2SPD-011 Comparative efficacy of eptinezumab, galcanezumab, fremanezumab and erenumab in the preventive treatment of chronic migraine
Bibliographic record
Abstract
Background and Importance Several monoclonal antibodies for preventive treatment of chronic migraine have been approved in recent years. However, there are no studies that directly compare these treatments. Aim and Objectives To establish, through an indirect comparison (IC) against placebo, whether eptinezumab (Ep), galcanezumab (Ga), fremanezumab (Fre) and erenumab (Ere) could be considered equivalent alternatives in efficacy for the preventive treatment of chronic migraine. Material and Methods A PubMed search was performed for pivotal clinical trials (CTs) of eptinetumab (300 mg/12 weeks), galcanezumab (240 mg/4 weeks), fremanezumab (675 mg/12 weeks) and erenumab (140 mg/4 weeks) for the preventive treatment of chronic migraine. The variable for comparison was the percentage of patients with ≥75% response (% of patients with a 75% reduction in migraine days per month) at week 12 after the start of treatment. With the results of ≥75% response, relative risk (RR) compared to placebo was calculated. Finally, with these values, an IC of these drugs was performed using the Bucher method (ITC calculator, Indirect Treatment Comparisons, of the Canadian Agency for Health Technology Assessment). The results were analysed, seeing if there were statistically significant differences between these four drugs. Results Four CTs were found, one with each drug, all of them compared to placebo as a common comparator. All the studies presented a similar methodology. However, CT of erenumab was a phase 2 CT, while the others were phase 3. Moreover, in the erenumab CT the sample size (667 patients) was smaller than in the other CTs (between 1072 and 1130 patients). These limitations for IC were eventually accepted. After applying the Bucher method, the following results were obtained: OR (Ep 300 mg vs Gal2 40 mg) 0,89 [IC 95% 0,48–1,65]; p=0,70 OR (Ep 300 mg vs Fre 675 mg) 0,95 [IC 95% 0,56–1,61]; p=0,85 OR (Ep 300 mg vs Ere 140 mg) 1,21 [IC 95% 0,69–2,13]; p=0,50 OR (Fre 675 mg vs Gal 240 mg) 0,93 [IC 95% 0,46–1,89]; p=0,85 OR(Ere 140 mg vs Gal 240 mg ) 0,73 [IC 95% 0,35–1,52]; p=0,40 OR(Fre 675 mg vs Ere140 mg ) 1,28 [IC 95% 0,66–2,46]; p=0,47 Conclusion and Relevance According to the results obtained, given that no statistically significant differences have been established between the different drugs in terms of efficacy, the choice of one or the other should be based on safety and efficiency criteria. Nevertheless, it would be of special interest to have a direct comparison of these drugs to confirm the equivalence. References and/or Acknowledgements Conflict of Interest No conflict of interest
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.001 |
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".