Background Rheumatoid Arthritis (RA) is a chronic rheumatological condition which causes inflammation of both the joint lining and extra-articular sites. It affects around 1% of the UK population and, if not properly treated, can lead joint damage, disability, and significant socioeconomic burden. The risk of long-term damage is reduced if treatment is started in an early disease stage with treatment in the first 3 months being associated with significantly improved clinical outcomes. However, treatment is often delayed due to long referral waits and challenges in identifying early RA in primary care. We plan to use large primary care datasets to develop and validate an RA risk prediction model for use in primary care, with the aim to provide an additional mechanism for early diagnosis and referral for treatment. Methods We identified candidate predictors from literature review, expert clinical opinion, and patient research partner input. Using coded primary care data held in Clinical Practice Research Datalink (CPRD) Aurum, we will use a time to event Cox proportional hazards model to develop a 1-year risk prediction model for RA. This will be validated first in CPRD GOLD and then independently in the Secure Anonymised Information Linkage dataset. We will also conduct a sensitivity analysis for the same model at 2 to 5 year risk, with a secondary outcome of RA and initiation of a disease modifying drug, and with the addition of laboratory test results as candidate predictors. Discussion The resulting risk prediction model may provide an additional mechanism to distinguish early RA in primary care and reduce treatment delays through earlier referral.
Competing Interest StatementJSC and KN are co-directors of DExtER operating division which is part of the University of Birmingham. DExtER operating division supports the extraction and preparing of healthcare data to support epidemiological analyses such as those seen in this article.
Funding StatementBH is funded by an MB-PhD studentship supported by The Kennedy Trust for Rheumatology Research [grant no. KENN 2021 04]. NIHR Research for Patient Benefit funds the Development and validation of Rheumatoid Arthritis PredIction moDel using primary care health records (RAPID), grant NIHR203621. AD is funded by a PhD studentship from the Applied Research Collaboration Northwest, in turn funded by the National Institute for Health Research (NIHR). KR, KN and NJA are supported by the NIHR Birmingham Biomedical Research Centre (BRC). This is independent research carried out at the NIHR BRC. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. CM is part funded by the NIHR ARC West Midlands and the NIHR School for Primary Care Research
Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.
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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:
CPRD obtains annual research ethics approval from the UKs Health Research Authority Research Ethics Committee (East Midlands, Derby; reference no.05/MRE04/87) to receive and supply patient data for research. Therefore, no additional ethics approval is required for studies using CPRD data for research, subject to individual research protocols meeting CPRD data governance requirements. The use of CPRD data for the study was approved by the CPRD Independent Scientific Advisory Committee (reference no. 22_002239). Individual patient data is available from CPRD with valid license.
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I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).
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I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.
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Data AvailabilityData access will be subject to ethics approval from CPRD.
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