Desvenlafaxine for the Prevention of Relapse in Major Depressive Disorder
Bibliographic record
Abstract
OBJECTIVES: To compare the efficacy and safety of desvenlafaxine (administered as desvenlafaxine succinate) with placebo in reducing relapse rate in patients with major depressive disorder (MDD). METHODS: This phase 3, multicenter, randomized trial included a 12-week, open-label (OL) treatment phase (intent-to-treat population, n = 575) followed by a 6-month, double-blind (DB) relapse prevention phase. Patients who responded to the OL treatment (17-item Hamilton Rating Scale for Depression total score or= 16 at any visit, Clinical Global Impression-Improvement score >or= 6 at any visit, or discontinuation due to unsatisfactory response). RESULTS: Patients receiving desvenlafaxine (n = 189) experienced significantly longer times to relapse of MDD versus patients receiving placebo (n = 185) during the DB period (log-rank test, P < 0.0001). The percentages of patients relapsing were 42% (78/185) and 24% (45/189) for placebo and desvenlafaxine, respectively (P < 0.001). The most common primary reason cited for discontinuation in the OL period was adverse events (19%), which consisted of nausea, dizziness, and insomnia. A total of 159 patients (42%) discontinued treatment during the DB period, including 101 placebo- (55%) and 58 desvenlafaxine-treated patients (31%). The most frequent adverse event reported as reason for treatment discontinuation in the DB period was depression, reported by 14 placebo- (8%) and 7 desvenlafaxine-treated patients (4%). CONCLUSIONS: Desvenlafaxine effectively prevented relapse of MDD during 6 months of DB treatment in patients who had responded to 12 weeks of OL desvenlafaxine therapy.
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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 | 0.001 | 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".