Effects of Discontinuation of Drugs Used for Augmentation Therapy on Treatment Outcomes in Depression: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
INTRODUCTION: There has been no consensus on whether and how long add-on drugs for augmentation therapy should be continued in the treatment of depression. METHODS: Double-blind randomized controlled trials that examined the effects of discontinuation of drugs used for augmentation on treatment outcomes in patients with depression were identified. Meta-analyses were performed to compare rates of study withdrawal due to any reason, study-defined relapse, and adverse events between patients who continued augmentation therapy and those who discontinued it. RESULTS: Seven studies were included (n=841 for continuing augmentation therapy; n=831 for discontinuing augmentation therapy). The rate of study withdrawal due to any reason was not significantly different between the 2 groups (risk ratio [RR]=0.86, 95% confidence interval [CI]=0.69-1.08, p=0.20). Study withdrawal due to relapse was less frequent in the continuation group than in the discontinuation group (RR=0.61, 95% CI=0.40-0.92, p=0.02); however, this statistical significance disappeared when one study using esketamine as augmentation was excluded. Analysis of the data from 5 studies that included a stabilization period before randomization found less frequent relapse in the continuation group than in the discontinuation group (RR=0.47, 95% CI=0.36-0.60, p<0.01). This finding was repeated when the esketamine study was excluded. DISCUSSION: No firm conclusions could be drawn in light of the small number of studies included. Currently available evidence suggests that add-on drugs, other than esketamine, used for augmentation therapy for depression may be discontinued. This may not be the case for patients who are maintained with augmentation therapy after remission.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| 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".