Evidence map›Paper›PMID 35373160›Full record

ArticleThe Lancet. Microbe2022

The 2021 WHO catalogue of

Timothy M Walker, Paolo Miotto, Claudio U Köser, Philip W Fowler, Jeff Knaggs, Zamin Iqbal, Martin Hunt, Leonid Chindelevitch, Maha Farhat, Daniela Maria Cirillo and 16 more

Open access · goldAbstract read
In one paragraph

Article in The Lancet. Microbe, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 181 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
181citing papers in PubMed, 2 pooled it
29.1field-weighted citation impact, top 1% of its field
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

181 citing papers in PubMed, 2 syntheses or guidelines pooled it, 286 citations in OpenAlex.

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  15. Predicting isoniazid resistance inJournal of clinical microbiology · 2026
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121 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

26 authors at 20 institutions in 18 countries.

Timothy M Walker *Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Paolo Miotto *San Raffaele Scientific Institute, Milano, Italy.
Claudio U Köser *Department of Genetics, University of Cambridge, Cambridge, UK.
Philip W FowlerNuffield Department of Medicine, University of Oxford, Oxford, UK.
Jeff KnaggsNuffield Department of Medicine, University of Oxford, Oxford, UK.
Zamin IqbalEuropean Bioinformatics Institute, Hinxton, UK.
Martin HuntNuffield Department of Medicine, University of Oxford, Oxford, UK.
Leonid ChindelevitchImperial College London, UK.
Maha FarhatHavard Medical School, Boston, USA.
Daniela Maria CirilloSan Raffaele Scientific Institute, Milano, Italy.
Iñaki ComasCIBER Epidemiology and Public Health, Madrid, Spain.
James PoseyCentres for Disease Control and Prevention, Atlanta, USA.
Shaheed V OmarNational Institute for Communicable Diseases, Johannesburg, South Africa.
Timothy Ea PetoNuffield Department of Medicine, University of Oxford, Oxford, UK.
Anita SureshThe Foundation for Innovative New Diagnostics, Geneva, Switzerland.
Swapna UplekarThe Foundation for Innovative New Diagnostics, Geneva, Switzerland.
Sacha LaurentThe Foundation for Innovative New Diagnostics, Geneva, Switzerland.
Rebecca E ColmanThe Foundation for Innovative New Diagnostics, Geneva, Switzerland.
Carl-Michael NathansonGlobal Tuberculosis Programme, World Health Organization, Geneva, Switzerland,*.
Matteo ZignolGlobal Tuberculosis Programme, World Health Organization, Geneva, Switzerland,*.
Ann Sarah WalkerNuffield Department of Medicine, University of Oxford, Oxford, UK.
CRyPTIC Consortium
Seq&Treat Consortium
Derrick W Crook *Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Nazir Ismail *Global Tuberculosis Programme, World Health Organization, Geneva, Switzerland,*.
Timothy C Rodwell *Division of Pulmonary, Critical Care and Sleep Medicine, University of California, San Diego, USA,*.
FIND · CHEuropean Bioinformatics Institute · GBVita-Salute San Raffaele University · ITNational Institute for Health Research · GBNational Institute for Communicable DiseasesWorld Health Organization · CHUniversity of Oxford · GBCenters for Disease Control and Prevention · USUniversity of Cambridge · GBBoston University · USImperial College London · GBInstituto Adolfo Lutz · BRInstituto de Biomedicina de Valencia · ESResearch Center Borstel - Leibniz Lung Center · DEChinese Academy of Sciences · CNChinese Center For Disease Control and Prevention · CNFoundation for Medical Research · INGates Foundation · USGerman Center for Infection Research · DEInstitut Pasteur de Madagascar · MG

Funding

Novel next-generation sequencing assay for monitoring multidrug resistant tuberculosis treatment in the setting of HIV infectionR01AI131939 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ENGELTHALER, DAVID M, METCALFE, JOHN ZAPATA · 2018 to 2023
$3.9M
Handheld and population-based sequencing for rapid detection of new and repurposed drug resistance in M. tuberculosisR01AI153213 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI David M Engelthaler, John Zapata Metcalfe · 2021 to 2026
$3.7M
Using the Mycobacterium tuberculosis Genome to Predict Tuberculosis Pathology, Drug Resistance Acquisition and Identify Community Transmission SitesR01AI146338 · NIAID · JOHNS HOPKINS UNIVERSITY · PI GILMAN, ROBERT H · 2020 to 2024
$3.3M
Medical Research Council MC_PC_16027Medical Research Council MR/R015600/1NIAID NIH HHS R01 AI146338Wellcome Trust 200205Wellcome Trust 214560World Health Organization 001
6 · The paper itself

Abstract

Background: Molecular diagnostics are considered the most promising route to achieving rapid, universal drug susceptibility testing for Methods: A candidate gene approach was used to identify mutations as associated with resistance, or consistent with susceptibility, for 13 WHO endorsed anti-tuberculosis drugs. 38,215 MTBC isolates with paired whole-genome sequencing and phenotypic drug susceptibility testing data were amassed from 45 countries. For each mutation, a contingency table of binary phenotypes and presence or absence of the mutation computed positive predictive value, and Fisher's exact tests generated odds ratios and Benjamini-Hochberg corrected p-values. Mutations were graded as Associated with Resistance if present in at least 5 isolates, if the odds ratio was >1 with a statistically significant corrected p-value, and if the lower bound of the 95% confidence interval on the positive predictive value for phenotypic resistance was >25%. A series of expert rules were applied for final confidence grading of each mutation. Findings: 15,667 associations were computed for 13,211 unique mutations linked to one or more drugs. 1,149/15,667 (7·3%) mutations were classified as associated with phenotypic resistance and 107/15,667 (0·7%) were deemed consistent with susceptibility. For rifampicin, isoniazid, ethambutol, fluoroquinolones, and streptomycin, the mutations' pooled sensitivity was >80%. Specificity was over 95% for all drugs except ethionamide (91·4%), moxifloxacin (91·6%) and ethambutol (93·3%). Only two resistance mutations were classified for bedaquiline, delamanid, clofazimine, and linezolid as prevalence of phenotypic resistance was low for these drugs. Interpretation: This first WHO endorsed catalogue of molecular targets for MTBC drug susceptibility testing provides a global standard for resistance interpretation. Its existence should encourage the implementation of molecular diagnostics by National Tuberculosis Programmes. Funding: UNITAID, Wellcome, MRC, BMGF.

Indexed as

EthambutolMycobacterium tuberculosisAntitubercular AgentsDrug ResistanceMicrobial Sensitivity TestsMutationWorld Health OrganizationAntitubercular AgentsEthambutol

Identifiers

PMID35373160
PMCPMC7612554
OpenAlexW3210823154

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.