Usefulness of Mirogabalin in Central Neuropathic Pain After Stroke: Post Hoc Analysis of a Phase 3 Study by Stroke Type and Location
Bibliographic record
Abstract
INTRODUCTION: δ ligand that is effective for the treatment of CNeP, including CPSP. However, it is unknown whether the analgesic effect of mirogabalin on CPSP varies in patients with different background factors. METHODS: This was a post hoc subgroup analysis of a multinational, open-label, long-term phase 3 study of mirogabalin for the treatment of CNeP conducted between March 2019 and December 2020. Data from patients with CPSP were stratified by type of stroke (ischemic or hemorrhagic), stroke location (thalamus, putamen, brainstem, or other), presence/absence of motor weakness, median time since stroke (≥ 59 or < 59 months), and median duration of CPSP (≥ 55.5 or < 55.5 months). Efficacy was assessed with the short-form McGill Pain Questionnaire (SF-MPQ), and treatment-emergent adverse events (TEAEs) and adverse drug reactions (ADRs) were recorded. RESULTS: This subanalysis included all 94 patients with CPSP from the phase 3 study; all were Japanese, and the mean age was 65.3 years. The least squares mean change [95% confidence interval] in SF-MPQ visual analog scale (VAS) score from baseline at week 52 (last observation carried forward) was - 17.0 [- 22.1, - 11.9] mm. Among the subgroups, least squares mean changes in SF-MPQ VAS scores were not different. Most TEAEs were mild or moderate; severe TEAEs occurred in six patients (6.4%). Somnolence (25.5%), peripheral edema (13.8%), dizziness (11.7%), and weight gain (6.4%) were the most common ADRs, and the types and frequencies of ADRs were similar among subgroups. CONCLUSION: Mirogabalin was generally effective and well tolerated in patients with CPSP, regardless of background factors such as stroke type or location, presence/absence of motor weakness, time since stroke, and duration of CPSP. TRIAL REGISTRATION: Trial registration number NCT03901352.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".