Future Prospects for Using Clinical Phenotypes in Tuberculosis Precision Medicine—An Approach for Clinical Management

Developing shorter treatment regimens for tuberculosis requires careful characterization of the clinical phenotype, which is defined by patient characteristics, radiological extent of disease, mycobacterial burden, drug susceptibility, and host response. Advances in 'omics and model-informed precision dosing, as well as integrated algorithms using artificial intelligence, need to be adapted and validated in clinical trials to improve classification of patients for stratified treatment. When treatment is initiated based on the clinical phenotype, monitoring of treatment response can be improved by quantification of bacterial load, transcriptomic and epigenetic biosignatures for sputum-free monitoring, and assessing disease burden by radiological and symptom scoring tools. Many of these tools are suitable for high-endemic settings. Such integrated monitoring allows prompt drug adjustments for rapid reduction in bacterial load, which prevents development of drug resistance and achieves relapse-free cure even with shorter treatment.

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Publication Details

Journal
Clinical Infectious Diseases
Published
2025-12-02
DOI
https://doi.org/10.1093/cid/ciaf663
Primary Topic
Tuberculosis Research and Epidemiology
Type
article
Field-Weighted Citation Impact
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Future Prospects for Using Clinical Phenotypes in Tuberculosis Precision Medicine—An Approach for Clinical Management

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Future Prospects for Using Clinical Phenotypes in Tuberculosis Precision Medicine—An Approach for Clinical Management

Elin M. Svensson, Katarina Niward, Gustav Svärdhagen, Stellah Mpagama, Thomas B. Schön, Daniel Augustinsson, Clara Braian, Rovina Ruslami, Isabelle Öhrnberg, Bruchfeld Judith
article en

Abstract

Developing shorter treatment regimens for tuberculosis requires careful characterization of the clinical phenotype, which is defined by patient characteristics, radiological extent of disease, mycobacterial burden, drug susceptibility, and host response. Advances in 'omics and model-informed precision dosing, as well as integrated algorithms using artificial intelligence, need to be adapted and validated in clinical trials to improve classification of patients for stratified treatment. When treatment is initiated based on the clinical phenotype, monitoring of treatment response can be improved by quantification of bacterial load, transcriptomic and epigenetic biosignatures for sputum-free monitoring, and assessing disease burden by radiological and symptom scoring tools. Many of these tools are suitable for high-endemic settings. Such integrated monitoring allows prompt drug adjustments for rapid reduction in bacterial load, which prevents development of drug resistance and achieves relapse-free cure even with shorter treatment.

Clinical Infectious Diseases
Linköping University (SE), Uppsala University (SE), The University of Sydney (AU), Karolinska University Hospital (SE), Radboud University Nijmegen (NL), Fairfield Infectious Diseases Hospital (AU), Taronga Conservation Society Australia (AU), Radboud University Medical Center (NL), Westmead Hospital (AU), Karolinska Institutet (SE), UNSW Sydney (AU), Landstinget i Kalmar län (SE), Linköping University Hospital (SE), Padjadjaran University (ID), Nelson Mandela African Institution of Science and Technology (TZ)
Good health and well-being
Openalex Percentile: Top 28%
Tuberculosis Research and Epidemiology
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