Efficacy of onabotulinumtoxinA in the treatment of unipolar major depression: Systematic review, meta-analysis and meta-regression analyses of double-blind randomised controlled trials
Bibliographic record
Abstract
BACKGROUND: OnabotulinumtoxinA is a novel therapeutic intervention whose mechanism of action is believed to modify the negative facial feedback, thus abating symptoms of depression. This putative new antidepressant agent offers minimal systemic side effects and negligible risk of pharmacological interactions. We set out to examine the evidence for the use of onabotulinumtoxinA in major depression. METHODS: A systematic search of the literature identified double-blind randomised controlled trials (RCTs) investigating the use of onabotulinumtoxinA in the treatment of major depression versus placebo. Data, reported according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA), was combined in meta-analyses (PROSPERO registration ID: CRD42020183538). RESULTS: The search identified five RCTs (four double-blind) comparing onabotulinumtoxinA to placebo. OnabotulinumtoxinA was more effective than placebo when administered within the 20-40 IU dose range in double-blind RCTs. The analysis was free of publication bias and significantly heterogeneous. Meta-regression analyses indicated that onabotulinumtoxinA was more efficacious in women and in higher doses in female patients and less effective with polypharmacy, especially when an increasing number of antidepressants were prescribed. The effectiveness of onabotulinumtoxinA was higher in more recently published double-blind RCTs. CONCLUSION: The meta-analysis supports the efficacy of the intervention with the results being highly heterogeneous across studies. In view of the heterogeneity of the findings and the significant moderators of benefit (sex, year of study completion and the interaction between sex and dose), more research is required to better understand the role of onabotulinumtoxinA in the treatment of depression.
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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 | 0.025 | 0.054 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.030 | 0.051 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".