Comparative efficacy of pharmacological treatments on measures of self-rated functional outcomes using the Sheehan Disability Scale in patients with major depressive disorder: a systematic review and network meta-analysis
Bibliographic record
Abstract
OBJECTIVE: More than 50% patients with major depressive disorder (MDD) have severe functional impairment. The restoration of patient functioning is a critical therapeutic goal among patients with MDD. We conducted a systematic review and network meta-analysis to evaluate the efficacy of pharmacological treatments on self-rated functional outcomes using the Sheehan Disability Scale in adults with MDD in randomized clinical trials. METHODS: PubMed, EMBASE, PsycINFO, Cochrane Library, and ClinicalTrials.gov were searched from inception to December 10, 2019. Summary statistics are reported as weighted mean differences with 95% confidence intervals. Interventions were ranked using the surface under the cumulative ranking probabilities. RESULTS: We included 42 randomized controlled trials (RCTs) (n = 18 998) evaluating the efficacy of 13 different pharmacological treatments on functional outcomes, as measured by the Sheehan Disability Scale (SDS). Duloxetine was the most effective pharmacological agent on functional outcomes, followed by (ranked by efficacy): paroxetine, levomilnacipran, venlafaxine, quetiapine, desvenlafaxine, agomelatine, escitalopram, amitriptyline, bupropion, sertraline, vortioxetine, and fluoxetine. Serotonin and norepinephrine reuptake inhibitors were more effective than other drug classes. Additionally, the comparison-adjusted funnel plot suggested the publication bias between small and large studies was relatively low. CONCLUSIONS: Our results indicate that there may be differences across antidepressant agents and classes with respect to self-reported functional outcomes. Validation and replication of these findings in large-scale RCTs are warranted. Our research results will be clinically useful for guiding psychiatrists in treating patients with MDD and functional impairment. PROSPERO registration number CRD42018116663.
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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 | 0.019 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.033 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".