Canadian multidisciplinary expert consensus on the use of biologics in upper airways: a Delphi study
Bibliographic record
Abstract
Abstract Background Chronic rhinosinusitis with nasal polyposis (CRSwNP) often coexists with lower airway disease. With the overlap between upper and lower airway disease, optimal management of the upper airways is undertaken in conjunction with that of the lower airways. Biologic therapy with targeted activity within the Type 2 inflammatory pathway can improve the clinical signs and symptoms of both upper and lower airway diseases. Knowledge gaps nevertheless exist in how best to approach patient care as a whole. There have been sixteen randomized, double-blind, placebo-controlled trails performed for CRSwNP targeted components of the Type 2 inflammatory pathway, notably interleukin (IL)-4, IL-5 and IL-13, IL- 5R, IL-33, and immunoglobulin (Ig)E. This white paper considers the perspectives of experts in various disciplines such as rhinology, allergy, and respirology across Canada, all of whom have unique and valuable insights to contribute on how to best approach patients with upper airway disease from a multidisciplinary perspective. Methods A Delphi Method process was utilized involving three rounds of questionnaires in which the first two were completed individually online and the third was discussed on a virtual platform with all the panelists. A national multidisciplinary expert panel of 34 certified specialists was created, composed of 16 rhinologists, 7 allergists, and 11 respirologists who evaluated the 20 original statements on a scale of 1–9 and provided comments. All ratings were quantitively reviewed by mean, median, mode, range, standard deviation and inter-rater reliability. Consensus was defined by relative interrater reliability measures—kappa coefficient ( $$\kappa$$ κ ) value > 0.61. Results After three rounds, a total of 22 statements achieved consensus. This white paper only contains the final agreed upon statements and clear rationale and support for the statements regarding the use of biologics in patients with upper airway disease. Conclusion This white paper provides guidance to Canadian physicians on the use of biologic therapy for the management of upper airway disease from a multidisciplinary perspective, but the medical and surgical regimen should ultimately be individualized to the patient. As more biologics become available and additional trials are published we will provide updated versions of this white paper every few years. Graphical abstract
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".