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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".