A Randomized, Double‐Blind Trial of Abatacept (CTLA‐4Ig) for the Treatment of Takayasu Arteritis
Bibliographic record
Abstract
Objective To compare the efficacy of abatacept to that of placebo for the treatment of Takayasu arteritis (TAK). Methods In this multicenter trial, patients with newly diagnosed or relapsing TAK were treated with abatacept 10 mg/kg intravenously on days 1, 15, and 29 and week 8, together with prednisone administered daily. At week 12, patients in remission underwent a double‐blinded randomization to continue to receive abatacept monthly or switch to placebo. Patients in both study arms received a standardized prednisone taper, reaching a dosage of 20 mg daily at week 12, with discontinuation of prednisone at week 28. All patients remained on their randomized assignment until meeting criteria for early termination or until 12 months after enrollment of the last patient. The primary end point was duration of remission (relapse‐free survival). Results Thirty‐four eligible patients with TAK were enrolled and treated with prednisone and abatacept; of these, 26 reached the week 12 randomization and underwent a blinded randomization to receive either abatacept or placebo. The relapse‐free survival rate at 12 months was 22% for those receiving abatacept and 40% for those receiving placebo ( P = 0.853). Treatment with abatacept in patients with TAK enrolled in this study was not associated with a longer median duration of remission (median duration 5.5 months for abatacept versus 5.7 months for placebo). There was no difference in the frequency or severity of adverse events, including infection, between the treatment arms. Conclusion In patients with TAK, the addition of abatacept to a treatment regimen with prednisone did not reduce the risk of relapse.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".