Prescription Pattern and Safety of Biologics in Autoimmune Rheumatologic Diseases in Tertiary Care Hospital of Bihar.
Shakur Adil Ali AA, Kumar Raj R, Ranjan Raushan Kumar RK, Hameed Saajid S et al.
Biologics have revolutionized the treatment of autoimmune rheumatologic diseases, but data on their real-world use and safety in resource-limited settings like Bihar, India, are scarce. This study aimed to evaluate the prescription patterns and safety profile of biologic disease-modifying antirheumatic drugs (b-DMARDs) in patients with rheumatoid arthritis (RA) at a tertiary care hospital in Bihar. A prospective, observational cohort study conducted over 12 months. A total of 120 adult patients with RA prescribed b-DMARDs were enrolled. Data on demographic, clinical characteristics, and treatment details were collected. Disease activity (DAS-28-CRP) and functional status (HAQ-DI) were assessed at baseline and 6 months. Adverse events, particularly infections, were recorded and analysed using multivariable logistic regression to identify risk factors. Biologicals were prescribed in 14.93% patients with RA. Adalimumab (49.17%) was the most prescribed b-DMARD, followed by etanercept (28.33%). Methotrexate was the most common concomitant conventional DMARD (85.83%). All b-DMARDs significantly improved DAS-28-CRP and HAQ-DI scores (P < .0001), with adalimumab showing the greatest improvement. Infliximab had the highest infection rate (53.33%), whereas etanercept had the lowest (14.70%). Regression analysis identified infliximab use (adjusted odds ratio [aOR]: 3.27), concomitant corticosteroid use (aOR: 2.74), and the presence of comorbidities (aOR: 2.13) as significant independent risk factors for infection. Biologic disease-modifying antirheumatic drugs are effective in RA, but infection risks vary. Adalimumab and etanercept demonstrated favourable efficacy and safety profiles, respectively. Treatment decisions should be personalized, considering drug-specific risks, corticosteroid co-therapy, and patient comorbidities, especially in resource-constrained settings.