Can simple or widely available factors be used to predict adverse outcomes in people with rheumatoid arthritis? Cross-sectional study of 5658 UK Biobank participants.

Problem

There is a need to identify prognostic factors, which are potentially readily available in a primary care setting, that can predict adverse health outcomes in people with rheumatoid arthritis (RA). We aimed to explore the associations, if any, between selected potential prognostic factors (including clinical, physiological and patient-reported measures) and risk of all-cause mortality and major adverse cardiovascular events (MACE; including myocardial infarction and stroke) in an RA population.

Approach

This cross-sectional study included UK Biobank participants that self-reported RA. Selected prognostic factors, identified in the literature as having predictive potential, that could be accessible in a primary care setting were categorised into the following domains: anthropometric measures (body mass index (BMI), body fat percentage, waist circumference, waist-to-hip ratio), functional measures (hand grip strength (HGS), usual walking pace (UWP)), inflammatory markers (C-reactive protein (CRP)), patient-reported measures (pain), physiological measures (blood pressure (BP), heart rate (HR)) and serological markers (rheumatoid factor (RF)). Associations between individual prognostic factors and outcomes of interest were explored using Cox proportional hazards models, adjusting for age, sex, socioeconomic status, additional long-term condition count and smoking status in the first instance to identify significant individual predictors. Models were further adjusted for any identified individual predictors to determine the most important prognostic factors.

Findings

In UK Biobank, 5658 (1.1%) participants self-reported RA (mean age 59; 69.8% female). 670 deaths and 370 MACE were recorded during the follow-up period (median 11 and 8 years, respectively). The following prognostic factors demonstrated significant associations with risk of all-cause mortality, independent of other significant predictors: underweight BMI (<18.5kg/m2) (hazard ratio (HR) 2.96 [95% confidence interval (CI) 1.59-5.51]), obese BMI (≥30.0kg/m2) (HR 0.52 [95% CI 0.36-0.76]), 3-10mg/L CRP (HR 1.41 [95% CI 1.14-1.75]), >10mg/L CRP (HR 1.77 [95% CI 1.39-2.26]), low HGS (<16kg female or <27kg male) (HR 1.28 [95% CI 1.05-1.56]) and slow UWP (HR 1.31 [95% CI 1.06-1.62]). Likewise, the following factors were found to be significantly associated with MACE, independent of other significant factors: >10mg/L CRP (HR 1.62 [95% CI 1.19-2.20]), low HGS (HR 1.61 [95% CI 1.26-2.07]) and slow UWP (HR 1.50 [95 % CI 1.15-1.97]).

Consequences

Our findings highlight the potential value of select prognostic factors for predicting adverse outcomes in RA populations. A simple, yet multidimensional approach to risk assessment, combining well-tolerated, easily repeatable measures such as those described here may provide important prognostic information at primary care level, while limiting excessive and overly invasive testing for RA patients. The use of such factors may enhance risk stratification and promote more personalised care for RA patients.