0549 Patient-Reported Outcomes for LEMborexant Treatment in Chinese Patients with Insomnia (PROEM): A Real-World Study
Bibliographic record
Abstract
Abstract Introduction Lemborexant (LEM) is a novel dual orexin receptor antagonist approved for treating adults with insomnia in the United States, Canada, Japan and some other countries. Except for one case report, there has been no published study of LEM treatment for patients with insomnia in China. This study assessed LEM treatment for patients with insomnia in routine clinical practice in China. Methods This multicenter, prospective, 12-week, real-world observational study (NCT06225947) plans to enroll 200 adult patients with insomnia who visited 1 of the 5 participating hospitals in China from Feburary2024. All patients were treated with LEM as per routine clinical practice. For the interim analysis, the primary endpoint was remitter rate after 4 weeks of treatment (patients with a post-treatment Insomnia Severity Index [ISI] score of < 8.). Treatment-emergent adverse events (TEAEs) were recorded. Results By the cut-off date of the interim analysis, 100 patients had been taking LEM for at ≥4 weeks (79) or withdrew from the study (21). They had a mean age of 45.18±13.17 years, mean insomnia duration of 6.35±7.71 years, and a mean baseline ISI score of 17.13±4.12 points. Sixty-four (64.00%) patients were female. Twenty-three (23.00%), 6 (6.00%) and 71 (71.00%) patients received LEM as initial monotherapy, transitioned to LEM, or added LEM to existing hypnotic therapy, respectively. The remitter rate was 33.00% (33/100) after 4 weeks of treatment, and the responder rates (ISI score decreased ≥6 points from baseline) after 1, 2 and 4weeks of treatment were 40.00% (40/100), 52.00% (52/100) and 54.00% (54/100), respectively. Mean ISI and Patient Health Questionnaire-9 scores decreased significantly after 1 week of treatment (-4.79±5.68, -1.03±4.04, respectively, both P< 0.001) and continued to decrease (-8.10±5.21, -2.71±3.51 after 4 weeks of treatment, respectively). Mean General Anxiety Disorder-7 score decreased significantly after 2 weeks of treatment and continued to decrease during the study. Hence, LEM treatment improved their mood as well. Twenty-two (22.00%) patients experienced mild (21) or moderate (1) treatment-related TEAEs. The most common TEAE was somnolence (11.00%). Conclusion This first real-world observational study of LEM treatment in China demonstrated that LEM treatment was effective and safe in treating Chinese adult patients with insomnia. Support (if any)
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".