362. COMPARISON OF EFFICACY AND SAFETY BETWEEN TOCILIZUMAB AND CYCLOPHOSPHAMIDE IN TREATING PATIENTS WITH TAKAYASU’S ARTERITIS
Bibliographic record
Abstract
Background: Tocilizumab (TCZ) benefits for controlling disease activity of giant cell arteritis, it does also for that of Takayasu’s arteritis (TAK). However, the characteristics of TCZ working in TAK and the advantages/disadvantages of TCZ and its reference cyclophosphamide (CYC) in TAK have not well been evaluated. Here, in this retrospective study, we compare the efficacy and safety between Tocilizumab and cyclophosphamide in treating patients with Takayasu’s arteritis. Methods: 49 patients with TAK were successively enrolled in this study. Each patient matched the classification of TAK proposed by American College of Rheumatology (ACR) in 1990. Among them, 27 patients were treated with TCZ (TCZ group), 22 patients were treated with CYC (CYC group). Clinical, laboratory, and imaging data were collected in six months span. Results: After 6 months therapy, the ESR, CRP levels and disease activity scores in TCZ group were significantly lower than those in CYC group [ESR 3 (2,6) mm/h vs.8(5,17) mm/h; CRP 0.13 (0.05,0.99) mg/L vs. 1.09 (0.46,3.33) mg/L; NIH score 0 (0,1) vs. 0 (1,1); ITAS2010 score 0 (0,2) vs. 0(0,3.5); ITAS.A score 0 (0,2) vs. 2.5 (0,3.5)] respectively (P < 0.05). The daily dose of prednisone in the TCZ group was lower than that in the CYC group, which was 20.1, 15.9 mg/d vs. 39.3, 16.7 mg/d prior to treatment (P < 0.05) and 5.1, 4.2 mg/d vs. 12.1, 4.6 mg/d after treatment (P < 0.05). The incidence of side events in TCZ group was significantly lower than that in CYC group (22.2% vs. 54.5%) individually (P < 0.05). Conclusion: Compared with CYC, TCZ had better efficacy and less side events in patients with TAK. Disclosures: None
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".