OA03 Developing a multivariable prediction model to identify anti-CCP positive individuals among those with non-specific musculoskeletal symptoms in primary care
Authors: Siddle Heidi J , Wilson Michelle , Nam Jacqueline L , Garcia-Montoya Leticia , Duquenne Laurence , Mankia Kulveer , Emery Paul , Hensor Elizabeth M A 
Published: April 2024

Background/Aims

A phase of immunologically imminent rheumatoid arthritis (RA) precedes the onset of clinical RA, characterised by increased circulating anti-cyclic citrullinated peptide (anti-CCP) antibodies. Early identification in the pre-clinical phase of RA in primary care (PC), through targeted anti-CCP testing, could prompt secondary care referral for earlier diagnosis, achieving better long-term outcomes. This study aimed to develop a model identifying those likely to be anti-CCP positive amongst people presenting to PC with non-specific musculoskeletal symptoms.

Methods

Participants were recruited across the UK between 2014 and 2020 to the Leeds ‘Co-ordinated Programme to Prevent Arthritis’, a prospective, observational cohort study. Participants were aged ≥18 years who presented to PC with non-specific musculoskeletal symptoms and no history of clinical synovitis. Fifteen baseline predictors were considered: age; gender; smoking status; first degree relative (FDR) with RA; and patient reported pain in: neck; back; shoulders; elbows; hips; wrists; thumbs; hand and/or fingers; knees; ankles; foot and/or toes. Participants were followed up at 12 months to determine if they had developed RA. Analysis was performed in R. Variable selection was carried out via LASSO logistic regression. Model performance was assessed using area under the receiver operating characteristic curve (ROC AUC); decision curve analysis was utilised to assess clinical utility. Internal validation was carried out via 200 bootstrap re-samples with replacement to estimate corrected model fit estimates.

Results

Analysis included 6,879 participants; 203 (2.95%) anti-CCP positive. Thirteen predictors were retained (age and ankles omitted); scores for each predictor were: sex (male) [+3], FDR with RA [+3], smoking (ever) [+2], pain in back [-3], neck [-2], knee [-1], wrist [+4], foot/toes [+3], hand/fingers [+3], shoulder [+3], thumb [+1]. With a score of ≥ 11 (≥4% risk) for anti-CCP testing, the ROC AUC was 0.65 (95% CI [0.61-0.69], corrected AUC=0.49). Choosing a threshold of 4% suggested that the benefit of testing one anti-CCP positive patient is 24 times larger than the harm of testing one anti-CCP negative patient. Sensitivity and specificity were 38.42 and 81.88 and positive- and negative-predicted values were 6.06 and 97.76. The net benefit was 0.0040 (corrected=0.0026). This threshold resulted in 19% being tested, corresponding to 39% of all anti-CCP positive participants. 12 month follow-up data were available for 2,480 participants. Out of those who would be tested using our model, 6.68% developed RA, compared with 1.94% if everyone was tested. Out of those tested who were anti-CCP positive, 56.85% developed RA (amongst those tested who were anti-CCP negative, 1.23% developed RA).

Conclusion

Targeted use of anti-CCP testing in PC may prompt earlier identification of people at risk of RA. Interviews with PC clinicians are currently being undertaken to understand the key behaviours required to support clinicians using this prediction model, alongside heath economic modelling to explore potential cost-effectiveness.

Disclosure

H.J. Siddle: Grants/research support; HJS has received funding from HEE/NIHR for this research [ICA-SCL-2018-04-ST2-004]. M. Wilson: None. J.L. Nam: None. L. Garcia-Montoya: None. L. Duquenne: None. K. Mankia: Consultancies; Serac Lifesciences. Honoraria; Galapagos, Lilly, Abbvie. Grants/research support; Eli Lilly, Gilead. Other; Attending meetings/travel: Abbvie. P. Emery: Consultancies; Lilly, Galapagos. Honoraria; Novartis, Lilly, Abbvie, Gilead, Galapagos. Grants/research support; Lilly, Samsung. Other; Advisory Board: Lilly, Astra Zeneca, BMS. E.M.A. Hensor: Grants/research support; Institution level grant for the NIHR Leeds Biomedical Research Centre.