SAT0067 SEVERE INFECTIONS REMAIN COMMON IN A REAL-WORLD RHEUMATOID ARTHRITIS COHORT: A SIMPLE CLINICAL MODEL TO PREDICT INFECTION RISK
Authors: D. Wang, A. L. Yeo, C. Dendle, S. Morton, M. Leech
Journal: Annals of the Rheumatic Diseases (2020)

Background: Patients with rheumatoid arthritis (RA) have a higher risk of infection due to immunological dysfunction, immunosuppressive use, and coexisting comorbidities 1 . An understanding of these risk factors has helped develop infection risk calculators 2 . However, there are currently no screening tools available to rapidly identify patients with high infection risk. Objectives: To investigate the incidence of severe infection in a real-world RA cohort, identify associated risk factors, and propose a simple infection risk screening tool. Methods: Between January and July 2019, patients were recruited consecutively from an Australian tertiary hospital’s RA clinic. We included all adult patients with RA. The primary outcome was a severe infection (any infection requiring hospital admission) between January 2018 and July 2019. We collected data using hospital notes, medical records and pathology results. We used validated scores such as the disease activity score of 28 joints (DAS28) and the Charlson comorbidity index to assess disease activity and comorbidity burden. Multivariable regression was used for statistical analysis. Results: We recruited 263 eligible patients. 45 severe infections occurred in 34 patients (13%), corresponding to 10.8 infections per 100 patient years. Respiratory (53%) and urinary tract infections (13%) were the most common. On multivariable analysis, the most significant risk factors for severe infection included low lymphocyte counts (odds ratio (OR) 4.08), a previous infection within the last three years (OR 3.58), a Charlson comorbidity index of two or more (OR 2.69) and higher disease activity (OR 1.35 per 0.5-increase in DAS-28). The multivariable model incorporating these factors had a large area under receiver operating characteristic (ROC) curve of 0.82. Glucocorticoid and biologic use were not significantly associated with infection. Conclusion: To our knowledge, this was one of the first Australian studies to evaluate severe infection rates in a real-world RA cohort. Rates remained high and comparable with older studies 3 . Lymphopenia, high disease activity, comorbidity burden and a previous infection were independent risk factors for infection. Our multivariable model is a composite of easily assessible clinical and biological parameters, with excellent predictive potential for infection. Once validated, it may be developed into a screening tool to help clinicians rapidly identify high risk patients and inform tailored clinical decision making. References: [1] Listing J, Gerhold K, Zink A. The risk of infections associated with rheumatoid arthritis, with its comorbidity and treatment. Rheumatology. 2012;52(1):53-61. [2] Strangfeld A, Eveslage M, Schneider M, Bergerhausen HJ, Klopsch T, Zink A, et al. Treatment benefit or survival of the fittest: What drives the time-dependent decrease in serious infection rates under TNF inhibition and what does this imply for the individual patient? Ann Rheum Dis. 2011;70(11):1914-20. [3] Doran MF, Crowson CS, Pond GR, O’Fallon WM, Gabriel SE. Frequency of infection in patients with rheumatoid arthritis compared with controls: A population-based study. Arthritis Rheum. 2002;46(9):2287-93. Table 1. Cohort Demographics Characteristic Median (Interquartile Range) or Number (%) Age (years) 62 (50-70) Sex (female) 191 (73) Length of diagnosis (years) 9 (5-18) Biologic use over study period 106 (40) Steroid use over study period 77 (29) Charlson comorbidity index (excluding age) 0 (0-1) Table 2. multivariable logistic regression model for severe infection Variables Odds Ratio p value Age ≥50* 0.60 0.368 Charlson comorbidity index (≥2) 2.69 0.043 Previous severe infection in last 3 years 3.58 0.015 Disease activity score of 28 joints (per 0.5 increase) 1.35 0.005 Low lymphocyte counts (&lt;1) 4.08 0.028 *Age was included despite insignificance due to an a priori decision about its clinical relevance Figure 1. Receiver operating characteristic curve (ROC) of the multivariable model for infection Disclosure of Interests: None declared