Combination of Antidepressant Medications From Treatment Initiation for Major Depressive Disorder: A Double-Blind Randomized Study
Bibliographic record
Abstract
OBJECTIVE: Various classes of antidepressant medications generally induce remission of major depressive disorder in only about one-third of patients. In a previous study using mirtazapine or paroxetine alone or in combination from treatment initiation, the rate of patients who remitted within a 6-week period was twice that of patients using either drug alone. In this double-blind study, the authors sought to produce evidence for the superiority of different combinations of antidepressant drugs from treatment initiation. METHOD: Patients (N=105) meeting DSM-IV criteria for major depressive disorder were randomly assigned to receive, from treatment initiation, either fluoxetine monotherapy (20 mg/day) or mirtazapine (30 mg/day) in combination with fluoxetine (20 mg/day), venlafaxine (225 mg/day titrated in 14 days), or bupropion (150 mg/day) for 6 weeks. The primary outcome measure was the Hamilton Depression Rating Scale (HAM-D) score. RESULTS: The overall dropout rate was 15%, without notable differences among the four groups. Compared with fluoxetine monotherapy, all three combination groups had significantly greater improvements on the HAM-D. Remission rates (defined as a HAM-D score of 7 or less) were 25% for fluoxetine, 52% for mirtazapine plus fluoxetine, 58% for mirtazapine plus venlafaxine, and 46% for mirtazapine plus bupropion. Among patients who had a marked response, double-blind discontinuation of one agent produced a relapse in about 40% of cases. CONCLUSIONS: The combination treatments were as well tolerated as fluoxetine monotherapy and more clinically effective. The study results, which add to a growing body of evidence, suggest that use of antidepressant combinations from treatment initiation may double the likelihood of remission compared with use of a single medication.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".