The Role of Biological Agents in the Management of Large Vessel Vasculitis (LVV): A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Giant cell arteritis (GCA) and Takayasu's arteritis (TAA) are large vessel vasculitides (LVV) for which corticosteroids (CS) are the mainstay for treatment. In patients with LVV unable to tolerate CS, biological agents have been used with variable effectiveness. OBJECTIVE: To systematically review the effectiveness and safety of biological agents in patients with LVV. METHODS: We searched 5 electronic databases (inception to October 2012) and conference abstracts with no language restrictions. Two reviewers independently selected studies, extracted data and assessed methodological quality. Our protocol was registered in PROSPERO. RESULTS: We included 25 studies (3 RCTs and 22 case series with ≥2 cases). 95 GCA and 98 TAA patients received biological agents. The RCTs using anti-TNF agents (infliximab, etanercept and adalimumab) did not suggest a benefit in GCA. GCA patients receiving tocilizumab, in case series, achieved remission (19 patients) and reduction of corticosteroid dose (mean difference, -16.55 mg/day (95% CI: -26.24, -6.86)). In case series, 75 patients with refractory TAA treated with infliximab discontinued CS 32% of the time. Remission was variably defined and the studies were clinically heterogeneous which precluded further analysis. CONCLUSION: This systematic review demonstrated a weak evidence base on which to assess the effectiveness of biological treatment in LVV. Evidence from RCTs suggests that anti-TNF agents are not effective for remission or reduction of CS use. Tocilizumab and infliximab may be effective in the management of LVV and refractory TAA, respectively, although the evidence comes from case series. Future analytical studies are needed to confirm these findings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".