ArticleBreathe (Sheffield, England)2026
Management of adverse events in TB care and active TB drug safety monitoring.
Article in Breathe (Sheffield, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tuberculosis (TB) remains the leading cause of death from a single infectious agent, with 10.8 million cases reported in 2023. While treatment is generally effective, both drug-susceptible (DS-TB) and drug-resistant TB (DR-TB) regimens are associated with adverse events (AEs) that compromise adherence and outcomes. In this viewpoint, we highlight the most clinically relevant AEs: hepatotoxicity, cutaneous reactions and ocular toxicity in DS-TB; and linezolid-associated neuropathy, myelosuppression, QT prolongation and hepatotoxicity in DR-TB. We argue that structured safety monitoring and integration of active TB Drug Safety Monitoring and Management into routine care are critical to improving patient safety. Looking ahead, pharmacogenomics, therapeutic drug monitoring, predictive algorithms and digital health solutions offer opportunities to move from reactive to proactive AE management. By prioritising monitoring, innovation and patient-centred approaches, TB programmes can reduce the burden of AEs, improve adherence and achieve better outcomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.