Escitalopram in the treatment of major depressive disorder: A meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To assess the relative antidepressant efficacy of escitalopram and comparator antidepressants. RESEARCH DESIGN AND METHODS: A meta-analysis was performed using studies in major depressive disorder (MDD) comparing escitalopram with active controls, including selective serotonin reuptake inhibitors [SSRIs] (citalopram, fluoxetine, paroxetine, sertraline) and serotonin/noradrenaline reuptake inhibitors [SNRIs] (venlafaxine, duloxetine). Adult patients had to meet DSM-IV criteria for MDD. MAIN OUTCOME MEASURES: The primary outcome measure was the treatment difference in Montgomery-Asberg Depression Rating Scale (MADRS) total score at week 8. Secondary outcome measures were response and remission (MADRS total score < or = 12) rates. RESULTS: Individual patient data (N = 4549) from 16 randomized controlled trials were included in the analyses (escitalopram n = 2272, SSRIs n = 1750, SNRIs n = 527). Escitalopram was significantly more effective than comparators in overall treatment effect, with an estimated mean treatment difference of 1.1 points on the MADRS (p < 0.0001), and in responder (63.7 vs. 58.3%, p < 0.0001) and remitter (53.1 vs. 49.4%, p < 0.0059) analyses. Escitalopram was significantly superior to SSRIs, with an estimated difference in response of 62.1 vs. 58.4% and remission of 51.6 vs. 49.0%. In comparison to SNRIs, the estimated difference in response was 68.3 vs. 59.0% (p = 0.0007) and for remission the difference was 57.8 vs. 50.5% (p = 0.0088). These results were similar for severely depressed patients (baseline MADRS > or = 30). Sensitivity analyses were performed with data from articles reporting Hamilton Rating Scale for Depression (HAMD) scores. The 8-week withdrawal rate due to adverse events was 5.4% for escitalopram and 7.9% for the comparators (p < 0.01). This difference was accounted for by statistically significant higher attrition rates in the SNRI comparisons. This work may be limited by the clinical methodology underlying meta-analytic studies, in particular, the exclusion of trials that fail to meet predetermined criteria for inclusion. CONCLUSIONS: In this meta-analysis, superior efficacy of escitalopram compared to SSRIs and SNRIs was confirmed, although the superiority over SSRIs was largely explained by differences between escitalopram and citalopram.
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.031 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".