Evidence map›Paper›PMID 27989591›Full record

ArticleThe Lancet. Respiratory medicine2017

Expected effects of adopting a 9 month regimen for multidrug-resistant tuberculosis: a population modelling analysis.

Emily A Kendall, Anthony T Fojo, David W Dowdy

Erratum issuedOpen access · hybridAbstract read
In one paragraph

Article in The Lancet. Respiratory medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
4.5field-weighted citation impact, top 5% 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

12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 32 citations in OpenAlex.

  1. Pooled it
  2. Effectiveness of interventions for reducing TB incidence in countries with low TB incidence: a systematic review of reviews.European respiratory review : an official journal of the European Respiratory Society · 2019
    Pooled it
  3. Article
  4. Globally diverseThe Lancet. Microbe · 2021
    Article
  5. Article
  6. Review
  7. Eligibility for a Shorter Treatment Regimen for Multidrug-resistant Tuberculosis in the United States, 2011-2016.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2020
    Article
  8. Article
  9. Article
  10. Drug-resistant tuberculosis in 2017: at a crossroads.The Lancet. Respiratory medicine · 2017
    Article
  11. Article
  12. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Emily A KendallDivision of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, MD, USA. Electronic address: ekendal2@jhmi.edu.
Anthony T FojoDivision of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
David W DowdyDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Johns Hopkins University · USJohns Hopkins Medicine · US

Funding

RESEARCH TRAINING IN MICROBIAL DISEASEST32AI007291 · NIAID · JOHNS HOPKINS UNIVERSITY · PI JOEL N BLANKSON, Sara Elizabeth Cosgrove · 1986 to 2026
$9.1M
NIAID NIH HHS T32 AI007291
6 · The paper itself

Abstract

backgroundIn May, 2016, WHO endorsed a 9 month regimen for multidrug-resistant tuberculosis that is cheaper and potentially more effective than the conventional, longer (20-24 month) therapy. We aimed to investigate the population-level implications of scaling up this new regimen.

methodsIn this population modelling analysis, we developed a dynamic transmission model to simulate the introduction of this short-course regimen as an instantaneous switch in 2016. We projected the corresponding percentage reduction in the incidence of multidrug-resistant tuberculosis by 2024 compared with continued use of longer therapy. In the primary analysis in a representative southeast Asian setting, we assumed that the short-course regimen would double treatment access (through savings in resources or capacity) and achieve long-term efficacy at levels seen in preliminary cohort studies. We then did extensive sensitivity analyses to explore a range of alternative scenarios.

findingsUnder the optimistic assumptions in the primary analysis, the incidence of multidrug-resistant tuberculosis in 2024 would be 3·3 (95% uncertainty range 2·2-5·6) per 100 000 population with the short-course regimen and 4·3 (2·9-7·6) per 100 000 population with continued use of longer therapy-ie, the short-course regimen could reduce incidence by 23% (10-38). Incidence would be reduced by 14% (4-28) if the new regimen affected only treatment effectiveness and by 11% (3-24) if it affected only treatment availability. Under more pessimistic assumptions, the short-course regimen would have minimal effect and even potential for harm-eg, when 30% of patients are ineligible for the new regimen because of second-line drug resistance, we projected a change in incidence of -2% (-20 to +28). The new regimen's effect was greater in settings with more ongoing transmission of multidrug-resistant tuberculosis, but results were otherwise similar across settings with different levels of tuberculosis incidence and prevalence of multidrug resistance.

interpretationThe short-course regimen has potential to substantially lessen the multidrug-resistant tuberculosis epidemic, but this effect depends on its long-term efficacy, its ability to expand treatment access, and the role of second-line drug resistance.

fundingUS National Institutes of Health and Bill & Melinda Gates Foundation.

Indexed as

Models, TheoreticalAntitubercular AgentsAsia, SoutheasternClinical ProtocolsDrug Administration ScheduleForecastingHumansIncidenceTime FactorsTreatment OutcomeTuberculosis, Multidrug-ResistantAntitubercular Agents

Identifiers

PMID27989591
PMCPMC5332590
OpenAlexW2567528646

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.