Evidence map›Paper›PMID 39014427›Full record

ArticleArthritis research & therapy2024

A novel method to monitor rheumatoid arthritis prevalence using hospital and medication databases.

Louise Koller-Smith, Ahmed Mehdi, Lyn March, Leigh Tooth, Gita D Mishra, Ranjeny Thomas

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Arthritis research & therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

  1. Pooled it
  2. Article
  3. 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.

Louise Koller-SmithFrazer Institute, The University of Queensland, Translational Research Institute (TRI), Level 7, 37 Kent St, Woolloongabba, QLD, 4102, Australia.
Ahmed MehdiFrazer Institute, The University of Queensland, Translational Research Institute (TRI), Level 7, 37 Kent St, Woolloongabba, QLD, 4102, Australia.
Lyn MarchFlorance and Cope Professorial Department of Rheumatology, Royal North Shore Hospital and Kolling Institute and Sydney MSK Flagship, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia.
Leigh ToothSchool of Public Health, The University of Queensland, Brisbane, QLD, Australia.
Gita D MishraSchool of Public Health, The University of Queensland, Brisbane, QLD, Australia.
Ranjeny ThomasFrazer Institute, The University of Queensland, Translational Research Institute (TRI), Level 7, 37 Kent St, Woolloongabba, QLD, 4102, Australia. ranjeny.thomas@uq.edu.au.ORCID 0000-0002-0518-8386

Funding

National Health and Medical Research Council APP2008287National Health and Medical Research Council APP2009577
6 · The paper itself

Abstract

backgroundMost estimates of rheumatoid arthritis (RA) prevalence, including all official figures in Australia and many other countries, are based on self-report. Self-report has been shown to overestimate RA, but the 'gold standard' of reviewing individual medical records is costly, time-consuming and impractical for large-scale research and population monitoring. This study provides an algorithm to estimate RA cases using administrative data that can be adjusted for use in multiple contexts to provide the first approximate RA cohort in Australia that does not rely on self-report.

methodsSurvey data on self-reported RA and medications from 25 467 respondents of the Australian Longitudinal Study on Women's Health (ALSWH) were linked with data from the national medication reimbursement database, hospital and emergency department (ED) episodes, and Medicare Benefits codes. RA prevalence was calculated for self-reported RA, self-reported RA medications, dispensed RA medications, and hospital/ED RA presentations. Linked data were used to exclude individuals with confounding autoimmune conditions.

resultsOf 25 467 survey respondents, 1367 (5·4%) women self-reported disease. Of the 26 840 women with hospital or ED presentations, 292 (1·1%) received ICD-10 codes for RA. There were 1038 (2·8%) cases by the medication database definition, and 294 cases (1·5%) by the self-reported medication definition. After excluding individuals with other rheumatic conditions, prevalence was 3·9% for self-reported RA, 1·9% based on the medication database definition and 0·5% by self-reported medication definition. This confirms the overestimation of RA based on self-reporting.

conclusionsWe provide an algorithm for identifying individuals with RA, which could be used for population studies and monitoring RA in Australia and, with adjustments, internationally. Its balance of accuracy and practicality will be useful for health service planning using relatively easily accessible input data.

Indexed as

Antirheumatic AgentsArthritis, RheumatoidDatabases, FactualSelf ReportAdultAgedAlgorithmsAustraliaFemaleHumansLongitudinal StudiesMiddle AgedPrevalenceAntirheumatic AgentsCase-findingDatabasePrevalenceRheumatoid arthritisSelf-report

Identifiers

PMID39014427
PMCPMC11251372

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.