Effect of biologics on depressive symptoms in patients with psoriasis: a systematic review
Bibliographic record
Abstract
BACKGROUND: Twenty to fifty percent of patients with psoriasis have depressive symptoms. OBJECTIVE: To describe the effects of biologics (tumour necrosis factor inhibitors [TNFi] or interleukin 12/23 inhibitors [IL-12/23i]) on depressive symptoms in patients with psoriasis. METHODS: Electronic databases were searched for randomized controlled trials (RCTs) examining the effects of biologics on depressive symptoms in adults with psoriasis. RESULTS: Of the 305 publications identified, three RCTs were included in a systematic review. In a trial evaluating ustekinumab, mean change in Hospital and Anxiety Depression Rating Scale at 24 weeks from baseline was 3.1 with ustekinumab (P < 0.001) vs. 0.21 with placebo (not significant). In a trial evaluating adalimumab, mean change in Zung Self-Rating Depression Scale at 12 weeks from baseline was -6.7 with adalimumab vs. -1.5 with placebo. In a trial evaluating etanercept, the between-group difference at 12 weeks in Beck Depression Inventory Scale was 1.8 (95% CI: 0.6, 2.90) in favour of etanercept over placebo. Limitations are that diagnostic criteria for depression were not used and scales and data from individual RCTs could not be combined. CONCLUSION: Adalimumab, etanercept and ustekinumab were associated with statistically significant reductions in depressive symptom scores using various scales in patients with moderate-to-severe psoriasis.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".