P.021 Evaluation of PREEMPT fixed-dose, fixed-site and follow the pain treatment paradigms in the PREDICT Study
Bibliographic record
Abstract
Background: Phase 3 PREEMPT established safety and efficacy of 155-195U onabotulinumtoxinA in adults with chronic migraine (CM). This analysis of the PREDICT study (NCT02502123) evaluates real-world effectiveness and safety of 155U, 156-195U and 195U-onabotulinumtoxinA in CM. Methods: Patients received onabotulinumtoxinA approximately every 12-weeks (≤7 treatment cycles [Tx]) per Canadian product monograph). Primary endpoint was mean change from baseline in Migraine-Specific Quality of Life (MSQ) at Tx4. Headache days, physician and patient satisfaction were evaluated. Analysis stratified safety population (≥1 onabotulinumtoxin A dose) into 3 groups (155U,156-195U,195U) by dose received on ≥3 of the first 4 Tx. Results: 184 patients received ≥1 onabotulinumtoxin A dose (155U, n=68; 156-195U, n=156; 195U, n=13 on ≥3 Tx). Headache days decreased over time compared to baseline (Tx4: -7.1[6.7] 155U; -6.5[6.7] 156-195U; -11.2[6.4] 195U). Physicians rated most patients as improved, and majority of patients were satisfied at final visit (80.8% 155U; 83.6% 156-195U; 90% 195U). Treatment-emergent adverse events (TEAEs) were reported in 18/68(26.5%) patients in 155U-group, 41/65(63.1%) in 156-195U-group and 10/13(76.9%) in 195U-group; treatment-related TEAEs were 9(13.2%), 10(15.4%) and 3(23.1%) respectively; serious TEAEs were 0, 3(4.6%) and 1(7.7%), none treatment-related. Conclusions: Long-term treatment with 155U, 156-195U, and 195U-onabotulinumtoxinA in PREDICT was safe and effective CM treatment. No new safety signals were identified.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 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".