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Record W4405733503 · doi:10.1177/19160216241307551

Biologics in the Treatment of Chronic Rhinosinusitis with Nasal Polyposis in Canada: Current Trends and Practice Patterns

2024· article· en· W4405733503 on OpenAlexafffundabout
Alexie Ouellette, Andrew Thamboo, Leigh J. Sowerby, Christopher J. Chin

Bibliographic record

VenueJournal of Otolaryngology - Head and Neck Surgery · 2024
Typearticle
Languageen
FieldMedicine
TopicSinusitis and nasal conditions
Canadian institutionsWestern UniversityUniversity of British ColumbiaDalhousie UniversitySaint John Regional Hospital
FundersFaculty of Medicine, Dalhousie UniversityDalhousie University
KeywordsChronic rhinosinusitisMedicineDermatologyNasal polypsIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: As the understanding of the pathophysiology of chronic rhinosinusitis has increased over the last few years, it has been discovered that biologic therapy targeting type 2 inflammatory molecules can be beneficial for those with difficult-to-treat chronic rhinosinusitis with nasal polyposis. Given the recency of biologics, there is somewhat limited evidence on when to prescribe these medications and who should receive them. A recent consensus paper published by a group of Canadian rhinologists gave recommendations regarding prescribing biologics to patients with chronic rhinosinusitis with nasal polyposis (CRSwNP). This study aimed to outline current practices and prescribing patterns of biologics for chronic rhinosinusitis in Canada and contrast this to existing guidelines. MATERIALS/METHODS: An online survey was distributed to members of the Canadian Rhinology Group of the Canadian Society of Otolaryngology-Head and Neck Surgery. The survey contained 44 questions, with 17 questions covering various topics related to criteria for initializing biologic therapy, investigations ordered prior to initialization of a biologic, and follow-up schedules. The responses were subsequently compared to clinical guidelines. RESULTS: Twenty-one physicians responded to the survey. One response was discarded for this analysis as the respondent did not prescribe biologics. The biologic agent of choice for the majority of physicians (85%) was Dupilumab (Dupixent). The most used patient-reported outcome measure used was the SNOT-22 (80%), and most physicians (90%) confirm that their patients have undergone adequate sinus surgery with a computed tomography (CT) scan prior to considering biologic therapy. Investigations ordered prior to therapy and follow-up schedules varied. Only 10% of respondents consistently refer their patients to a multidisciplinary clinic prior to prescribing biologics despite recommendations in guidelines, but 70% involve an allergist and/or a respirologist in the care of these patients. CONCLUSIONS: Most respondents follow the recommendations made by the Canadian and international guidelines [European Position Paper on Rhinosinusitis and Nasal Polyps (EPOS), European Forum for Research and Education in Allergy and Airway Diseases (EUFOREA)]. The lack of multidisciplinary clinics across the country could be contributing to the low number of physicians using this resource for their patients despite recommendations. As our knowledge about biologics and CRSwNP improves, and with updated guidelines recently published, this survey should be expanded and repeated in the future to revaluate biologic prescribing practices in Canada.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.974
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.007
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.028
GPT teacher head0.300
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes3
Has abstractyes

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