Evidence map›Paper›PMID 31041318›Full record

ArticleERJ open research2019

Association of anti-tuberculosis drug concentrations in hair and treatment outcomes in MDR- and XDR-TB.

John Metcalfe, Peter Bacchetti, Roy Gerona, Ali Esmail, Keertan Dheda, Monica Gandhi

Abstract read
In one paragraph

Article in ERJ open research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Review
  6. Review
  7. Article
  8. Therapeutic drug monitoring of corticosteroids/βFrontiers in pharmacology · 2023
    Article
  9. Review
  10. 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

6 authors.

John MetcalfeDivision of Pulmonary and Critical Care Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, University of California, San Francisco, CA, USA.
Peter BacchettiDept of Epidemiology and Biostatistics, University of California, UCSF, San Francisco, CA, USA.
Roy GeronaMaternal-Fetal Medicine Division, Dept of Obstetrics, Gynecology and Reproductive Sciences, University of California, UCSF, San Francisco, CA, USA.
Ali EsmailLung Infection and Immunity Unit, Division of Pulmonology, University of Cape Town, Cape Town, South Africa.
Keertan DhedaLung Infection and Immunity Unit, Division of Pulmonology, University of Cape Town, Cape Town, South Africa.
Monica GandhiDivision of HIV, Infectious Diseases and Global Medicine, Dept of Medicine, University of California, UCSF, San Francisco, CA, USA.

Funding

Virology CoreP30AI027763 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MALLORY O JOHNSON · 1988 to 2026
$93.6M
Novel methods of pharmacologic monitoring for multidrug resistant tuberculosis treatment in the setting of HIV infectionR01AI123024 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GANDHI, MONICA, METCALFE, JOHN ZAPATA · 2016 to 2020
$3.6M
NIAID NIH HHS P30 AI027763NIAID NIH HHS R01 AI123024
6 · The paper itself

Abstract

Therapeutic drug monitoring for drug-resistant tuberculosis (TB) is likely to improve treatment outcomes. While assessments of plasma drug levels can explain pharmacokinetic variability among trial participants, these measures require phlebotomy and a cold chain, and are generally not repeated frequently enough to characterise drug exposure over time. Using a novel multi-analyte assay, we found evidence that higher anti-TB drug concentrations in hair, a non-biohazardous and noninvasively collected biomatrix, predict extensively-drug resistant-TB clinical outcomes in a high-burden setting.

Identifiers

PMID31041318
PMCPMC6484095

What OpenQuestion holds

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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.