Objective To predict the development of arthritis in anticyclic citrullinated peptide antibodies and/or IgM rheumatoid factor positive (seropositive) arthralgia patients.

Methods A prediction rule was developed using a prospective cohort of 374 seropositive arthralgia patients, followed for the development of arthritis. The model was created with backward stepwise Cox regression with 18 variables.

Results 131 patients (35%) developed arthritis after a median of 12 months. The prediction model consisted of nine variables: Rheumatoid Arthritis in a first degree family member, alcohol non-use, duration of symptoms <12 months, presence of intermittent symptoms, arthralgia in upper and lower extremities, visual analogue scale pain ≥50, presence of morning stiffness ≥1 h, history of swollen joints as reported by the patient and antibody status. A simplified prediction rule was made ranging from 0 to 13 points. The area under the curve value (95% CI) of this prediction rule was 0.82 (0.75–0.89) after 5 years. Harrell's C (95% CI) was 0.78 (0.73–0.84). Patients could be categorised in three risk groups: low (0–4 points), intermediate (5–6 points) and high risk (7–13 points). With the low risk group as a reference, the intermediate risk group had a hazard ratio (HR; 95% CI) of 4.52 (2.42–8.77) and the high risk group had a HR of 14.86 (8.40–28.32).

Conclusions In patients presenting with seropositive arthralgia, the risk of developing arthritis can be predicted. The prediction rule that was made in this patient group can help (1) to inform patients and (2) to select high-risk patients for intervention studies before clinical arthritis occurs.