesia. Acta Medica Philippina, 59(19), p.84-90.

Long-term risk of death after tuberculosis diagnosis and treatment [TBN 053]

What

Tuberculosis (TB) is widely recognized as a treatable and curable disease, yet this study shows that its consequences extend far beyond the active infection phase. Individuals who survive TB continue to face a significantly elevated risk of death for many years after diagnosis and even after completing treatment. This long-term mortality burden is largely overlooked in public health frameworks, with no dedicated guidance from global authorities such as the WHO to address post-TB health risks. The persistence of this risk is thought to arise from a combination of biological damage—such as permanent lung impairment and chronic inflammation—as well as ongoing social and health vulnerabilities, including comorbid conditions and poverty.

The magnitude and duration of excess mortality are substantial. Immediately after TB diagnosis, mortality risk is extremely high, particularly within the first month, and although it declines over time, it remains elevated even 14 years later. Individuals who complete treatment fare better than those newly diagnosed, but still experience roughly double the mortality risk of comparable TB-free individuals over the long term. Importantly, this is not just a relative effect; the absolute number of excess deaths is large, indicating a significant population-level burden that persists well beyond clinical recovery.

This increased mortality risk spans multiple causes of death rather than being limited to TB-related complications. Elevated risks are observed for cardiovascular disease, respiratory conditions, cancer, and metabolic disorders. Certain patterns stand out: respiratory and cancer-related deaths are particularly high shortly after diagnosis or treatment, while cardiovascular mortality becomes more prominent over time. Additionally, deaths from external causes—especially assaults—are also higher among TB-affected individuals, suggesting that social determinants and environmental risks play a meaningful role alongside biological factors.

The impact of TB on mortality is not uniform across populations. Younger adults show higher relative risks, whereas older individuals bear a greater absolute burden of excess deaths. Differences by sex are modest, though slightly higher risks are observed among women in some contexts. Disease severity also matters: individuals with extrapulmonary or mixed forms of TB tend to have worse outcomes than those with pulmonary TB alone. Comorbidities further amplify risk, with diabetes emerging as a particularly important factor—associated with even greater absolute excess mortality than HIV in this study. Notably, household contacts of TB patients also exhibit modestly increased mortality, reinforcing the role of shared socioeconomic and environmental exposures.

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How

This study was designed as a large-scale retrospective cohort analysis using nationwide administrative data from Brazil. It leveraged the “100 Million Brazilian Cohort,” which captures over 130 million individuals enrolled in social welfare programs and represents predominantly low-income populations. These data were linked to national TB notification records and mortality registries, allowing researchers to follow individuals over time and assess long-term outcomes with high completeness and reliability. The study period spanned from 2004 to 2018, providing sufficient duration to evaluate long-term mortality trends.

Two main exposure groups were defined: individuals at the time of TB diagnosis and individuals who had successfully completed TB treatment. Each exposed individual was matched to a TB-free control using exact matching on a wide range of demographic and socioeconomic variables, including age, sex, race or ethnicity, geographic location, housing conditions, and household characteristics. This matching approach was designed to minimize confounding by ensuring that exposed and unexposed groups were highly comparable at baseline, particularly with respect to social determinants of health.

The study focused primarily on “natural deaths,” defined as deaths excluding TB, HIV, and external causes, in order to isolate the indirect and longer-term physiological consequences of TB. Secondary outcomes included all-cause mortality and specific causes of death, such as cardiovascular disease, cancer, respiratory illness, metabolic disorders, and external causes like accidents and assaults. Mortality outcomes were classified using standardized ICD-10 codes, enabling consistent categorization across the dataset.

Participants were followed from the point of TB diagnosis or treatment completion until death, the end of the study period, or (for controls) a subsequent TB diagnosis. Statistical analysis used the Aalen–Johansen estimator to calculate cumulative incidence while accounting for competing risks from different causes of death. Key measures included risk ratios, incidence rate ratios, and absolute risk differences, providing both relative and population-level perspectives on mortality risk over time.

