ReviewThe Journal of infectious diseases2024
Does PET-CT Have a Role in the Evaluation of Tuberculosis Treatment in Phase 2 Clinical Trials?
Review in The Journal of infectious diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 16 citations in OpenAlex.
- PET-CT outcomes from a randomised controlled trial of rosuvastatin as an adjunct to standard tuberculosis treatment.Nature communications · 2024Trial
- Navigating Tuberculosis in Pregnancy and Lactation: A Review of Maternal and Neonatal Considerations.Diseases (Basel, Switzerland) · 2026Review
- Article
- Host- and pathogen-related determinants of pulmonaryEuropean respiratory review : an official journal of the European Respiratory Society · 2026Review
- Comparative Study of [Molecular imaging and biology · 2025Article
- New drugs for the management of tuberculosis.Current opinion in infectious diseases · 2025Review
- Characterizing PET CT patterns and bacterial dissemination features of tuberculosis relapse in the macaque model.Infection and immunity · 2025Article
- Review
- Diffuse lymphadenopathy with significantly elevated standardized uptake values on positron emission tomography-computed tomography: a case description of lymph node tuberculosis without lung lesions.Quantitative imaging in medicine and surgery · 2025Article
- Computed tomography in the diagnosis of bilateral renal tuberculosis: diagnostic value, limitations, and future directions.Frontiers in medical technology · 2025Review
- Recent Breakthroughs in PET-CT Multimodality Imaging: Innovations and Clinical Impact.Bioengineering (Basel, Switzerland) · 2024Review
- Incipient tuberculosis: a comprehensive overview.Infection · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 5 institutions in 6 countries.
Funding
Abstract
Positron emission tomography-computed tomography (PET-CT) has the potential to revolutionize research in infectious diseases, as it has done with cancer. There is growing interest in it as a biomarker in the setting of early-phase tuberculosis clinical trials, particularly given the limitations of current biomarkers as adequate predictors of sterilizing cure for tuberculosis. PET-CT is a real-time tool that provides a 3-dimensional view of the spatial distribution of tuberculosis within the lung parenchyma and the nature of lesions with uptake (ie, whether nodular, consolidative, or cavitary). Its ability to provide functional data on changes in metabolism, drug penetration, and immune control of tuberculous lesions has the potential to facilitate drug development and regimen selection for advancement to phase 3 trials in tuberculosis. In this narrative review, we discuss the role that PET-CT may have in evaluating responses to drug therapy in active tuberculosis treatment and the challenges in taking PET-CT forward as predictive biomarker of relapse-free cure in the setting of phase 2 clinical trials.
Indexed as
Identifiers
What OpenQuestion holds
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.