Evidence map›Paper›PMID 40120087›Full record

ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2025

Paucibacillary Tuberculosis Drives the Low Positive Predictive Value of Xpert MTB/RIF Ultra for Rifampicin Resistance Detection in Low-Prevalence Settings.

Isabel Cuella-Martin, Francois Hakizayezu, Aymen Ahmed, Docteur Runyambo, Hosee Niyompano, Jelle Keysers, Willem Bram De Rijk, Wim Mulders, Ellen M H Mitchell, Tom Decroo and 6 more

Abstract read
In one paragraph

Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

16 authors.

Isabel Cuella-MartinMycobacteriology Unit, Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.ORCID 0000-0001-7543-3386
Francois HakizayezuNational Reference Laboratory Division, Department of Biomedical Services, Rwanda Biomedical Centre, Kigali, Rwanda.
Aymen AhmedResearch Innovation and Data Science Division, Rwanda Biomedical Centre, Kigali, Rwanda.ORCID 0000-0002-9516-9508
Docteur RunyamboNational Reference Laboratory Division, Department of Biomedical Services, Rwanda Biomedical Centre, Kigali, Rwanda.ORCID 0009-0006-6103-6703
Hosee NiyompanoNational Reference Laboratory Division, Department of Biomedical Services, Rwanda Biomedical Centre, Kigali, Rwanda.
Jelle KeysersMycobacteriology Unit, Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.ORCID 0009-0000-4685-7972
Willem Bram De RijkMycobacteriology Unit, Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.
Wim MuldersMycobacteriology Unit, Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.
Ellen M H MitchellMycobacterial Diseases and Neglected Tropical Diseases Unit, Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium.ORCID 0000-0002-2824-3499
Tom DecrooHIV and Tuberculosis Unit, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.ORCID 0000-0002-1205-1484
Yves Mucyo HabimanaTuberculosis and Other Respiratory Diseases Division, Rwanda Biomedical Centre, Kigali, Rwanda.
Patrick MigambiTuberculosis and Other Respiratory Diseases Division, Rwanda Biomedical Centre, Kigali, Rwanda.
Claude Mambo MuvunyiDepartment of Clinical Biology, Rwanda Biomedical Centre, Kigali, Rwanda.
Bouke C de JongMycobacteriology Unit, Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.ORCID 0000-0002-1017-4675
Leen RigoutsMycobacteriology Unit, Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.
Jean Claude Semuto NgabonzizaMycobacteriology Unit, Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.ORCID 0000-0002-6075-5603

Funding

Belgian Directorate General for Development CooperationFlemish Government, Science & Innovation DIR/av/2020/119ITM's SOFI programResearch Foundation-Flanders 1SE7622NThe Belgian Federal Public Service of Development Cooperation BE-BCE_KBO-0410057701-prg2022-13-RW
6 · The paper itself

Abstract

backgroundXpert MTB/RIF Ultra (Ultra) aimed to improve the specificity in identifying rifampicin-resistant tuberculosis (RR-TB), compared to Xpert MTB/RIF.

methodsIn a nationwide study in Rwanda, patients diagnosed with RR-TB by Ultra between December 2021 and January 2024 underwent repeat Ultra testing, complemented by rpoB gene sequencing and phenotypic drug-susceptibility testing (pDST), serving as reference tests.

resultsOf 129 patients initially diagnosed with RR-TB by Ultra, only 41 (32%) had concordant rifampicin results upon repeat Ultra testing. The remaining 88 patients (68%) had unconfirmed resistance on repeat Ultra. Reference testing was available for 40 (98%) of 41 confirmed cases, all verified as true RR-TB. Among 88 unconfirmed cases, reference testing was available for 61 (69%), with 7 (11%) confirmed as true RR-TB, whereas 54 (89%) were found to have rifampicin-susceptible TB. Notably, 89% of 55 patients with very low bacillary loads on their initial Ultra had false RR-TB results, a significantly higher risk of false resistance compared to other bacillary load categories combined (risk ratio: 8.20; 95% confidence interval [CI]: 3.56-18.85; P < .001). Consequently, 53% (54/101) of initial RR patients with available reference testing received unnecessary RR-TB treatment.

conclusionsUltra represents a valuable tool for rapid RR-TB detection; however, in low prevalence settings its low positive predictive value for RR detection is largely driven by samples with very low bacillary loads. As programs expand active case-finding and early detection of asymptomatic disease, the proportion of TB detected with very low bacillary load will increase. Diagnostic algorithms require adjustments to prevent unnecessary RR-TB treatment.

Indexed as

Antibiotics, AntitubercularDrug Resistance, BacterialMycobacterium tuberculosisRifampinTuberculosis, Multidrug-ResistantAdolescentAdultDNA-Directed RNA PolymerasesFemaleHumansMaleMicrobial Sensitivity TestsMiddle AgedMolecular Diagnostic TechniquesPredictive Value of TestsPrevalenceAntibiotics, AntitubercularDNA-Directed RNA PolymerasesRifampinfalse-positivepaucibacillary TBpositive predictive value (PPV)TB case managementXpert MTB/RIF ultra

Identifiers

PMID40120087
PMCPMC12448619

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Registered trials

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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.