Risk of serious infections in arthritis patients treated with biological drugs: a matched cohort study and development of prediction model.

Abstract

Serious infection is a concern for patients with inflammatory joint diseases treated with biological drugs (bDMARDs). The objectives were to compare risk of serious infection, defined as infection leading to hospitalization, in patients initiating bDMARD treatment with that in the general population and, second, to develop a simple clinical prediction model and to obtain risk estimates for individual patients. This was a matched-cohort study based on nationwide registries in Denmark. Patients with RA, axial SpA and PsA initiating first bDMARD monitored in the DANBIO registry were matched 1:10 by age, gender and postal code with controls from the general population. The risk of serious infection during 12 months' follow-up was assessed with Cox regression. Prediction models were developed using logistic regression and compared using area under the receiver operating characteristic curve (AUC). We included 11372 patients and 113715 controls. During follow-up, 522 patients (4.6%) and 1434 controls (1.3%) developed a serious infection (hazard ratio 3.7, 95% CI 3.4, 4.1). Age-stratified risk was largely similar across diagnoses. A simple prediction model, the 'DANBIO infection risk score', based on age and a count of six clinical risk factors had moderate discriminative power (internal validation: AUC 0.69) that was comparable to that of the existing RABBIT (Rheumatoide Arthritis Beobachtung der BIologika-Therapie) Risk Score (external validation: AUC 0.68). Patients with inflammatory joint diseases initiating bDMARD treatment had a four times increased risk of serious infection compared with the general population. A simple prediction model, feasible for shared decision-making, was developed to obtain risk estimates for individual patients.