Abatacept for Delay of Type 1 Diabetes Progression in Stage 1 Relatives at Risk: A Randomized, Double-Masked, Controlled Trial
Bibliographic record
Abstract
OBJECTIVE: Previous studies showed that inhibiting lymphocyte costimulation reduces declining β-cell function in individuals newly diagnosed with type 1 diabetes. We tested whether abatacept would delay or prevent progression of type 1 diabetes from normal glucose tolerance (NGT) to abnormal glucose tolerance (AGT) or to diabetes and the effects of treatment on immune and metabolic responses. RESEARCH DESIGN AND METHODS: We conducted a phase 2, randomized, placebo-controlled, double-masked trial of abatacept in antibody-positive participants with NGT who received monthly abatacept/placebo infusions for 12 months. The end point was AGT or diabetes, assessed by oral glucose tolerance tests. RESULTS: A total of 101 participants received abatacept and 111 placebo. Of these, 81 (35 abatacept and 46 placebo) met the end point of AGT or type 1 diabetes diagnosis (hazard ratio 0.702; 95% CI 0.452, 1.09; P = 0.11) The C-peptide responses to oral glucose tolerance tests were higher in the abatacept arm (P < 0.03). Abatacept reduced the frequency of inducible T-cell costimulatory (ICOS)+ PD1+ T-follicular helper (Tfh) cells during treatment (P < 0.0001), increased naive CD4+ T cells, and also reduced the frequency of CD4+ regulatory T cells (Tregs) from the baseline (P = 0.0067). Twelve months after treatment, the frequency of ICOS+ Tfh, naive CD4+ T cells, and Tregs returned to baseline. CONCLUSIONS: Although abatacept treatment for 1 year did not significantly delay progression to glucose intolerance in at-risk individuals, it impacted immune cell subsets and preserved insulin secretion, suggesting that costimulation blockade may modify progression of type 1 diabetes.
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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 | 0.001 | 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) | 0.000 | 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".