Atypical Antipsychotic Augmentation for Treatment-Resistant Depression: A Systematic Review and Network Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Previous meta-analyses of atypical antipsychotics for depression were limited by few trials with direct comparisons between two treatments. We performed a network meta-analysis, which integrates direct and indirect evidence from randomized controlled trials (RCTs), to investigate the comparative efficacy and tolerability of adjunctive atypical antipsychotics for treatment-resistant depression (TRD). METHODS: Systematic searches resulted in 18 RCTs (total n = 4422) of seven different types and different dosages of atypical antipsychotics and a placebo that were included in the review. RESULTS: All standard-dose atypical antipsychotics were significantly more efficacious than placebo in the efficacy (standardized mean differences [SMDs] ranged from -0.27 to -0.43). There were no significant differences between these drugs. Low-dose atypical antipsychotics were not significantly more efficacious than the placebo. In terms of tolerability, all standard-dose atypical antipsychotics, apart from risperidone, had significantly more side-effect discontinuations than placebo (odds ratios [ORs] ranged from 2.72 to 6.40). In terms of acceptability, only quetiapine (mean 250-350 mg daily) had significantly more all-cause discontinuation than placebo (OR = 1.89). In terms of quality of life/functioning, standard-dose risperidone and standard-dose aripiprazole were more beneficial than placebo (SMD = -0.38; SMD = -0.26, respectively), and standard-dose risperidone was superior to quetiapine (mean 250-350 mg daily). CONCLUSIONS: All standard-dose atypical antipsychotics for the adjunctive treatment of TRD are efficacious in reducing depressive symptoms. Risperidone and aripiprazole also showed benefits in improving the quality of life of patients. Atypical antipsychotics should be prescribed with caution due to abundant evidence of side effects.
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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 | 0.020 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.035 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".