Evidence map›Paper›PMID 26503434›Full record

ArticleBMC infectious diseases2015

The potential of a multiplex high-throughput molecular assay for early detection of first and second line tuberculosis drug resistance mutations to improve infection control and reduce costs: a decision analytical modeling study.

A H Van't Hoog, I Bergval, N Tukvadze, S Sengstake, R Aspindzelashvili, R M Anthony, F Cobelens

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 31% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Preventing the spread of multidrug-resistant tuberculosis and protecting contacts of infectious cases.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2017
    Pooled it
  2. Article
  3. Article
  4. Article
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

7 authors at 4 institutions in 2 countries.

A H Van't HoogDepartment of Global Health, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands. a.h.vanthoog@aighd.org.
I BergvalKIT Biomedical Research, Royal Tropical Institute, Amsterdam, The Netherlands. i.bergval@kit.nl.
N TukvadzeNational Tuberculosis Reference Laboratory, National Center for Tuberculosis and Lung Diseases, Tbilisi, Georgia. marikushane@yahoo.com.
S SengstakeKIT Biomedical Research, Royal Tropical Institute, Amsterdam, The Netherlands. s.sengstake@kit.nl.
R AspindzelashviliNational Tuberculosis Reference Laboratory, National Center for Tuberculosis and Lung Diseases, Tbilisi, Georgia. asporusiko@yahoo.com.
R M AnthonyKIT Biomedical Research, Royal Tropical Institute, Amsterdam, The Netherlands. r.anthony@kit.nl.
F CobelensDepartment of Global Health, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands. f.cobelens@aighd.org.
Royal Tropical Institute · NLNational Center for Tuberculosis and Lung Disease · GEAmsterdam Institute for Global Health and Development · NLUniversity of Amsterdam · NL

Funding

Emory-Georgia TB Research Training ProgramD43TW007124 · FIC · EMORY UNIVERSITY · PI HENRY M BLUMBERG, Nestani Tukvadze · 2004 to 2026
$4.6M
FIC NIH HHS D43 TW007124
6 · The paper itself

Abstract

backgroundMolecular resistance detection (MRD) of resistance to second-line anti-tuberculous drugs provides faster results than phenotypic tests, may shorten treatment and allow earlier separation among patients with and without second-line drug resistance.

methodsIn a decision-analytical model we simulated a cohort of patients diagnosed with TB in a setting where drug resistant TB is highly prevalent and requires initial hospitalization, to explore the potential benefits of a high-throughput MRD-assay for reducing potential nosocomial transmission of highly resistant strains, and total costs for diagnosis of drug resistance, treatment and hospitalization. In the base case scenario first-line drug resistance was diagnosed with WHO-endorsed molecular tests, and second-line drug resistance with culture and phenotypic methods. Three alternative scenarios were explored, each deploying high-throughput MRD allowing either detection of second-line mutations in cultured isolates, directly on sputum, or MRD with optimized markers.

resultsCompared to a base case scenario, deployment of high-throughput MRD reduced total costs by 17-21 %. The period during which nosocomial transmission may take place increased by 15 % compared to the base case if MRD had currently reported suboptimal sensitivity and required cultured isolates; increased by 7 % if direct sputum analysis were possible including in patients with smear-negative TB, and reduced by 24 % if the assay had improved markers, but was still performed on cultured isolates. Improved clinical sensitivity of the assay (additional markers) by more than 35 % would be needed to avoid compromising infection control.

conclusionsFurther development of rapid second-line resistance testing should prioritize investment in optimizing markers above investments in a platform for direct analysis of sputum.

Indexed as

MutationAntitubercular AgentsCosts and Cost AnalysisCross InfectionDrug Resistance, Multiple, BacterialEarly DiagnosisGeorgia (Republic)High-Throughput Screening AssaysHumansInfection ControlMiddle AgedMycobacterium tuberculosisSputumTuberculosisTuberculosis, Multidrug-ResistantAntitubercular Agents

Identifiers

PMID26503434
PMCPMC4624169
OpenAlexW2175758729

What OpenQuestion holds

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LicenceCC BY
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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.