Evidence map›Paper›PMID 26132584›Full record

ArticlePloS one2015

The Potential Impact of Up-Front Drug Sensitivity Testing on India's Epidemic of Multi-Drug Resistant Tuberculosis.

Kuldeep Singh Sachdeva, Neeraj Raizada, Radhey Shyam Gupta, Sreenivas Achuthan Nair, Claudia Denkinger, Chinnambedu Nainarappan Paramasivan, Shubhangi Kulsange, Rahul Thakur, Puneet Dewan, Catharina Boehme and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
3.7field-weighted citation impact, top 7% 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

  1. Pooled it
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  4. Rifampicin resistance inNew microbes and new infections · 2021
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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

11 authors at 4 institutions in 3 countries.

Kuldeep Singh SachdevaCentral TB Division, Government of India, New Delhi, India.
Neeraj RaizadaFoundation for Innovative New Diagnostics, New Delhi, India.
Radhey Shyam GuptaCentral TB Division, Government of India, New Delhi, India.
Sreenivas Achuthan NairWorld Health Organization, India Country Office, New Delhi, India.
Claudia DenkingerFoundation for Innovative New Diagnostics, New Delhi, India.
Chinnambedu Nainarappan ParamasivanFoundation for Innovative New Diagnostics, New Delhi, India.
Shubhangi KulsangeFoundation for Innovative New Diagnostics, New Delhi, India.
Rahul ThakurFoundation for Innovative New Diagnostics, New Delhi, India.
Puneet DewanBill and Melinda Gates Foundation, New Delhi, India.
Catharina BoehmeFoundation for Innovative New Diagnostics, New Delhi, India.
Nimalan ArinaminpathyDepartment of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
Government of India · INGates Foundation · USImperial College London · GBWorld Health Organization - India · IN

Funding

Medical Research Council MR/K010174/1World Health Organization 001
6 · The paper itself

Abstract

backgroundIn India as elsewhere, multi-drug resistance (MDR) poses a serious challenge in the control of tuberculosis (TB). The End TB strategy, recently approved by the world health assembly, aims to reduce TB deaths by 95% and new cases by 90% between 2015 and 2035. A key pillar of this approach is early diagnosis of tuberculosis, including use of higher-sensitivity diagnostic testing and universal rapid drug susceptibility testing (DST). Despite limitations of current laboratory assays, universal access to rapid DST could become more feasible with the advent of new and emerging technologies. Here we use a mathematical model of TB transmission, calibrated to the TB epidemic in India, to explore the potential impact of a major national scale-up of rapid DST. To inform key parameters in a clinical setting, we take GeneXpert as an example of a technology that could enable such scale-up. We draw from a recent multi-centric demonstration study conducted in India that involved upfront Xpert MTB/RIF testing of all TB suspects.

resultsWe find that widespread, public-sector deployment of high-sensitivity diagnostic testing and universal DST appropriately linked with treatment could substantially impact MDR-TB in India. Achieving 75% access over 3 years amongst all cases being diagnosed for TB in the public sector alone could avert over 180,000 cases of MDR-TB (95% CI 44187 - 317077 cases) between 2015 and 2025. Sufficiently wide deployment of Xpert could, moreover, turn an increasing MDR epidemic into a diminishing one. Synergistic effects were observed with assumptions of simultaneously improving MDR-TB treatment outcomes. Our results illustrate the potential impact of new and emerging technologies that enable widespread, timely DST, and the important effect that universal rapid DST in the public sector can have on the MDR-TB epidemic in India.

Indexed as

Microbial Sensitivity TestsAntitubercular AgentsEpidemicsHumansIncidenceIndiaModels, TheoreticalPrevalenceTuberculosis, Multidrug-ResistantAntitubercular Agents

Identifiers

PMID26132584
PMCPMC4488842
OpenAlexW791943867

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.