A Randomized, Double‐Blind Trial of Abatacept (CTLA‐4Ig) for the Treatment of Giant Cell Arteritis
Bibliographic record
Abstract
OBJECTIVE: To compare the efficacy of abatacept to that of placebo for the treatment of giant cell arteritis (GCA). METHODS: In this multicenter trial, patients with newly diagnosed or relapsing GCA 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, 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 rate). RESULTS: Forty-nine eligible patients with GCA were enrolled and treated with prednisone and abatacept; of these, 41 reached the week 12 randomization and underwent a blinded randomization to receive abatacept or placebo. Prednisone was tapered using a standardized schedule, reaching a daily dosage of 20 mg at week 12 with discontinuation in all patients at week 28. The relapse-free survival rate at 12 months was 48% for those receiving abatacept and 31% for those receiving placebo (P = 0.049). A longer median duration of remission was seen in those receiving abatacept compared to those receiving placebo (median duration 9.9 months versus 3.9 months; P = 0.023). There was no difference in the frequency or severity of adverse events, including infection, between the treatment arms. CONCLUSION: In patients with GCA, the addition of abatacept to a treatment regimen with prednisone reduced the risk of relapse and was not associated with a higher rate of toxicity compared to prednisone alone.
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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 | 0.003 |
| 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) | 0.008 | 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".