Real‐World Adverse Events After Type 2 Biologic use in Chronic Rhinosinusitis with Nasal Polyps
Bibliographic record
Abstract
OBJECTIVE: To investigate the frequency and nature of adverse events related to type 2 biologic use in patients with chronic rhinosinusitis with nasal polyps (CRSwNP), including dupilumab and mepolizumab. METHODS: This is a single-institution retrospective study of real-world patient data. Patients were included if they have a diagnosis of CRSwNP, have undergone at least one endoscopic sinus surgery, and have taken at least two doses of dupilumab or mepolizumab between January 1, 2016, and July 1, 2023. Data collected include clinicodemographic information and past medical/surgical history. The primary outcomes are the incidence and types of adverse events. Adjusted odds ratio was calculated to compare the biologics using logistic regression. Risk factors for developing adverse events were investigated. RESULTS: Eighty-seven patients on dupilumab and 51 patients on mepolizumab were included. Thirty-nine (45%) and 10 (20%) patients respectively encountered adverse events, which differed from phase 3 trial data. The adjusted odds ratio for adverse event rates between these two treatment groups was 3.8 (95% CI, 1.5-10.5). The most common adverse events for dupilumab were arthralgia (16%), rash (14%), and conjunctivitis or xerophthalmia (10%). The main adverse events for mepolizumab were headache (6%) and fatigue (6%). Seven dupilumab and three mepolizumab patients discontinued therapy due to adverse events. The average duration of treatment was 22.5 (range: 1-77) months for mepolizumab and 15.9 (range: 1-35) months for dupilumab. CONCLUSION: Dupilumab and mepolizumab have distinct adverse event profiles. This study contributes to informing clinicians' decisions regarding the use of type 2 biologics in CRSwNP patients. LEVEL OF EVIDENCE: 3 Laryngoscope, 134:3054-3059, 2024.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".