Evidence map›Paper›PMID 30440033›Full record

ArticlePloS one2018

A scoring strategy for progression risk and rates of treatment completion in subjects with latent tuberculosis.

Michael Scolarici, Ken Dekitani, Ling Chen, Marcia Sokol-Anderson, Daniel F Hoft, Soumya Chatterjee

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.1field-weighted citation impact, top 48% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
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 at 2 institutions in 1 country.

Michael ScolariciSt Louis University School of Medicine, St Louis, MO, United States of America.
Ken DekitaniSt Louis University School of Medicine, St Louis, MO, United States of America.
Ling ChenDivision of Biostatistics, Washington University in St. Louis School of Medicine, St Louis, MO, United States of America.
Marcia Sokol-AndersonDivision of Infectious Diseases, Allergy and Immunology, Department of Internal Medicine, St Louis University, St Louis, MO, United States of America.
Daniel F HoftDivision of Infectious Diseases, Allergy and Immunology, Department of Internal Medicine, St Louis University, St Louis, MO, United States of America.
Soumya ChatterjeeDivision of Infectious Diseases, Allergy and Immunology, Department of Internal Medicine, St Louis University, St Louis, MO, United States of America.ORCID 0000-0003-3628-3738
Saint Louis University · USWashington University in St. Louis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is unknown whether patients with LTBI at high vs. low risk of developing active TB are currently adequately identified and treated in the US. In this study our objective was 1) To retrospectively apply the online calculator (tstin3d.com) to determine the probability of having LTBI and assign cumulative risk of progression. 2) Measure treatment outcomes in subjects with Low: 0-<10%, Intermediate: 10-<50% and High: 50-100% cumulative risk. We performed medical record review of tuberculin skin test and/or Interferon-γ release assay (IGRAs) positive patients with LTBI seen from 2010-2015. Of 125 subjects included, 51(41%), 46 (37%) and 28 (22%) subjects were in Low, Intermediate and High risk groups respectively. Tstin3d.com was useful in determining the probability of LTBI in tuberculin skin test positive US-born subjects. Overall treatment completion rate was 61% in 114 subjects with complete treatment information and similar completion rates were seen in the three groups (Low-60%, Intermediate-63% and High-57%). Provider assessment of important clinical risk factors was often incomplete. Logistic regression analysis showed no association of assessment of important risk factors with treatment completion. The major limitations of the calculator are the lack of an updated data on country-specific prevalence of TB disease as the global burden of TB continues to decrease as well as falsely high positive predictive values that due to "transiently" positive IGRA results in subjects from countries with low prevalence. Nonetheless, our findings suggest that tstin3d.com could be utilized in the US setting for improving providing awareness of risk stratification of patients with LTBI for short course treatment regimens based on risk.

Indexed as

AdultAgedAged, 80 and overDisease ProgressionFemaleHumansInterferon-gamma Release TestsLatent TuberculosisMaleMiddle AgedOutcome Assessment, Health CarePredictive Value of TestsRetrospective StudiesRisk FactorsTuberculin TestYoung Adult

Identifiers

PMID30440033
PMCPMC6237398
OpenAlexW2900956240

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.