Systemic Bevacizumab for Treatment of Respiratory Papillomatosis: International Consensus Statement
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: The purpose of this study is to develop consensus on key points that would support the use of systemic bevacizumab for the treatment of recurrent respiratory papillomatosis (RRP), and to provide preliminary guidance surrounding the use of this treatment modality. STUDY DESIGN: Delphi method-based survey series. METHODS: A multidisciplinary, multi-institutional panel of physicians with experience using systemic bevacizumab for the treatment of RRP was established. The Delphi method was used to identify and obtain consensus on characteristics associated with systemic bevacizumab use across five domains: 1) patient characteristics; 2) disease characteristics; 3) treating center characteristics; 4) prior treatment characteristics; and 5) prior work-up. RESULTS: The international panel was composed of 70 experts from 12 countries, representing pediatric and adult otolaryngology, hematology/oncology, infectious diseases, pediatric surgery, family medicine, and epidemiology. A total of 189 items were identified, of which consensus was achieved on Patient Characteristics (9), Disease Characteristics (10), Treatment Center Characteristics (22), and Prior Workup Characteristics (18). CONCLUSION: This consensus statement provides a useful starting point for clinicians and centers hoping to offer systemic bevacizumab for RRP and may serve as a framework to assess the components of practices and centers currently using this therapy. We hope to provide a strategy to offer the treatment and also to provide a springboard for bevacizumab's use in combination with other RRP treatment protocols. Standardized delivery systems may facilitate research efforts and provide dosing regimens to help shape best-practice applications of systemic bevacizumab for patients with early-onset or less-severe disease phenotypes. LEVEL OF EVIDENCE: 5 Laryngoscope, 131:E1941-E1949, 2021.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 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".