Rationale and Design of BeatNF2 Trial: A Clinical Trial to Assess the Efficacy and Safety of Bevacizumab in Patients with Neurofibromatosis Type 2 Related Vestibular Schwannoma
Bibliographic record
Abstract
Neurofibromatosis type 2 (NF2) causes bilateral vestibular schwannomas (VSs), leading to deafness. VS is treated by surgery or radiation, but neither treatments prevent hearing loss. Bevacizumab was found to be effective in suppressing the tumor's growth and may help to improve hearing. We are conducting a randomized, double-blind, multicenter clinical trial to verify the efficacy and safety of bevacizumab in NF2-related VS. The primary objective is to evaluate the efficacy of bevacizumab in improving hearing in the affected ear. One of the secondary objectives is to evaluate bevacizumab's efficacy in rechallenge treatment in relapsed cases. Sixty patients will randomly receive either bevacizumab or a placebo and will be clinically observed for 48 weeks in the initial intervention phase. In the first half (24 weeks), they will receive either 5 mg/kg of bevacizumab or a placebo drug. In the second half, all patients will receive 5 mg/kg of bevacizumab. If hearing function deteriorated in a patient who had shown improvement during the first phase, a rechallenge dose with bevacizumab would be offered.
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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 | 0.021 | 0.016 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".