Evidence map›Paper›PMID 41536913›Full record

ArticleRheumatology advances in practice2026

Development of a clinical tool to identify patients with early inflammatory arthritis at high risk of employment loss: analysis from the National Early Inflammatory Arthritis Audit.

Ed Alveyn, Katie Bechman, Maryam Adas, Paul Amlani-Hatcher, Mini Dey, Sarah Gallagher, Mark Gibson, Bethan Jones, Daksh Mehta, Sam Norton and 5 more

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In one paragraph

Article in Rheumatology advances in practice, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper, 1 of them a synthesis that pooled it.

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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Ed AlveynDepartment of Inflammation Biology, Centre of Rheumatic Disease, King's College London, London, UK.
Katie BechmanDepartment of Inflammation Biology, Centre of Rheumatic Disease, King's College London, London, UK.
Maryam AdasDepartment of Inflammation Biology, Centre of Rheumatic Disease, King's College London, London, UK.ORCID https://orcid.org/0000-0002-5560-6603
Paul Amlani-HatcherNEIAA Patient Panel, British Society for Rheumatology, London, UK.
Mini DeyDepartment of Inflammation Biology, Centre of Rheumatic Disease, King's College London, London, UK.
Sarah GallagherNEIAA, British Society for Rheumatology, London, UK.
Mark GibsonDepartment of Inflammation Biology, Centre of Rheumatic Disease, King's College London, London, UK.
Bethan JonesFaculty of Health and Life Sciences, University of Liverpool, Liverpool, UK.
Daksh MehtaDepartment of Inflammation Biology, Centre of Rheumatic Disease, King's College London, London, UK.
Sam NortonDepartment of Inflammation Biology, Centre of Rheumatic Disease, King's College London, London, UK.ORCID https://orcid.org/0000-0003-1714-9963
Elizabeth PriceDepartment of Rheumatology, Great Western Hospital NHS Foundation Trust, Swindon, UK.ORCID https://orcid.org/0000-0003-3042-0201
Mark RussellDepartment of Inflammation Biology, Centre of Rheumatic Disease, King's College London, London, UK.ORCID https://orcid.org/0000-0001-8171-7772
Karen Walker-BoneMonash Centre for Occupational and Environmental Health, Monash University, Melbourne, Australia.ORCID https://orcid.org/0000-0002-5992-1459
Elizabeth MacPhieRheumatology, Minerva Health Centre, Preston, UK.
James GallowayDepartment of Inflammation Biology, Centre of Rheumatic Disease, King's College London, London, UK.ORCID https://orcid.org/0000-0002-1230-2781

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Work disability is an early consequence of inflammatory arthritis. Preventive interventions exist but access is limited, highlighting the need for risk stratification. We aimed to develop a tool using routinely collected data to identify patients at greatest risk of employment loss. Methods: This cohort study used data from the National Early Inflammatory Arthritis Audit. Patients ≥16 years with early inflammatory arthritis (EIA), enrolled May 2018-April 2025, employed at diagnosis and with three-month follow-up were included. The outcome was self-reported employment loss at 3 months. Predictors were occupation (manual vs non-manual), age, sex, disease activity (DAS28 > 5.1), mental health (anxiety/depression) and musculoskeletal burden (MSKHQ ≤25v > 25). Employment loss was modelled using Poisson regression. Model discrimination, calibration and bootstrap validation were assessed. A risk score was derived and stratified into low, medium and high-risk groups. Results: Of 11 894 patients with EIA, 6036 were employed at baseline and 1662 had complete work-outcome data. At 3 months, 168(10.1%) reported employment loss. Manual workers had higher risk than non-manual (14.1% vs 7.8%). In multivariable analysis, manual work (IRR: 1.54, 95% CI: 1.15-2.06), older age (per 10 years: IRR: 1.65, 95% CI: 1.43-1.90), high musculoskeletal burden (IRR: 1.55, 1.10-2.19) and anxiety/depression (IRR: 1.45, 1.02-2.06) were associated with employment loss, whereas DAS28 was not. The optimal model (age, occupation, musculoskeletal and mental health) showed good discrimination (C-statistic 0.710) and calibration. An 8-point score stratified patients into low (2.5%), medium (9.1%) and high-risk (19.5%). Conclusion: Employment loss in EIA is driven by occupation, age, musculoskeletal symptoms and mental health. A risk tool incorporating these domains can stratify patients and guide targeted interventions.

Indexed as

early inflammatory arthritisemployment lossmanual occupationrisk stratificationwork disability

Identifiers

PMID41536913
PMCPMC12798532

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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.