Comparative efficacy of escitalopram in the treatment of major depressive disorder
Bibliographic record
Abstract
BACKGROUND: Escitalopram is an allosteric selective serotonin reuptake inhibitor (SSRI) with some indication of superior efficacy in the treatment of major depressive disorder. In this systematic review, we critically evaluate the evidence for comparative efficacy and tolerability of escitalopram, focusing on pooled and meta-analysis studies. METHODS: A literature search was conducted for escitalopram studies that quantitatively synthesized data from comparative randomized controlled trials in MDD. Studies were excluded if they did not focus on efficacy, involved primarily subgroups of patients, or synthesized data included in subsequent studies. Outcomes extracted from the included studies were weighted mean difference or standard mean difference, response and remission rates, and withdrawal rate owing to adverse events. RESULTS: The search initially identified 24 eligible studies, of which 12 (six pooled analysis and six meta-analysis studies) met the criteria for review. The pooled and meta-analysis studies with citalopram showed significant but modest differences in favor of escitalopram, with weighted mean differences ranging from 1.13 to 1.73 points on the Montgomery Asberg Depression Rating Scale, response rate differences of 7.0%-8.3%, and remission rate differences of 5.1%-17.6%. Pooled analysis studies showed efficacy differences compared with duloxetine and with serotonin noradrenaline reuptake inhibitors combined, but meta-analysis studies did not. The effect sizes of the efficacy differences increased in the severely depressed patient subgroups. CONCLUSION: Based on pooled and meta-analysis studies, escitalopram demonstrates superior efficacy compared with citalopram and with SSRIs combined. Escitalopram shows similar efficacy to serotonin noradrenaline reuptake inhibitors but the number of trials in these comparisons is limited. Efficacy differences are modest but clinically relevant, especially in more severely depressed patients.
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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) | 0.000 | 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".