Disease activity and its predictors in early inflammatory arthritis: findings from a national cohort

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Objectives

We set out to characterise patient factors that predict disease activity during the first year of treatment for early inflammatory arthritis (EIA).

Methods

We used an observational cohort study design, extracting data from a national clinical audit. All NHS organisations providing secondary rheumatology care in England and Wales were eligible to take part, with recruitment from 215/218 (99%) clinical commissioning groups (CCGs)/Health Boards. Participants were greater than 16 years old and newly diagnosed with rheumatoid arthritis pattern EIA between May 2018 and May 2019. Demographic details collected at baseline included age, gender, ethnicity, work status, and postcode, which was converted to an area level measure of socioeconomic position (SEP). Disease activity scores (DAS28) were collected at baseline, three and 12 months follow up.

Results

A total of 7,455 participants were included in analyses. Significant levels of CCG/Health board variation could not be robustly identified from mixed effects modelling. Gender and SEP were predictors of low disease activity at baseline, three and 12 months follow up. Mapping of margins identified a gradient for SEP, whereby those with higher degrees of deprivation had higher disease activity. Black, Asian and Minority Ethnic patients had a lower odds of remission at three months follow up.

Conclusion

Patient factors (gender, SEP, ethnicity) predict disease activity. The rheumatology community should galvanise to improve access to services for all members of society. More data are required to characterise area level variation in disease activity.



View the full article @ Rheumatology (Oxford, England)


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