Evidence map›Paper›PMID 39385313›Full record

ArticleBMC rheumatology2024

Survey self-report of rheumatoid arthritis and treatments versus specialist clinician confirmation.

Shamil Jugnundan, Gabriela Schmajuk, Laura Trupin, Paul D Blanc

Abstract read
In one paragraph

Article in BMC rheumatology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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.

Shamil JugnundanDivision of Occupational Environmental and Climate Medicine, University of California San Francisco, San Francisco, CA, 94143-0843, USA.
Gabriela SchmajukDepartment of Medicine, San Francisco Veterans Affairs Health Care System, San Francisco, CA, USA.
Laura TrupinDivision of Rheumatology, University of California San Francisco, San Francisco, CA, USA.
Paul D BlancDivision of Occupational Environmental and Climate Medicine, University of California San Francisco, San Francisco, CA, 94143-0843, USA. Paul.Blanc@ucsf.edu.

Funding

Alpha Foundation AFC618SP-88
6 · The paper itself

Abstract

objectiveTo assess agreement between patient survey report and physician recorded arthritic conditions and medication use in order to validate population-based epidemiologic approaches to auto-immune arthritic conditions.

methodsRheumatologists in the U.S. Appalachian region recruited men 50 years or older with a confirmed rheumatoid arthritis (RA) diagnosis. For each participating patient, the treating specialist completed a brief chart abstraction that included rheumatic diagnosis and corresponding treatment. Patients participated in a telephone interview using the same questionnaire as applied in a larger random digit dial survey that queried arthritis diagnosis and treatment. We assessed patient-clinician agreement with the Prevalence Adjusted and Biased Adjusted Kappa (PABAK) statistic.

resultsWe included 36 patient-clinician dyads in this analysis. All clinicians and patients concurred in the RA diagnosis (PABAK = 1). For concomitant systemic lupus and scleroderma, we observed generally concordant responses (PABAK 0.89 and 1, respectively). For medication use, for hydroxychloroquine or sulfasalazine was associated with the lowest PABAK (0.39), intermediate values for methotrexate and for the "other conventional synthetic DMARDs" category (0.67), and with the highest agreement PABAK value for the "biologic DMARD or JAK 2 inhibitor" category (0.89).

conclusionSurvey-based self-report of RA offers a useful approach in epidemiological investigation. This is particularly relevant to population-based approaches to autoimmune arthritis related to occupational and environmental factors.

Identifiers

PMID39385313
PMCPMC11462809

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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.