Long-Term Efficacy of Clobazam for Drop Attacks in Lennox-Gastaut Syndrome Is Consistent Across Patient Age Ranges (P3.249)
Bibliographic record
Abstract
OBJECTIVE: We evaluated whether clobazam (CLB) was efficacious in decreasing weekly rates of drop seizures for all age groups over the long term. BACKGROUND: In a Phase III study (CONTAIN), CLB was consistently efficacious in decreasing weekly rates of drop seizures (baseline to maintenance phase) vs. placebo for all age groups and dosages, except for patients 蠅12 to <17 years of age in the low-dosage group (attributed to low sample sizes/not considered meaningful).1 DESIGN/METHODS: Patients who had completed 1 of 2 RCTs received CLB in an open-label extension (OLE) study. Most patients initially received 0.5 mg/kg/day (≤40 mg/day). Dosages were then adjusted based on efficacy/tolerability, up to 80 mg/day (maximum dosage). Visits were at Day 1, Week 1, Months 1, 2, 3, 6, 9, and 12, and every 6 months thereafter. We evaluated results from baseline (first day on CLB) for patients 蠅2 to <12 years of age; 蠅12 to ≤16 years; and >16 years. RESULTS: 267 patients entered the OLE. As of March 23, 2012, 188 (70.4%) had completed the study. 251 patients had received CLB for 蠅6 months, 229 for 蠅1 year, 210 for 蠅2 years, 121 for 蠅3 years, 54 for 蠅4 years, 44 for 蠅5 years, and 11 for 蠅6 years. At Years 1, 2, and 3, median percentage decreases for patients 蠅2 to <12 years were 83.5%, 86.3%, and 89.9%; for patients 蠅12 to ≤16 years were 94.2%, 91.3%, and 98.8%; and for patients >16 years were 76.4%, 81.3%, and 88.2%. Of note, efficacy persisted for those 蠅12 to ≤16 years. CONCLUSIONS: CLB was efficacious in the long term in decreasing drop seizures for all age groups (consistent with 15-week CONTAIN study). Seizure improvement in adult LGS patients was consistent with results for younger patients. 1Mitchell W, et al. Epilepsy Curr. 2012;12(1 Suppl 1):Abstract #B.04. Study Supported by: Lundbeck LLC.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".