Efficacy of Lumateperone in depression associated with bipolar II disorder: a pooled analysis of late-phase clinical trials
Bibliographic record
Abstract
Abstract Objective Treatment options are limited for depressive episodes in patients with bipolar II disorder. This post hoc analysis evaluated the efficacy of lumateperone in three pooled short-term, Phase 3 studies in patients with a major depressive episode (MDE) associated with bipolar II disorder. Methods This post hoc analysis pooled data from patients (18–75 years) with DSM-5 diagnosed bipolar II disorder experiencing an MDE in randomized, double-blind, placebo-controlled studies of lumateperone 42 mg monotherapy (Study 401, Study 404) and adjunctive therapy to lithium or valproate (Study 402). Primary and key secondary outcomes were change from baseline in Montgomery-Åsberg Depression Rating Scale (MADRS) Total and Clinical Global Impression Scale-Bipolar Version-Severity (CGI-BP-S) scores. Safety was also assessed. Results Lumateperone significantly improved MADRS Total score at Day 43 in the bipolar II population (placebo, n = 87; lumateperone, n = 87; least squares mean difference vs. placebo [LSMD], −4.0; P < .05). In the bipolar II population, lumateperone significantly improved CGI-BP-S Total (LSMD, −1.0; P < .05), Depression (LSMD, −0.5; P < .05), and Overall Bipolar Illness scores (LSMD, −0.5; P < .05) compared with placebo at Day 43. No new safety signals were identified, with minimal risk of extrapyramidal symptoms, cardiometabolic abnormalities, or prolactin elevation. Conclusions Lumateperone 42 mg monotherapy or adjunctive therapy significantly improved symptoms of depression and disease severity in patients with bipolar II disorder across Phase 3 studies. Lumateperone was generally well tolerated. These results support lumateperone 42 mg to treat MDEs associated with bipolar II disorder.
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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 | 0.016 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.014 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".