Published in PLOS One on 2025-12-22, this study is presented as an attributed evidence briefing. The excerpts below are the original researchers’ words, reproduced under their Creative Commons Attribution licence. Health Signal has selected the abstract and, where needed, opening background paragraphs; the complete methods, results, limitations and references remain in the linked paper.
Original authors: Sarapia P. Mallya, Peter M. Mbelele, Riziki M. Kisonga, Daphine D. Mtunga, Haroun H. Banzi, Stephen S. Mpiima, Muzafaru Twinomujuni, Joel Bazira, Kennedy Kassaza
Source: PLOS One • DOI 10.1371/journal.pone.0327936
Read the complete primary study ↗ · Creative Commons Attribution licence
From the researchers
Abstract
Tuberculosis (TB), caused by Mycobacterium tuberculosis remains a global threat, affecting 10.8 million people and causes 1.3 million deaths annually. Over 2.5 million cases go undiagnosed partly due to current diagnostic limitations. In particular, smear microscopy is less sensitive, culture is slow and prone to contamination, and the rapid Xpert® MTB/RIF Ultra (Ultra) needs advanced infrastructure. This study assessed the diagnostic accuracy of TrueNat™ MTB Plus assay (TrueNat), a portable, WHO-endorsed point-of-care tool, compared to Ultra, smear microscopy, and Löwenstein–Jensen (LJ) culture. This cross-sectional study enrolled 260 consenting adult participants (≥18 years) with presumptive TB in northern Tanzania. Participants’ sputum samples were tested for M. tuberculosis using smear microscopy, LJ culture, Ultra and TrueNat. TrueNat performance was assessed using sensitivity, specificity, predictive values and area under the curve (AUC) against the standard-of-care and a composite reference standard. Age and body-mass-index were summarised using median and interquatile range (IQR). Categorical variables were reported as proportions. Multivariate logistic regression identified TB predictors (p < 0.05). Data analysis and visualization were conducted using R. Among 260 participants, 165 (63.5%) were male, with a median age of 46.0 years (IQR: 35.5–57.3); 15 (5.8%) were HIV-positive, and 52 (20%) had undernutrition. TB was detected in 109 (41.9%) participants by at least one test. TrueNat showed sensitivity/specificity of 34.4%/94.7% vs. smear microscopy, 98.9%/95.3% vs. culture, and 86.2%/95.2% vs. Ultra. The AUC values were 0.75, 0.92, 0.96, and 0.91 compared to smear microscopy, LJ culture, Ultra, and a composite reference method, respectively. Participants reporting weight loss were 2.84 times more likely (95% CI: 1.68–4.84, p < 0.001) to test positive for TB by TrueNat. The TrueNat compared favorably to both Ultra and culture in terms of diagnostic accuracy, offering the added benefits of faster results and greater suitability for resource-limited settings. These findings suggest that TrueNat is a promising test for rapid TB detection in low-resource settings, warranting further studies to evaluate its implementation and impact on patient management.
Introduction
Tuberculosis (TB), caused by Mycobacterium tuberculosis remains a significant public health challenge globally. Over the past decade, annual TB incidence has persistently exceeded 10 million cases worldwide [1]. From 2015 to 2023, the global TB incidence rate declined by only 8.3%, falling far short of the WHO End TB Strategy milestone of a 50% reduction by 2025. In 2023, TB reclaimed its position as the leading cause of death from a single infectious disease, with 1.25 million fatalities, surpassing COVID-19 and causing nearly twice as many deaths as HIV/AIDS [1]. Sub-Saharan Africa accounted for 24% of the 10.8 million global TB cases, underlining the region’s disproportionate burden. Despite the WHO’s ambitious goal to end TB by 2030, progress remains off track. Concerningly, 2.7 million people were undetected and untreated in 2023, amplifying community transmission and increasing mortality by an estimated 50%. In Tanzania, 100,747 cases were notified, leaving a significant diagnostic gap with mortality reduction rate falling below 23%, far short of the 75% target set for 2025 [2].
Reading this evidence
Use the full paper to check the study design, participant selection, comparator and outcome definitions before drawing a practical conclusion. An association does not by itself show cause and effect. A reported performance measure needs its denominator and uncertainty. A finding from a particular facility, sample or time period should retain that scope when it is discussed elsewhere.
This briefing makes the source accessible within the wider technology & industry desk. It does not assess an individual patient or certify a product. When considering relevance to another health system, examine the original authors’ account of context and limitations, then seek local implementation evidence. The related reporting below provides other studies to read alongside this one; it is a topic connection, rather than a claim that their results are directly comparable.
© 2025 Sarapia P. Mallya, Peter M. Mbelele, Riziki M. Kisonga, Daphine D. Mtunga, Haroun H. Banzi, Stephen S. Mpiima, Muzafaru Twinomujuni, Joel Bazira, Kennedy Kassaza. Excerpts reproduced under CC BY. Selection, formatting and contextual notes by Health Signal. The researchers are the authors of the source study, not members of Health Signal’s staff.
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- Evidence brief: Contribution of xpert MTB/RIF assay and Urine LF-LAM for the diagnosis of tuberculosis in children aged 5 – 14 years, at selected health facilities in Ethiopia, 2016 – 2019
- Evidence brief: Challenges, innovations and considerations for the use of tongue swabs in Mycobacterium tuberculosis complex detection
- Evidence brief: Annual trends in Mycobacterium tuberculosis detection and rifampicin resistance at a regional referral hospital in Northern Ghana, 2019–2024