To ensure data quality and interpretability, several exclusion criteria were applied, including removal of individuals with missing key variables, implausible dates, prior TB diagnoses before cohort entry, or extreme ages. Additional subgroup analyses were conducted to examine variation in mortality risk by age, sex, comorbidities, TB type, and household exposure. The study also incorporated analyses of household contacts, allowing for comparison between TB patients and individuals sharing similar living environments, further strengthening the interpretation of both biological and social drivers of long-term mortality.

Source: Cerqueira-Silva, T., Boaventura, V.S., Paixão, E.S., Sanchez, M., Leyrat, C., Ranzani, O., Barreto, M.L. and Pescarini, J.M., 2026. Long-term risk of death after tuberculosis diagnosis and treatment. Nature Medicine, pp.1-8.

Medication Adherence among Drug-Resistant Tuberculosis Patients at UI Hospital

Who

The study involved 87 drug-resistant tuberculosis (DR-TB) patients aged 18 years or older who were receiving treatment and attending routine monthly follow-up visits at Universitas Indonesia Hospital. Most participants were male and aged 18–59 years.

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What

The study assessed medication adherence levels among DR-TB patients. Results showed that 50.6% of patients had low adherence, 47.1% moderate adherence, and only 2.3% high adherence. Adherence was significantly associated with gender, and tended to be higher among females, patients aged 18–59 years, those with secondary education, new TB cases, and patients receiving long-term treatment regimens.

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When

The study was conducted between February and March 2024.

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Where

The research took place at Universitas Indonesia Hospital in Depok City, Indonesia.

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Why

The study aimed to evaluate treatment adherence among DR-TB patients, as poor adherence can compromise treatment effectiveness, prolong therapy, and increase the risk of poor clinical outcomes in DR-TB management.

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How

An observational cross-sectional study design was used. Data were collected using the validated Indonesian version of the Morisky Medication Adherence Scale (MMAS-8). Adherence scores were classified into low (<6), moderate (6 to <8), and high (8). Associations between patient characteristics and adherence levels were analyzed.

Source: Harahap, D.W.S., Andrajati, R., Sari, S.P. and Handayani, D., 2024. Medication Adherence among Drug-Resistant Tuberculosis (DR-TB) Patients at Universitas Indonesia Hospital. Jurnal Respirologi Indonesia, 44(3), pp.196-200.

The association between TB–HIV coinfection and DR-TB treatment failure

Who

The study included 4,261 drug-resistant tuberculosis (DR-TB) patients aged 15 years or older who were diagnosed, treated, and recorded in the Indonesian Tuberculosis Information System (SITB) during 2022–2023. Among them, 153 patients had TB–HIV coinfection and 4,108 did not. Patients who were lost to follow-up (1,051 cases) were excluded.

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What

The study examined the association between TB–HIV coinfection and DR-TB treatment failure. The findings showed that TB–HIV coinfection was significantly associated with a higher risk of treatment failure. After adjusting for age, patients with TB–HIV coinfection had a 2.3 times higher risk of DR-TB treatment failure compared with patients without TB–HIV coinfection.

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When

Data were collected from the 2022–2023 SITB database, with treatment outcomes evaluated up to 2023, accounting for the long duration of DR-TB treatment (up to 20 months).

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Where

The study was conducted in Indonesia, using nationwide data from the Indonesian Tuberculosis Information System (SITB).

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Why

The research aimed to address the limited evidence on whether TB–HIV coinfection contributes to DR-TB treatment failure in Indonesia, while controlling for important confounding factors such as age, TB–DM coinfection, sex, and type of anti-tuberculosis drug regimen.

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How

An observational analytic retrospective cohort design was used with secondary data from SITB. DR-TB diagnosis was based on Xpert MTB/RIF testing. HIV status was determined using HIV rapid tests, and TB–DM coinfection was assessed using rapid blood glucose tests. Treatment outcomes were categorized into treatment failure and treatment success. Statistical analyses included bivariate analysis, stratified analysis, homogeneity testing, and multivariable logistic regression to identify confounders and calculate adjusted odds ratios (AORs).

Source: Laili, F., Ronoatmodjo, S. and Murtiani, F., 2024. Ko-Infeksi TB-HIV terhadap Kegagalan Pengobatan Pasien Tuberkulosis Resistan Obat di Indonesia. The Indonesian Journal of Infectious Diseases, 10(2), pp.153-165.