The Non‐Inferiority Margins in Migraine Research ( <scp>NIMM</scp> ) Survey
Bibliographic record
Abstract
OBJECTIVES: To survey experts in Headache Medicine on their opinions regarding appropriate non-inferiority margins for outcomes commonly used in migraine research. METHODS: Members of the American Headache Society and the Canadian Headache Society were invited to participate in the Non-Inferiority Margins in Migraine Research (NIMM) survey. Adult and child neurologists with expertise in Headache Medicine were eligible to participate. The survey had a multiple choice format and comprised questions on respondent characteristics, eligibility, as well as expert opinion on non-inferiority margins for outcomes commonly used in trials of both prophylactic and acute interventions for migraine. RESULTS: Ninety-nine eligible respondents completed the survey. Most respondents were adult neurologists (84.9%) and 74% reported practicing in the USA. The following were the most commonly selected non-inferiority margins: (1) change in monthly migraine attacks comparing baseline to the treatment period: 1 attack (39.4% selecting), (2) change in monthly migraine days comparing baseline to the treatment period: 1 day (44.4%), (3) change in average migraine intensity on a 4-point scale comparing baseline to the treatment period: 1.0 (31.3%), (4) percentage of participants who are pain-free 2 hours after the intervention: 5% (41.4%), (5) percentage of participants who have a migraine recurrence within 48 hours of treatment: 5% (42.4%), and (6) percentage of participants with sustained pain freedom: 5% (42.4%). CONCLUSIONS: The results of the NIMM survey describe the opinions of a group of experts on appropriate non-inferiority margins for outcomes commonly used in migraine clinical trials. There was significant variability in responses and lack of consensus on the choice of non-inferiority margins. The survey did not incorporate the patient perspective and was not validated prior to distribution. Further work in this area is required in order to explore how to incorporate clinical considerations into the selection of non-inferiority margins for migraine research.
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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 | 0.042 | 0.077 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".