Background Lifestyle factors can help us identify a cohort “at risk” of RA for further targeted genetic and serological screening for possible primary prevention.
Objectives To develop a prediction score for individual risk of developing inflammatory polyarthritis (IP) and rheumatoid arthritis (RA) using easily ascertained demographic and lifestyle factors available to primary care and general physicians.
Methods Lifestyle data were obtained from a prospective population-based study, the European Prospective Investigation of Cancer in Norfolk (EPIC-Norfolk) between 1994 and 1997. Individuals who subsequently developed IP were identified by linkage with the Norfolk Arthritis Register (NOAR), a primary-care based disease register with an overlapping catchment area. The primary outcome was development of IP. A Cox proportional hazards model was developed. A score was assigned to each risk factor based on the β-coefficients from the model (with negative scores for protective factors). The odds of developing IP based on the score were calculated by logistic regression.
Results 25,455 EPIC participants aged 40-79 years were followed for a median (IQR) of 14.2 (12.9, 15.3) years (342,916 person-years of follow-up). 184 developed incident IP (69.6% women). The 10-year cumulative incidence of IP was 0.37% in men and 0.67% in women. For men, every 10 pack-years of smoking, being obese and having diabetes mellitus scored positively, whereas drinking up to 3 units of alcohol per day, and being of a higher occupational class scored negatively (Table, Area under the ROC curve 0.59). For women, smoking status was a better predictor than pack-years smoked and additional positive scores were assigned for having 2 or more children, whereas negative scores were assigned for every 6 months of breastfeeding (Table, area under the ROC curve 0.66). 1159 (8.4%) women had scores that reflect at least a 2% 10-year risk of IP which is >3 times the risk of those with a score of 0.
Conclusions Our scoring system, based on simply ascertained clinical and lifestyle factors can identify individuals at higher risk for IP. This will help focus enhanced serological and genetic screening in the population and aid in implementing preventative strategies against IP.
Disclosure of Interest None Declared