Comparative efficacy and safety of rimegepant, ubrogepant, and lasmiditan for acute treatment of migraine: a network meta-analysis
Bibliographic record
Abstract
OBJECTIVE: In the absence of head-to-head comparisons, the objective of this study was to conduct a network meta-analysis (NMA) to indirectly compare the relative efficacy and safety of rimegepant, ubrogepant, and lasmiditan for the acute treatment of migraine. METHODS: A systematic literature review was conducted to identify randomized controlled trials (RCTs) of rimegepant, ubrogepant, and lasmiditan in adults with acute migraine. Outcomes included sustained pain freedom and -relief 2-48 hours post-dose, and adverse events. No RCTs were identified that directly compared these interventions. Therefore, a fixed-effects Bayesian NMA was conducted by identifying a connected (via comparison to placebo) network of RCTs. RESULTS: Five RCTs were identified as follows: rimegepant study 303 (n = 1,466), ubrogepant ACHIEVE I and II (n = 1,672 and n = 1,686, respectively), and lasmiditan SAMURAI and SPARTAN (n = 2,231 and n = 3,005, respectively). Efficacy outcomes (pain freedom and relief at 2, 24, 48 hours) tended to be highest for lasmiditan 200 mg and rimegepant followed lower doses of lasmiditan and all doses of ubrogepant. However, lasmiditan 200 mg was also associated with higher rates of adverse events, particularly somnolence and dizziness. CONCLUSIONS: Lasmiditan, rimegepant, and ubrogepant all performed significantly better than placebo with respect to pain freedom and pain relief. Efficacy results were similar for rimegepant and lasmiditan with rimegepant having higher rates of pain freedom and relief than lower doses of lasmiditan, while somnolence and dizziness outcomes were lower for rimegepant than higher doses of lasmiditan.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.030 | 0.049 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.053 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".