Antidepressant Prophylaxis Reduces Depression Risk but Does Not Improve Sustained Virological Response in Hepatitis C Patients Receiving Interferon Without Depression at Baseline: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Depression complicates interferon-based hepatitis C virus (HCV) antiviral therapy in 10% to 40% of cases, and diminishes patient well-being and ability to complete a full course of therapy. As a consequence, the likelihood of achieving a sustained virological response (SVR [ie, permanent viral eradication]) is reduced. OBJECTIVE: To systematically review the evidence of whether pre-emptive antidepressant prophylaxis started before HCV antiviral initiation is beneficial. METHODS: Inclusion was restricted to randomized controlled trials in which prophylactic antidepressant therapy was started at least two weeks before the initiation of HCV antiviral treatment. Studies pertaining to patients with active or recent depressive symptoms before commencing HCV antiviral therapy were excluded. English language articles from 1946 to July 2012 were included. The MEDLINE, Embase and Cochrane Central databases were searched. Where possible, meta-analyses were conducted evaluating the effect of antidepressant prophylaxis on SVR and major depression as well as on Montgomery-Asberg Depression Rating Scale and Beck Depression Index scores at four, 12 and 24 weeks. The Cochrane Collaboration tool was used to assess bias risk. RESULTS: Six randomized clinical trials involving 522 patients met the inclusion criteria. Although the frequency of on-treatment clinical depression was decreased with antidepressant prophylaxis (risk ratio 0.60 [95% CI 0.38 to 0.93]; P=0.02; I2=24%), no benefit to SVR was identified (risk ratio 1.08 [95% CI 0.74 to 1.57]; P=0.69; I2=58%). CONCLUSION: This practice is not justified to improve SVR in populations free of active depressive symptoms leading up to HCV antiviral therapy.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.030 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".