Data was obtained from the Information System for the Development of Research in Primary Care (SIDIAP8). This contains the primary care clinical records of over five million people (more than 80% of the population aged ≥14 years) in Catalonia, Spain. GPs use ICD-10 codes to record clinical diagnoses. Each patient is assigned a unique identifier for confidentiality and data protection. The data is highly representative of the population of Catalonia,9 and has been used to study the epidemiology of musculoskeletal conditions such as osteoporotic fractures10 and osteoarthritis.11 In addition, SIDIAP contains complete information on blood test results performed in primary care. Pharmacy invoicing data is available for all subsidized medications dispensed in community pharmacies. Medicines data is classified using the World Health Organization Anatomical Therapeutic Chemical classification/Defined Daily Dose (ATC/DDD) index.

The study protocol was approved by the SIDIAP ethics review. We included all participants registered in the SIDIAP Database aged ≥18 years that were tested for RF between 01/01/2006 and 31/12/2011 and followed them up until the end of 2012. We considered that testing contributed to the diagnosis of RA only if the time between testing and subsequent diagnosis was less than 1 year.

We excluded participants with a diagnosis of RA at the start of the study period, and those diagnosed during the study period that had not been tested for RF during the previous year. We identified the results for all RF tests performed in primary care, and used the result nearest to a subsequent diagnosis of RA where patients were tested more than once. We used the laboratory upper limit of normal to define a positive RF result (≥10IU/mL). RF testing was performed using a latex-enhanced immunoturbidimetric assay.

We identified incident RA cases between 01/01/2006 and 31/12/2012, using ICD-10 codes M05 and M06 as registered in primary care records. We used a modified algorithm previously developed in the UK Clinical Practice Research Datalink (CPRD) database to confirm a diagnosis of RA in patients with Read codes for RA.12 This excluded patients with no prescription records for Disease Modifying Anti-Rheumatic Drugs (DMARDs) including azathioprine, ciclosporin, gold, hydroxychloroquine, leflunomide, methotrexate, mycophenolate, penicillamine, and sulfasalazine; or who had a subsequent alternative diagnosis (ankylosing spondylitis, dermato-polymyositis, fibromyalgia, gout, osteoarthritis, psoriatic arthritis, reactive arthritis, scleroderma, septic arthritis, systemic lupus erythematosus and other spondylo-arthropathies). This algorithm was subsequently validated for use in SIDIAP.13

We used a receiver operating characteristic (ROC) curve for RF against an incident diagnosis of RA made in the following year and estimated the area under the curve (95% confidence intervals) to explore the sensitivity and specificity. We identified the best “theoretical threshold” as the cut-off with the highest value of the total of sensitivity plus specificity.

We calculated the sensitivity, specificity, likelihood ratios, and positive/negative predictive values for both the pre-specified threshold and best theoretical threshold for RF. We estimated age and gender-adjusted odds ratios (OR) for a diagnosis of RA in the year following testing using the Mantel-Haeszel test.

Finally, we calculated the total cost of RF testing during the study period and the cost per true positive and negative case.

All statistical analyses were performed using Stataversion 12.0 SE for Mac.

The main strength is the comprehensive dataset, which includes all blood tests and results in primary care, and all primary care prescribing data. The study relies on the correct use of ICD-10 codes by GPs, which may be inaccurate. There was no access to clinical data to confirm ACR/EULAR classification criteria. However, we used a previously validated algorithm to select the most probable RA cases.12,13 We used a relatively low cut-off for defining a positive RF however the PPV remained low despite using the calculated best theoretical cut-off of 13.4IU/mL.

The sensitivity and specificity obtained for RF were in keeping with previous studies.16,17 We considered that a positive RF only contributed to the diagnosis of RA if it occurred within the year prior to diagnosis; this approach may exclude earlier RF tests that were relevant to diagnosis. However, calculating sensitivity and specificity based on a longer period between test and diagnosis (5 years) did not substantially change the results (data available on request). Only 955 patients were tested for anti-cyclic citrullinated peptide and so sensitivity and specificity was not calculated for this test due to the inherent selection bias of this group.

Primary care services in Spain have state-funded GPs acting as gate-keepers to secondary care.18 For the best use of limited resources, it is important to use tests appropriately. Less than 1% of patients tested had a subsequent diagnosis of RA suggesting that GPs may be using RF as a screening tool. This will increase the overall cost of testing.7 In this 6 year study period almost €4 million were spent and the cost of testing per true positive case was €1432. In comparison, the estimated cost of a GP consultation in the Catalan healthcare system is €40, a hand radiograph €9, and a first rheumatology appointment €101 to €143.19 Limiting RF testing to patients with a higher pre-test probability would significantly reduce the cost of testing.

Inappropriate testing also increases the laboratory workload and may lead to extra consultations to discuss results. Patient care is also impacted; if GPs use the results of RF testing to support referral decisions, there may be a delay for patients with clinical evidence of RA but who have a negative RF result, even though early diagnosis and treatment of RA leads to better outcomes20,21 and keeps patients in work.22

Potential solutions include criteria restricted primary care access to RF testing, issuing guidelines or reminder aids for when RF testing should be requested with local audit and feedback, and primary care educational interventions such as outreach by rheumatologists and peer facilitated workshops. The literature so far is unclear on which of these is the best approach; a review of research on the effectiveness of interventions to improve laboratory test ordering in primary care found low levels of evidence with poor quality of studies.23

In conclusion, RF testing is inefficient and costly when used in primary care patients with a low risk of inflammatory arthritis.