Minocycline in depression not responding to first-line therapy: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Major depressive disorder is often resistant to first-line treatment, with around 30% failing to respond to traditional therapy. Treatment-resistant depression results in prolonged hospitalization and healthcare costs. Anti-inflammatory drugs have shown promising results in depression not responding to initial therapy. Minocycline has anti-inflammatory properties and crosses the blood-brain barrier. It has demonstrated varied results in several randomized controlled trials (RCTs). METHODS: We assessed the efficacy of minocycline compared to placebo in depression not responding to one first-line antidepressant via a systematic review and meta-analysis. We performed a comprehensive literature search across PubMed, Cochrane, and Scopus for RCTs. We visualized the results using forest plots and drapery plots. We assessed and explored heterogeneity using I2, prediction interval, and meta-regression. Then, we rated the certainty of the evidence. RESULTS: Four RCTs revealed a non-significant difference in depression severity [-3.93; 95% CI: -16.14 to 8.28], rate of response [1.15; 0.33-4.01], and rate of remission [0.94; 0.44-2.01]. However, the reduction in depression severity is significant at a trend of P < .1. The high between-study heterogeneity (I2 = 78%) for depression severity could be answered by meta-regression (P = .02) for the duration of therapy. CONCLUSION: There is no significant difference with minocycline compared to placebo for depression not responding to first-line antidepressant therapy. However, the treatment response varies with treatment duration and patients' neuroinflammatory state. Thus, larger and longer RCTs, especially in diverse disease subgroups, are needed for further insight. This is needed to allow greater precision medicine in depression and avoid elevated healthcare expenditure associated with hit-and-trial regimens. REGISTRATION: CRD42023398476 (PROSPERO).
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.040 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".