Efficacy and acceptability of lurasidone for bipolar depression: a systematic review and dose–response meta-analysis
Bibliographic record
Abstract
QUESTION: The optimal dose of lurasidone for bipolar depression is unclear. This study examined its dose-response relationship for efficacy, acceptability, and metabolic/endocrine profiles. STUDY SELECTION AND ANALYSIS: Five databases and grey literature published until 1 August 2024, were systematically reviewed. The outcomes included efficacy (changes in depression, anxiety, clinical global impression, disability and quality of life), acceptability (dropout, manic switch, suicidality and side effects) and metabolic/endocrine profiles (changes in body weight, glucose, lipid and prolactin levels). Effect sizes were calculated using a one-step dose-response meta-analysis, expressed as standardised mean differences (SMDs), risk ratios (RRs) and mean differences (MDs) with 95% CIs. FINDINGS: Five randomised clinical trials (2032 patients, mean treatment duration 6 weeks) indicated that the optimal therapeutic dose of lurasidone (40-60 mg) improved depression (50 mg: SMD -0.60 (95% CI -0.30, -0.89)), anxiety (50 mg: -0.32 (95% CI -0.21, -0.42)), clinical global impression (50 mg: -0.67 (95% CI -0.30, -1.03)) and disability (50 mg: -0.38 (95% CI -0.08, -0.69)). Side effects increased with higher doses (50 mg: RR 1.15 (95% CI 1.05, 1.25); 100 mg: 1.18 (95% CI 1.02, 1.36)), but dropout, manic switch and suicidality did not show a dose-effect relationship. Weight increased at doses<60 mg (40 mg: MD 0.38 (95% CI 0.16, 0.60) kg), while blood glucose levels rose at doses>70 mg (100 mg: 3.16 (95% CI 0.76, 5.57) mg/dL). Prolactin levels increased in both males (50 mg: 3.21 (95% CI 1.59, 4.84) ng/mL; 100 mg: 5.61 (95% CI 2.42, 8.81)) and females (50 mg: 6.64 (95% CI 3.50, 9.78); 100 mg: 5.33 (95% CI 0.67, 10.00)). CONCLUSIONS: A daily dose of 40-60 mg of lurasidone is a reasonable choice for bipolar depression treatment. TRIAL REGISTRATION NUMBER: INPLASY202430069.
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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 | 0.026 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.037 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".