Validity and Reproducibility of Measurement of Islet Autoreactivity by T-Cell Assays in Subjects With Early Type 1 Diabetes
Bibliographic record
Abstract
OBJECTIVE: Type 1 diabetes results from an immunemediated destruction of beta-cells, likely to be mediated by T lymphocytes, but the sensitivity, specificity, and other measures of validity of existing assays for islet autoreactive T-cells are not well established. Such assays are vital for monitoring responses to interventions that may modulate disease progression. RESEARCH DESIGN AND METHODS: We studied the ability of cellular assays to discriminate responses in patients with type 1 diabetes and normal control subjects in a randomized blinded study in the U.S. and U.K. We evaluated the reproducibility of these measurements overall and to individual analytes from repeat collections. RESULTS: Responses in the cellular immunoblot, U.K.-ELISPOT, and T-cell proliferation assays could differentiate patients from control subjects with odds ratios of 21.7, 3.44, and 3.36, respectively, with sensitivity and specificity as high as 74 and 88%. The class II tetramer and U.S. ELISPOT assays performed less well. Despite the significant association of the responses with type 1 diabetes, the reproducibility of the measured responses, both overall and individual analytes, was relatively low. Positive samples from normal control subjects (i.e., false positives) were generally isolated to single assays. CONCLUSIONS: The cellular immunoblot, U.K.-ELISPOT, and T-cell proliferation assays can distinguish responses from patients with type 1 diabetes and healthy control subjects. The limited reproducibility of the measurements overall and of responses to individual analytes may reflect the difficulty in detection of low frequency of antigen-specific T-cells or variability in their appearance in peripheral blood.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".