Safety Profile of Biologics Used in Rheumatology: An Italian Prospective Pharmacovigilance Study.
Maria Antonietta BarbieriGiuseppe CicalaPaola Maria CutroneoElisabetta GerratanaCaterina PalleriaCaterina De SarroAda VeroLuigi IannoneAntonia MantiEmilio RussoGiovambattista De SarroFabiola AtzeniEdoardo SpinaPublished in: Journal of clinical medicine (2020)
Post-marketing surveillance activities are essential to detect the risk/benefit profile of biologic disease-modifying antirheumatic drugs (bDMARDs) in inflammatory arthritis. The aim of this study was to evaluate adverse events (AEs) in patients treated with bDMARDs in rheumatology during a prospective pharmacovigilance study from 2016 to 2018. Descriptive statistical analyses were performed to evaluate bDMARDs-related variables of patients without AEs/failures vs patients with AEs and failures. The risk profile among biologics was assessed by comparing patients treated with each bDMARD to patients treated with etanercept. A total of 1155 patients were enrolled, mostly affected by rheumatoid arthritis (46.0%). AEs and failures were experienced by 8.7% and 23.3%, respectively. The number of comorbidities significantly influenced the onset of AEs, while anxiety-depressive, gastrointestinal disease, and fibromyalgia influenced onset of failures. The probability of developing an AE was significantly lower in patients treated with secukinumab, while the probability of developing treatment failure was significantly lower in patients treated with golimumab, secukinumab and tocilizumab. A total of 216 AEs were reported (25.5% serious), mostly regarding infections (21.8%), musculoskeletal (17.6%) and skin (16.2%) disorders. Serious AEs included neutropenia (12.7%), lymphocytosis (9.1%) and uveitis (7.3%). The obtained results revealed known AEs but real-world data should be endorsed for undetected safety concerns.
Keyphrases
- rheumatoid arthritis
- ankylosing spondylitis
- juvenile idiopathic arthritis
- end stage renal disease
- newly diagnosed
- ejection fraction
- disease activity
- prognostic factors
- public health
- chronic kidney disease
- rheumatoid arthritis patients
- systemic lupus erythematosus
- machine learning
- emergency department
- single cell
- depressive symptoms
- cross sectional
- bipolar disorder
- idiopathic pulmonary fibrosis
- artificial intelligence
- deep learning
- stress induced