Which antidepressants have demonstrated superior efficacy? A review of the evidence
Bibliographic record
Abstract
A review of published evidence of superior efficacy of a particular antidepressant in major depressive disorder may assist clinicians in making considered treatment choices. To identify such candidates, an international group of experts met to assess published evidence (identified through searches in Medline and Embase databases and discussions with experts in the field) from randomized, controlled trials and meta-analyses comparing two antidepressants under conditions of fair comparison. Criteria were defined to judge the strength of evidence. Two pivotal studies in moderate-to-severe major depressive disorder that demonstrate superiority on the primary efficacy measure, or alternatively one pivotal study supported by consistent results from meta-analyses, was considered to constitute evidence for definite superiority. Three antidepressants met these criteria: clomipramine, venlafaxine, and escitalopram. Three antidepressants were found to have probable superiority: milnacipran, duloxetine, and mirtazapine. Only escitalopram was found to have definite superiority in the treatment of severe depression; probable superiority was identified for venlafaxine and possible superiority for milnacipran and clomipramine. This review of published data found evidence that only a very few antidepressants are shown to be more effective than others.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".