SynthesisJournal of clinical microbiology2022
Biomarkers That Correlate with Active Pulmonary Tuberculosis Treatment Response: a Systematic Review and Meta-analysis.
Synthesis in Journal of clinical microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 3 of them syntheses that pooled it.
What it found
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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.
The trial behind it
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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Who cites it
48 citing papers in PubMed, 3 syntheses or guidelines pooled it, 56 citations in OpenAlex.
- Reproducibility of liver iron concentration measured by R2* method based on 1.5-T MRI: a meta-analysis.European radiology · 2025Pooled it
- CXCL9/CXCL10 as biomarkers the monitoring of treatment responses in Pulmonary TB patients: a systematic review and meta-analysis.BMC infectious diseases · 2024Pooled it
- Tryptophan and Its Derived Metabolites as Biomarkers for Tuberculosis Disease: A Systematic ReviewIranian biomedical journal · 2024Pooled it
- Blood transcriptomic signatures predict poor outcomes in drug-susceptible pulmonary tuberculosis in Brazil.American journal of respiratory and critical care medicine · 2026Article
- Serum tuberculosis biomarkers and their association with clinical characteristics among hospitalized adults living with HIV in Uganda.Journal of clinical tuberculosis and other mycobacterial diseases · 2026Article
- Tuberculosis-Related Hospitalization According to Comorbidity Burden: A Retrospective Single-Center Cohort Study.Tropical medicine and infectious disease · 2026Article
- The study of immunological markers in tuberculosis across animal models and its translation to human research.Lab animal · 2026Review
- Does Tuberculosis Leave a Thromboinflammatory Memory After Cure? A Narrative Review with a Conceptual Framework on Hypercoagulability, Cellular Reservoirs, and Extracellular Vesicle Signaling.International journal of molecular sciences · 2026Review
- Metabolomic Biomarkers for Monitoring Tuberculosis Treatment Response: A Comprehensive Literature Review.Diagnostics (Basel, Switzerland) · 2026Review
- Beyond tumor biology: nursing interventions for psychological and immune health in cancer patients.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026Review
- Article
- C-Reactive Protein for Pulmonary Tuberculosis Screening and Treatment Response Monitoring in Children.Open forum infectious diseases · 2026Article
- Article
- Host-response biomarkers for precision tuberculosis: from immune transcriptomic signatures to clinical risk stratification.Frontiers in cell and developmental biology · 2026Review
- Transformer-based ensemble framework for tuberculosis treatment response prediction: multi-omics integration with clinical-grade performance.Frontiers in molecular biosciences · 2026Article
- Integrative transcriptomic meta-analysis reveals conserved transcriptional signatures and predictive biomarkers for active tuberculosis: a pathway-based machine learning approach.Frontiers in microbiology · 2026Article
- Blood transcriptomic signatures predict poor treatment outcomes in drug-susceptible pulmonary TB in Brazil.medRxiv : the preprint server for health sciences · 2025Article
- A cytoderm metabolic labeling TPAPy-Tre for real-time detection of vitality ofMicrobiology spectrum · 2025Article
- Evaluation of the PATHFAST TB LAM Ag assay as a treatment monitoring tool for pulmonary tuberculosis in Nairobi, Kenya.Tropical medicine and health · 2025Article
- A plasma proteomic signature of the actin-coagulation axis accurately predicts progression to active tuberculosis.Frontiers in microbiology · 2025Article
Corrections and comments
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Authors and funding
10 authors at 5 institutions in 5 countries.
Funding
Abstract
Current WHO recommendations for monitoring treatment response in adult pulmonary tuberculosis (TB) are sputum smear microscopy and/or culture conversion at the end of the intensive phase of treatment. These methods either have suboptimal accuracy or a long turnaround time. There is a need to identify alternative biomarkers to monitor TB treatment response. We conducted a systematic review of active pulmonary TB treatment monitoring biomarkers. We screened 9,739 articles published between 1 January 2008 and 31 December 2020, of which 77 met the inclusion criteria. When studies quantitatively reported biomarker levels, we meta-analyzed the average fold change in biomarkers from pretreatment to week 8 of treatment. We also performed a meta-analysis pooling the fold change since the previous time point collected. A total of 81 biomarkers were identified from 77 studies. Overall, these studies exhibited extensive heterogeneity with regard to TB treatment monitoring study design and data reporting. Among the biomarkers identified, C-reactive protein (CRP), interleukin-6 (IL-6), interferon gamma-induced protein 10 (IP-10), and tumor necrosis factor alpha (TNF-α) had sufficient data to analyze fold changes. All four biomarker levels decreased during the first 8 weeks of treatment relative to baseline and relative to previous time points collected. Based on limited data available, CRP, IL-6, IP-10, and TNF-α have been identified as biomarkers that should be further explored in the context of TB treatment monitoring. The extensive heterogeneity in TB treatment monitoring study design and reporting is a major barrier to evaluating the performance of novel biomarkers and tools for this use case. Guidance for designing and reporting treatment monitoring studies is urgently needed.
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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.