Perampanel for the treatment of people with idiopathic generalized epilepsy in clinical practice
Bibliographic record
Abstract
OBJECTIVE: This study was undertaken to evaluate perampanel (PER) when used under real-world conditions to treat people with idiopathic generalized epilepsy (IGE) included in the PERaMpanel pooled analysIs of effecTiveness and tolerability (PERMIT) study. METHODS: The multinational, retrospective, pooled analysis PERMIT explored the use of PER in people with focal and generalized epilepsy treated in clinical practice across 17 countries. This subgroup analysis included PERMIT participants with IGE. Time points for retention and effectiveness measurements were 3, 6, and 12 months (last observation carried forward, defined as "last visit," was also applied to effectiveness). Effectiveness was evaluated by seizure type (total seizures, generalized tonic-clonic seizures [GTCS], myoclonic seizures, absence seizures) and included ≥50% responder rate and seizure freedom rate (defined as no seizures since at least the previous visit). Safety/tolerability was monitored throughout PER treatment and evaluated by documenting the incidence of adverse events (AEs), including psychiatric AEs and those leading to treatment discontinuation. RESULTS: The Full Analysis Set included 544 people with IGE (51.9% women, mean age = 33.3 years, mean epilepsy duration = 18.1 years). At 3, 6, and 12 months, 92.4%, 85.5%, and 77.3% of participants were retained on PER treatment, respectively (Retention Population, n = 497). At the last visit, responder and seizure freedom rates were, respectively, 74.2% and 54.6% (total seizures), 81.2% and 61.5% (GTCS), 85.7% and 66.0% (myoclonic seizures), and 90.5% and 81.0% (absence seizures) (Effectiveness Population, n = 467). AEs occurred in 42.9% of patients and included irritability (9.6%), dizziness/vertigo (9.2%), and somnolence (6.3%) (Tolerability Population, n = 520). Treatment discontinuation due to AEs was 12.4% over 12 months. SIGNIFICANCE: This subgroup analysis of the PERMIT study demonstrated the effectiveness and good tolerability of PER in people with IGE when administered under everyday clinical practice conditions. These findings are in line with clinical trial evidence, supporting PER's use as broad-spectrum antiseizure medication for the treatment of IGE.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".