1. TB Infection Estimates and Changing Paradigms
- Traditional TB burden estimates suggest ~1.8 billion people infected globally, based on immune reactivity, assuming lifelong infection.
- Current tests (IGRA, TST) can't determine bacterial viability or differentiate recent from old infections.
- New research challenges the latent/active TB binary, suggesting TB exists on a spectrum and many may self-clear infection.
- More precise diagnostics are needed to identify those truly at risk of disease progression and improve cost-effectiveness of TB preventive treatment (TPT).
See also: Lin TB Lab
2. Challenges and Gaps in TB Preventive Treatment (TPT)
- The TB prevention cascade (risk identification to treatment adherence) sees major drop-offs, with <20% completing all steps.
- Coverage among HIV-positive individuals is better but still suboptimal; even lower among other groups like migrants.
- Global TPT targets (e.g., 90% for PLHIV, 24M contacts by 2022) have not been met; new 2027 UN goals aim to reach 45M people, requiring intensified efforts.
- Community-based testing, digital tools, patient incentives, and improved contact tracing are promising strategies for boosting coverage and completion.
3. Evolving TPT Regimens and Future Innovations
- Traditional isoniazid preventive therapy (IPT) is limited by side effects and long duration.
- Shorter rifamycin-based regimens (3HR, 3HP, 1HP) improve adherence and safety but may still face cost/adverse event issues.
- Pediatric-friendly formulations are in development.
- A future pan-TPT regimen (e.g., single-dose, slow-release) could transform prevention, similar to vaccines or mass deworming campaigns.
See also: Yoseph Samodra
4. Data-Driven Screening and Risk Prediction Tools
- Community Scoring Model: A new predictive model outperforms WHO symptom-based TB screening tools, especially when stratified by HIV status; it improves detection and cost-effectiveness in real-world settings.
- Administrative Risk Model (Canada): A validated tool based on health records identifies high-risk individuals, particularly migrants, but needs further calibration for certain subgroups (e.g., elderly, refugees, HIV+).
- These tools support more targeted screening and resource use, enhancing early intervention.
5. Clinical Predictors of TB Mortality in the Elderly
- A competing-risk model in China found age (≥85), retreatment, cavities, hypoalbuminemia, and elevated CRP as strong predictors of TB-specific mortality in older adults.
- Developed a nomogram with high predictive accuracy to support personalized treatment planning for elderly TB patients.
6. Isoniazid Monoresistance and Early Treatment Outcomes
- Large Taiwanese cohort showed isoniazid resistance does not broadly impact early treatment outcomes.
- However, younger adults and patients without comorbidities may face delayed culture conversion and slightly worse outcomes.
- These subgroups may need closer monitoring and tailored care despite overall neutral findings.
7. Environmental Risk Factor: Air Pollution and TB
- A large Chinese study linked outdoor air pollutants—especially CO, SO₂, NO₂, PM₁₀, and PM₂.₅—to increased PTB risk, with pollutant-specific lag effects.
- Stronger impacts were seen during colder seasons.
- Highlights air quality control as a potential strategy in TB prevention.
8. Long-Term Trend Analysis with Age-Period-Cohort (APC) Models
- APC models help disentangle the roles of age, period, and cohort in TB incidence trends.
- Despite methodological challenges, they provide valuable insights into shifting epidemiology and help identify high-risk groups.
- Growing use in TB research supports better-targeted public health strategies when paired with contextual understanding.
References:
- Matteelli, A., Churchyard, G., Cirillo, D., den Boon, S., Falzon, D., Hamada, Y., Houben, R.M., Kanchar, A., Kritski, A., Kumar, B. and Miller, C., 2024. Optimizing the cascade of prevention to protect people from tuberculosis: A potential game changer for reducing global tuberculosis incidence. PLOS Global Public Health, 4(7), p.e0003306.
- Yang, C.C., Shih, Y.J., Ayles, H., Godfrey-Faussett, P., Claassens, M. and Lin, H.H., 2024. Cost-effectiveness analysis of a prediction model for community-based screening of active tuberculosis. Journal of Global Health, 14, p.04226.
- Li, Z., Liu, Q., Chen, L., Zhou, L., Qi, W., Wang, C., Zhang, Y., Tao, B., Zhu, L., Martinez, L. and Lu, W., 2024. Ambient air pollution contributed to pulmonary tuberculosis in China. Emerging Microbes & Infections, 13(1), p.2399275.
- Puyat, J.H., Brode, S.K., Shulha, H., Romanowski, K., Menzies, D., Benedetti, A., Duchen, R., Huang, A., Fang, J., Macdonald, L. and Marras, T.K., 2025. Predicting Risk of Tuberculosis (TB) Disease in People Who Migrate to a Low-TB Incidence Country: Development and Validation of a Multivariable, Dynamic Risk-Prediction Model Using Health Administrative Data. Clinical Infectious Diseases, 80(3), pp.644-652.
- Wang, S., Gu, R., Ren, P., Chen, Y., Wu, D. and Li, L., 2025. Prediction of tuberculosis-specific mortality for older adult patients with pulmonary tuberculosis. Frontiers in Public Health, 12, p.1515867.
- Lee, M.R., Keng, L.T., Lee, M.C., Chen, J.H., Lee, C.H. and Wang, J.Y., 2024. Impact of isoniazid monoresistance on overall and vulnerable patient populations in Taiwan. Emerging Microbes & Infections, 13(1), p.2417855.
- Luo, D., Wang, F., Chen, S., Zhang, Y., Wang, W., Wu, Q., Ling, Y., Zhou, Y., Li, Y., Liu, K. and Chen, B., 2025. Application of the age-period-cohort model in tuberculosis. Frontiers in Public Health, 13, p.1486946.
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