Evidence map›Paper›PMID 24719444›Full record

ArticleJournal of clinical microbiology2014

Simplified microarray system for simultaneously detecting rifampin, isoniazid, ethambutol, and streptomycin resistance markers in Mycobacterium tuberculosis.

Yvonne Linger, Alexander Kukhtin, Julia Golova, Alexander Perov, Amine Lambarqui, Lexi Bryant, George B Rudy, Kim Dionne, Stefanie L Fisher, Nicole Parrish and 1 more

Abstract readEvaluation Study
In one paragraph

Article in Journal of clinical microbiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Use of reverse dot blot hybridization DNA-array and targeted next-generation sequencing for the detection of drug resistance in patients with tuberculosis: a prospective diagnostic accuracy study.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026
    Article
  3. Article
  4. Article
  5. A Current Microbiological Picture ofPolish journal of microbiology · 2020
    Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Use of DNA microarray chips for the rapid detection ofExperimental and therapeutic medicine · 2017
    Article
  12. Article
  13. Review
  14. Article
  15. Review
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.

Yvonne LingerAkonni Biosystems, Inc., Frederick, Maryland, USA.
Alexander KukhtinAkonni Biosystems, Inc., Frederick, Maryland, USA.
Julia GolovaAkonni Biosystems, Inc., Frederick, Maryland, USA.
Alexander PerovAkonni Biosystems, Inc., Frederick, Maryland, USA.
Amine LambarquiAkonni Biosystems, Inc., Frederick, Maryland, USA.
Lexi BryantAkonni Biosystems, Inc., Frederick, Maryland, USA.
George B RudyAkonni Biosystems, Inc., Frederick, Maryland, USA.
Kim DionneThe Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Stefanie L FisherThe Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Nicole ParrishThe Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Darrell P ChandlerAkonni Biosystems, Inc., Frederick, Maryland, USA dchandler@akonni.com.

Funding

Diagnostic MDR- and XDR-TB PCR TruArrayRC3AI089106 · NIAID · AKONNI BIOSYSTEMS, INC. · PI CHANDLER, DARRELL P · 2010 to 2010
$3.0M
NIAID NIH HHS RC3 AI089106
6 · The paper itself

Abstract

We developed a simplified microarray test for detecting and identifying mutations in rpoB, katG, inhA, embB, and rpsL and compared the analytical performance of the test to that of phenotypic drug susceptibility testing (DST). The analytical sensitivity was estimated to be at least 110 genome copies per amplification reaction. The microarray test correctly detected 95.2% of mutations for which there was a sequence-specific probe on the microarray and 100% of 96 wild-type sequences. In a blinded analysis of 153 clinical isolates, microarray sensitivity for first-line drugs relative to phenotypic DST (true resistance) was 100% for rifampin (RIF) (14/14), 90.0% for isoniazid (INH) (36/40), 70% for ethambutol (EMB) (7/10), and 89.1% (57/64) combined. Microarray specificity (true susceptibility) for first-line agents was 95.0% for RIF (132/139), 98.2% for INH (111/113), and 98.6% for EMB (141/143). Overall microarray specificity for RIF, INH, and EMB combined was 97.2% (384/395). The overall positive and negative predictive values for RIF, INH, and EMB combined were 84.9% and 98.3%, respectively. For the second-line drug streptomycin (STR), overall concordance between the agar proportion method and microarray analysis was 89.5% (137/153). Sensitivity was 34.8% (8/23) because of limited microarray coverage for STR-conferring mutations, and specificity was 99.2% (129/130). All false-susceptible discrepant results were a consequence of DNA mutations that are not represented by a specific microarray probe. There were zero invalid results from 220 total tests. The simplified microarray system is suitable for detecting resistance-conferring mutations in clinical M. tuberculosis isolates and can now be used for prospective trials or integrated into an all-in-one, closed-amplicon consumable.

Indexed as

Drug Resistance, BacterialAntitubercular AgentsGenes, BacterialGenotyping TechniquesHumansMicroarray AnalysisMicrobial Sensitivity TestsMutationMycobacterium tuberculosisSensitivity and SpecificityTuberculosis, Multidrug-ResistantAntitubercular Agents

Identifiers

PMID24719444
PMCPMC4042730

What OpenQuestion holds

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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.