Long-term efficacy of solriamfetol for excessive sleepiness in narcolepsy or obstructive sleep apnea
Bibliographic record
Abstract
Introduction: Solriamfetol (JZP-110), a selective dopamine and norepinephrine reuptake inhibitor, was effective in treating excessive daytime sleepiness (EDS) in narcolepsy and obstructive sleep apnea (OSA) in phase 3 studies. Aims and Objectives: To evaluate long-term safety and efficacy of solriamfetol for EDS in narcolepsy and OSA. Methods: Participants who completed prior solriamfetol studies initiated open-label (OL) solriamfetol with a 2-wk titration followed by a maintenance phase of ≤50 wk. A 2-wk placebo-controlled randomized withdrawal (RW) phase began after 6 mo. Change in Epworth Sleepiness Scale (ESS) during RW was the primary endpoint. Patient and Clinician Global Impression of Change (PGI-C and CGI-C, respectively) were secondary endpoints. Results: The safety population comprised 643 participants (226 narcolepsy; 417 OSA); 280 participants (141 placebo; 139 solriamfetol) comprised the RW modified intent-to-treat population. At RW end, least squares mean change in ESS score for placebo vs solriamfetol was 5.3 vs 1.6 (P<0.0001); higher percentages of participants on placebo vs solriamfetol had worsening on PGI-C and CGI-C (P<0.0001). Similar results were observed for each population separately. Maintenance of efficacy was observed with OL solriamfetol at study end. At wk 40, 43% of narcolepsy and 82% of OSA participants had ESS ≤10 (normal range). The most frequent adverse events (AEs; ≥5%) were headache, nausea, nasopharyngitis, insomnia, dry mouth, anxiety, decreased appetite, and upper respiratory tract infection; 27 (4.2%) participants had ≥1 serious AE. Conclusions: These results demonstrate long-term efficacy and safety of solriamfetol for EDS in narcolepsy or OSA.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".