Evidence map›Paper›PMID 28091336›Full record

ArticleEpidemiology and infection2017

Who are the patients that default tuberculosis treatment? - space matters!

C Nunes, R Duarte, A M Veiga, B Taylor

Abstract read
In one paragraph

Article in Epidemiology and infection, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 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, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Article
  6. Tuberculosis in Prisons: Importance of Considering the Clustering in the Analysis of Cross-Sectional Studies.International journal of environmental research and public health · 2023
    Article
  7. Article
  8. [Factors associated with unsuccessful treatment of patients with drug-sensitive tuberculosis in Paraguay].Revista panamericana de salud publica = Pan American journal of public health · 2020
    Article
  9. Observational
  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

4 authors.

C NunesEscola Nacional de Saúde Pública,Universidade NOVA de Lisboa,Portugal.
R DuarteCentro Diagnóstico Pneumológico de Vila Nova de Gaia,Faculdade de Medicina da Universidade do Porto,Portugal.
A M VeigaEscola Nacional de Saúde Pública,Universidade NOVA de Lisboa,Portugal.
B TaylorLancaster University,Faculty of Health and Medicine,Lancaster,UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The goals of this article are: (i) to understand how individual characteristics affect the likelihood of patients defaulting their pulmonary tuberculosis (PTB) treatment regimens; (ii) to quantify the predictive capacity of these risk factors; and (iii) to quantify and map spatial variation in the risk of defaulting. We used logistic regression models and generalized additive models with a spatial component to determine the odds of default across continental Portugal. We focused on new PTB cases, diagnosed between 2000 and 2013, and included some individual information (sex, age, residence area, alcohol abuse, intravenous drug use, homelessness, HIV, imprisonment status). We found that the global default rate was 4·88%, higher in individuals with well-known risk profiles (males, immigrants, HIV positive, homeless, prisoners, alcohol and drug users). Of specific epidemiological interest was that our geographical analysis found that Portugal's main urban areas (the two biggest cities) and one tourist region have higher default rates compared to the rest of the country, after adjusting for the previously mentioneded risk factors. The challenge of treatment defaulting, either due to other individual non-measured characteristics, healthcare system failure or patient recalcitrance requires further analysis in the spatio-temporal domain. Our findings suggest the presence of significant within-country variation in the risk of defaulting that cannot be explained by these classical individual risk factors alone. The methods we advocate are simple to implement and could easily be applied to other diseases.

Indexed as

Medication AdherenceAdolescentAdultAgedAged, 80 and overAntitubercular AgentsChildChild, PreschoolFemaleHumansInfantInfant, NewbornMaleMiddle AgedPortugalRisk AssessmentAntitubercular AgentsNoncompliancepulmonary tuberculosisrisk factorsspatial patterntreatment

Identifiers

PMID28091336
PMCPMC9507839

What OpenQuestion holds

Textmetadata
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.