Evidence map›Paper›PMID 25765106›Full record

ReviewThe Journal of infectious diseases2015

Integration of published information into a resistance-associated mutation database for Mycobacterium tuberculosis.

Hugh Salamon, Ken D Yamaguchi, Daniela M Cirillo, Paolo Miotto, Marco Schito, James Posey, Angela M Starks, Stefan Niemann, David Alland, Debra Hanna and 3 more

Abstract readReview
In one paragraph

Review in The Journal of infectious diseases, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. A Comprehensive Review of Genetic Mechanisms ofInfection and drug resistance · 2026
    Review
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  9. Pyrazinamide Susceptibility andAntimicrobial agents and chemotherapy · 2017
    Article
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  14. Review
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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

13 authors.

Hugh SalamonKnowledge Synthesis Inc., Berkeley, California.
Ken D YamaguchiKnowledge Synthesis Inc., Berkeley, California.
Daniela M CirilloIRCCS San Raffaele Scientific Institute, Milan, Italy.
Paolo MiottoIRCCS San Raffaele Scientific Institute, Milan, Italy.
Marco SchitoHJF-DAIDS, a Division of The Henry M. Jackson Foundation for the Advancement of, Military Medicine, Inc., NIH, DHHS, Bethesda, Maryland.
James PoseyCenter for Disease Control and Prevention, Atlanta, Georgia.
Angela M StarksCenter for Disease Control and Prevention, Atlanta, Georgia.
Stefan NiemannForschungszentrum Borstel, Germany.
David AllandRutgers University, New Jersey.
Debra HannaCritical Path Institute, Tucson, Arizona.
Enrique AvilesCritical Path Institute, Tucson, Arizona.
Mark D PerkinsFIND, Geneva, Switzerland.
David L DolingerFIND, Geneva, Switzerland.

Funding

NIAID NIH HHS HHSN272200800014C
6 · The paper itself

Abstract

Tuberculosis remains a major global public health challenge. Although incidence is decreasing, the proportion of drug-resistant cases is increasing. Technical and operational complexities prevent Mycobacterium tuberculosis drug susceptibility phenotyping in the vast majority of new and retreatment cases. The advent of molecular technologies provides an opportunity to obtain results rapidly as compared to phenotypic culture. However, correlations between genetic mutations and resistance to multiple drugs have not been systematically evaluated. Molecular testing of M. tuberculosis sampled from a typical patient continues to provide a partial picture of drug resistance. A database of phenotypic and genotypic testing results, especially where prospectively collected, could document statistically significant associations and may reveal new, predictive molecular patterns. We examine the feasibility of integrating existing molecular and phenotypic drug susceptibility data to identify associations observed across multiple studies and demonstrate potential for well-integrated M. tuberculosis mutation data to reveal actionable findings.

Indexed as

Databases, GeneticDrug Resistance, BacterialMutationAntitubercular AgentsGenotypeHumansMycobacterium tuberculosisTuberculosisAntitubercular Agentsdatabasedrug resistancedrug susceptibility testinggenomic sequencingresistance-associated mutationstuberculosis

Identifiers

PMID25765106
PMCPMC4366577

What OpenQuestion holds

Textmetadata
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.