Search

Objective: There is growing evidence that genetic data are of benefit in the rheumatology outpatient setting by aiding early diagnosis. A genetic probability tool (G‐PROB) has been developed to aid diagnosis has not yet been tested in a real‐world setting. Our aim was to assess whether G‐PROB could aid diagnosis in the rheumatology outpatient setting using data from the Norfolk Arthritis Register (NOAR), a prospective observational cohort of patients presenting with early inflammatory arthritis. Methods: Genotypes and clinician diagnoses were obtained from patients from NOAR. Six G‐probabilities (0%–100%) were created for each patient based on known disease‐associated odds ratios of published genetic risk variants, each corresponding to one disease of rheumatoid arthritis, systemic lupus erythematosus, psoriatic arthritis, spondyloarthropathy, gout, or "other diseases." Performance of the G‐probabilities compared with clinician diagnosis was assessed. Results: We tested G‐PROB on 1,047 patients. Calibration of G‐probabilities with clinician diagnosis was high, with regression coefficients of 1.047, where 1.00 is ideal. G‐probabilities discriminated clinician diagnosis with pooled areas under the curve (95% confidence interval) of 0.85 (0.84–0.86). G‐probabilities <5% corresponded to a negative predictive value of 96.0%, for which it was possible to suggest >2 unlikely diseases for 94% of patients and >3 for 53.7% of patients. G‐probabilities >50% corresponded to a positive predictive value of 70.4%. In 55.7% of patients, the disease with the highest G‐probability corresponded to clinician diagnosis. Conclusion: G‐PROB converts complex genetic information into meaningful and interpretable conditional probabilities, which may be especially helpful at eliminating unlikely diagnoses in the rheumatology outpatient setting. [ABSTRACT FROM AUTHOR]

Introduction: Cardiovascular disease (CVD) is the leading cause of death in patients with inflammatory polyarthritis (IP), especially in seropositive disease. In established rheumatoid arthritis (RA), insulin resistance (IR) is increased and associated with CVD. We investigated factors associated with IR in an inception cohort of patients with early IP., Methods: Patients with early IP (two or more swollen joints for four or more weeks), aged 18 to 65 years, seen within 24 months of symptom onset were recruited from the Norfolk Arthritis Register (NOAR), a primary-care-based inception cohort. Assessment included joint examination, current and prior therapy and completion of the Health Assessment Questionnaire. Fasting blood was taken for measurement of CVD risk factors, rheumatoid factor (RF), anti-citrullinated protein antibodies (ACPA), C-reactive protein (CRP), and insulin levels. IR was calculated using the homeostatic model assessment (HOMA-IR). We examined factors associated with IR using univariate and multivariable linear regression models., Results: A total of 196 patients, including 59 (30%) males, were studied with a median (interquartile range, IQR) age and IP symptom duration of 49 (40 to 57) years and 6.7 (4.6 to 10.7) months, respectively. After age and gender adjustment, HOMA-IR was associated with obesity, (β-Coefficient (95% CI); 1.60 (0.96, 2.24)), higher systolic and diastolic blood pressure (0.03 (0.01, 0.05) and 0.04 (0.01, 0.08) respectively), triglycerides (1.06 (0.54, 1.57)), and HDL (-1.38 (-2.17,-0.58)). HOMA-IR was associated with serological status and this association persisted after adjustment for classic CVD risk factors and other IP-related variables (RF β-Coefficient (95% CI); 0.87 (0.20, 1.53) and ACPA β-Coefficient (95% CI); 1.42 (0.70, 2.15))., Conclusions: Seropositivity for RF or ACPA was associated with IR in this early IP cohort. This association may, in part, explain why seropositive patients have excess CVD mortality.