Evidence map›Paper›PMID 28558651›Full record

ArticleBMC infectious diseases2017

A user-friendly mathematical modelling web interface to assist local decision making in the fight against drug-resistant tuberculosis.

Romain Ragonnet, James M Trauer, Justin T Denholm, Ben J Marais, Emma S McBryde

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC infectious diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Romain RagonnetFaculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia. romain.ragonnet@burnet.edu.au.ORCID 0000-0001-8520-2362
James M TrauerFaculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia.
Justin T DenholmVictorian Tuberculosis Program, Melbourne Health, Melbourne, Australia.
Ben J MaraisMarie Bashir Institute and the Centre for Research Excellence in Tuberculosis, University of Sydney, Sydney, Australia.
Emma S McBrydeFaculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multidrug-resistant and rifampicin-resistant tuberculosis (MDR/RR-TB) represent an important challenge for global tuberculosis (TB) control. The high rates of MDR/RR-TB observed among re-treatment cases can arise from diverse pathways: de novo amplification during initial treatment, inappropriate treatment of undiagnosed MDR/RR-TB, relapse despite appropriate treatment, or reinfection with MDR/RR-TB. Mathematical modelling allows quantification of the contribution made by these pathways in different settings. This information provides valuable insights for TB policy-makers, allowing better contextualised solutions. However, mathematical modelling outputs need to consider local data and be easily accessible to decision makers in order to improve their usefulness. We present a user-friendly web-based modelling interface, which can be used by people without technical knowledge. Users can input their own parameter values and produce estimates for their specific setting. This innovative tool provides easy access to mathematical modelling outputs that are highly relevant to national TB control programs. In future, the same approach could be applied to a variety of modelling applications, enhancing local decision making.

Indexed as

Models, TheoreticalAntitubercular AgentsDecision MakingDrug Resistance, BacterialHumansPrecision MedicineRetreatmentRifampinTuberculosisTuberculosis, Multidrug-ResistantUser-Computer InterfaceAntitubercular AgentsRifampinCausal pathwayDecision makingMisdiagnosisMultidrug-resistant tuberculosisRe-treatmentTuberculosisUser Interface

Identifiers

PMID28558651
PMCPMC5450394

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.