P.053 Efficacy of lemborexant in adults with insomnia is supported by improvements in both objective and subjective measures
Bibliographic record
Abstract
Background: Improvements in sleep-onset, maintenance, and daytime functioning, are all important outcomes for the treatment of insomnia. These improvements are usually assessed by objective or patient-reported (subjective) measures or both. Some sleep-promoting drugs do not report consistently aligned subjective and objective outcomes. Therefore, we examined concordance in change from baseline (CFB) in sleep parameters (objective/subjective measures) and daytime functioning (subjective measures) in the clinical program of lemborexant (LEM), a dual-orexin receptor antagonist. Methods: Study E2006-G000-304 (NCT02783729), a 1-month, placebo (PBO)- and active-controlled (zolpidem; not discussed here) study, and Study E2006-G000-303 (NCT02952820), a 12-month, randomized, PBO-controlled study (first 6-months), evaluated the efficacy/safety of LEM 5mg (LEM5) and LEM 10mg (LEM10) in subjects with insomnia disorder. The primary/secondary endpoints in both studies included multiple objective/subjective sleep parameters and patient-reported measures, which were assessed for concordance. Results: In both studies, statistically significant improvements with LEM5/LEM10 were reported in multiple objective and patient-reported measures versus PBO, showing a concordance of results, with observed improvements continuing through 12 months. LEM was well tolerated; most treatment-emergent adverse events were mild/moderate. Conclusions: When deciding which sleep agent to prescribe, it is important that improvement can be demonstrated in both objective and patient-reported measures. LEM treatment showed concordance among observed measures.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.084 | 0.007 |
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".