Randomized, double‐blind, 6‐week non‐inferiority study of lurasidone and risperidone for the treatment of schizophrenia
Bibliographic record
Abstract
AIM: The aim of the present study was to evaluate the efficacy and safety of lurasidone for the treatment of Chinese schizophrenic patients. METHODS: Hospitalized schizophrenia patients aged 18-65 were randomized to 6 weeks of double-blind, double-dummy, flexible-dose treatment with lurasidone (40 or 80 mg/day) or risperidone (2, 4 or 6 mg/day). Efficacy was evaluated using a non-inferiority comparison of lurasidone relative to risperidone based on week 6 change in the Positive and Negative Syndrome Scale (PANSS) total score. Safety assessments included adverse events, clinical laboratory measures, and electrocardiograms. RESULTS: Four hundred and forty-four patients were screened to obtain an intent-to-treat sample of 384 patients, of whom 54 patients discontinued treatment prior to 6 weeks. Lurasidone met the criteria for non-inferiority versus risperidone on the PANSS total score. Adjusted mean (SE) change at week 6 on the PANSS total score was -31.2 (1.0) and -34.9 (1.0) in the lurasidone and risperidone group, respectively. The mean difference score was 3.7, and the upper boundary of the 95%-confidence interval (1.0-6.3) was less than the prespecified margin of 7.0. No clinically meaningful between-treatment group differences were evident on secondary efficacy measures, including PANSS positive, PANSS negative, Clinical Global Impression scale - Severity, and Calgary Depression Scale for Schizophrenia scales. The incidence of adverse events was lower for lurasidone vs risperidone for extrapyramidal symptoms (17.0% vs 38.2%), akathisia (7.2% vs 13.6%), prolactin increase (3.1% vs 14.1%), and weight increase (0.5% vs 5.2%). CONCLUSION: Lurasidone was found to be non-inferior to risperidone on the primary endpoint with minimal effects on weight, metabolic parameters, or prolactin levels.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".