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Published on: January 21, 2018
Comparative Efficacy of Seven Biologics for Chronic Rhinosinusitis With Nasal Polyps: A Network Meta-Analysis
Shenglong Xu1,2, Shiru Cai1,2, Yan Zhao1,2
1Department of Otolaryngology Head and Neck Surgery, Beijing TongRen Hospital, Capital Medical University, Beijing, People's Republic of China.
Background:
Multiple randomized controlled trials (RCTs) of biologics for chronic rhinosinusitis with nasal polyps (CRSwNP) have expanded treatment options. This network meta-analysis (NMA) aimed to synthesize available evidence to compare the efficacy of these biologics.
Methods:
A systematic literature search was conducted. Primary outcomes were nasal polyp score (NPS) and nasal congestion score (NCS), while secondary outcomes included the 22-item Sino-Nasal Outcome Test score, loss of smell score, the University of Pennsylvania Smell Identification Test score, and the Lund-Mackay score. A Bayesian random-effects NMA model was applied. Rank probabilities and mean differences were calculated to compare the biologics at Week 24 and at the end of follow-up (> 48 weeks), and the probabilities that the top-ranked biologic exceeded others by the between-group minimal important difference (MID) were estimated.
Results:
A total of 13 trials involving seven biologics were included. Dupilumab, stapokibart, and tezepelumab demonstrated more favorable efficacy profiles across NPS, NCS, and secondary outcomes compared with omalizumab, mepolizumab, depemokimab, and benralizumab, forming a distinct top tier. The probabilities of exceeding MID thresholds between these three biologics were generally low, suggesting limited clinically meaningful differences among them. Subgroup analyses showed no significant differences in treatment effects between patients with and without comorbid asthma or prior nasal surgery.
Conclusions:
Dupilumab, stapokibart, and tezepelumab may be considered leading options for patients with CRSwNP. Nevertheless, additional head-to-head trials and real-world studies are warranted to further validate these findings and inform optimal biologic selection.
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