A novel TB screening strategy developed by researchers at Queen Mary University of London promises to drastically enhance tuberculosis detection by simultaneously identifying both active and latent infections. Tuberculosis remains one of the deadliest infectious diseases globally, causing over a million deaths each year and posing a persistent public health challenge. Current TB screening protocols, primarily designed to detect either active disease or latent infection separately, often fail to capture the full scope of infection, leading to missed diagnoses and ongoing transmission. This innovative approach could transform TB control efforts by integrating immunological tests that detect dormant TB infection alongside conventional diagnostic methods, thereby increasing screening accuracy and enabling earlier intervention.
Tuberculosis, caused by the bacterium Mycobacterium tuberculosis, affects millions worldwide with 10.8 million new cases and approximately 1.25 million deaths recorded in 2023 alone. The disease’s complexity lies partly in its ability to remain latent within an individual for years without symptoms before potentially activating and causing severe illness. Detecting the dormant form of TB infection—often called latent TB infection (LTBI)—is vital for controlling the spread of the disease, particularly in high-risk populations such as migrants from endemic areas. However, existing diagnostic algorithms typically separate tests for latent and active TB, overlooking the interplay between the two stages and reducing overall diagnostic efficacy.
The Queen Mary-led study, recently published in the European Respiratory Journal, represents the first comprehensive analysis combining 13 different TB tests described across 437 original research articles and systematic reviews. The researchers employed advanced decision tree analytical modeling techniques to assess not only the sensitivity and specificity of individual tests but also the synergistic effects of combining them. Their rigorous meta-analysis revealed that integrating immunological assays for latent infection—specifically interferon gamma release assays (IGRAs)—with classical screening tools like chest X-rays and sputum cultures markedly improves the accuracy of detecting active TB cases, including difficult-to-diagnose extrapulmonary and pediatric TB.
Traditionally, TB diagnostics have bifurcated into methods targeting active disease, such as radiological imaging and microbiological culture, and those aimed at identifying latent infection, including the tuberculin skin test (TST) and IGRAs. While these tests were developed for distinct clinical purposes, this research challenges their isolated use. It demonstrates that TBI (tuberculosis infection) tests, when performed concurrently with active TB diagnostics, provide additive value by revealing immunological signatures indicating both ongoing infection and latent reservoirs. This dual detection not only enhances early identification but also reduces false-positive rates, minimizing unnecessary treatments that carry their own risks.
One of the pivotal findings of the study is the potential of IGRAs—a blood test measuring immune response to TB antigens—to elevate screening performance in migrant populations from high TB burden countries. Migrants often represent a substantial fraction of active TB cases in many low-incidence countries, yet current screening regimens may inadequately capture infection nuances within this group. Dr. Dominik Zenner, the study’s lead author and Clinical Reader in Infectious Disease Epidemiology, emphasizes that applying combined screening methodologies has “high accuracy for migrants” and can dramatically improve both individualized patient care and overarching public health benefits by curbing transmission chains.
The significance of this research extends beyond theoretical modeling to direct clinical and policy implications. Previous TB control strategies endorsed by the World Health Organization (WHO) and other global health bodies have not fully incorporated immunological tests for latent infection into standard active TB screening algorithms. By advocating for an inclusive approach that integrates IGRAs with conventional diagnostics, this study provides robust evidence supporting guideline revisions worldwide. Mario Raviglione, former Director of the WHO Global Tuberculosis Programme, lauds the study as “a sophisticated and well-thought investigation” with “major implications for clinical and public health practice,” underscoring the potential for widespread policy transformation.
Additionally, the study sheds light on the diagnostic challenges posed by extrapulmonary TB—cases where the infection manifests outside the lungs—and pediatric TB, both of which have historically evaded reliable detection. The enhanced sensitivity offered by combining immunological tests with standard diagnostics can facilitate earlier detection of these often overlooked forms of the disease, allowing for timely treatment interventions that prevent morbidity and mortality.
The public health importance of accurate and early TB diagnosis is underscored by epidemiological data from East London, which currently records the highest rates of newly diagnosed TB cases in Western Europe. TB disproportionately impacts deprived communities in this region, highlighting a critical need for improved screening practices tailored to vulnerable populations. Researchers at Queen Mary University have actively collaborated with Barts Health NHS Trust to establish a new centre of excellence for TB research and treatment, aiming to translate these scientific advances into effective clinical and community strategies.
By simultaneously detecting active and latent TB infection through optimized test combinations, the novel screening algorithm challenges long-standing diagnostic paradigms. It moves the field towards a more holistic, immunologically informed approach that acknowledges the continuum of Mycobacterium tuberculosis infection states. This reconceptualization not only has the potential to save countless lives through earlier treatment but also addresses key epidemiological drivers by intercepting latent cases before disease activation and transmission occur.
From a methodological perspective, the study’s reliance on systematic review and meta-analytic techniques confers exceptional rigor, as it synthesizes a vast body of evidence while applying sophisticated statistical modeling. Decision tree analyses allowed the team to simulate and compare multiple screening algorithm permutations, accurately projecting both their diagnostic yield and implications for false positive rates. This methodology exemplifies the power of integrating epidemiological data with cutting-edge analytical frameworks to resolve complex clinical challenges.
In conclusion, the breakthrough findings by the Queen Mary University of London team pave the way for a new era in TB diagnosis—one that unites immunological and traditional diagnostics to deliver a comprehensive and accurate detection strategy. Their research not only promises to revolutionize clinical pathways for migrants and other high-risk groups but also signals a critical step forward in global TB eradication efforts. Implementation of these algorithms could reduce TB incidence worldwide, saving lives and alleviating the burden on healthcare systems.
Subject of Research: People
Article Title: How to diagnose TB in migrants? A systematic review of reviews and decision tree analytical modelling exercise to evaluate properties for single and combined TB screening tests
News Publication Date: 24-Apr-2025
Web References: https://doi.org/10.1183/13993003.02000-2024
References: Zenner, D. et al. “How to diagnose TB in migrants? A systematic review of reviews and decision tree analytical modelling exercise to evaluate properties for single and combined TB screening tests.” European Respiratory Journal. DOI: 10.1183/13993003.02000-2024
Keywords: Tuberculosis, Public health, Disease control, Diagnostic accuracy
