Evidence map›Paper›PMID 41537599›Full record

ReviewClinical infectious diseases : an official publication of the Infectious Diseases Society of America2026

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

Katarina Niward, Clara Braian, Gustav Svärdhagen, Daniel Augustinsson, Isabelle Öhrnberg, Rovina Ruslami, Stellah Mpagama, Elin M Svensson, Judith Bruchfeld, Jan-Willem Alffenaar and 1 more

Abstract readReview
In one paragraph

Review in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Katarina NiwardDepartment of Infectious Diseases, Region Östergötland, Linköping University, Linköping, Sweden.ORCID 0000-0002-5290-5165
Clara BraianDepartment of Biomedical and Clinical Sciences, Division of Inflammation and Infection, Linköping University, Linköping, Sweden.ORCID 0000-0003-1784-2864
Gustav SvärdhagenDepartment of Biomedical and Clinical Sciences, Division of Inflammation and Infection, Linköping University, Linköping, Sweden.ORCID 0009-0004-1992-4219
Daniel AugustinssonDepartment of Infectious Diseases, Region Östergötland, Linköping University, Linköping, Sweden.ORCID 0009-0004-8269-193X
Isabelle ÖhrnbergDepartment of Infectious Diseases, Region Östergötland, Linköping University, Linköping, Sweden.ORCID 0009-0003-7950-2934
Rovina RuslamiDepartment of Biomedical Sciences, Faculty of Medicine, Universitas Padjadjaran, Bandung, Indonesia.ORCID 0000-0003-4995-5054
Stellah MpagamaDepartment of Infectious Diseases, Kibong'oto Infectious Diseases Hospital, Kilimanjaro, Tanzania.ORCID 0000-0002-0660-6930
Elin M SvenssonDepartment of Pharmacy, Uppsala University, Uppsala, Sweden.ORCID 0000-0002-0093-6445
Judith BruchfeldDepartment of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden.
Jan-Willem AlffenaarSydney Institute for Infectious Diseases, The University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0001-6703-0288
Thomas SchönDepartment of Infectious Diseases, Region Östergötland, Linköping University, Linköping, Sweden.

Funding

County of Östergötland, Sweden 09150161910052County of Östergötland, Sweden ALF 987589County of Östergötland, Sweden RÖ-1005642Dutch Research CouncilSwedish Heart-Lung Foundation 2022-0148Swedish Heart-Lung Foundation 2022-0238Swedish Research Council 2019-05912Swedish Research Council 2022-00865Swedish Research Council 2022-04041Swedish Research Council 2022-05263
6 · The paper itself

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.

Indexed as

Antitubercular AgentsPrecision MedicineTuberculosisBacterial LoadHumansMycobacterium tuberculosisPhenotypeAntitubercular Agentsdisease severityprecision medicinestratified treatmenttreatment monitoringtuberculosis

Identifiers

PMID41537599
PMCPMC13189667

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.