1442-P: Composite Scores Using Fasting and Stimulated C-Peptide Are Equivalent and Can Track Beta-Cell Function in New-Onset Type 1 Diabetes
Bibliographic record
Abstract
Composite scores using fasting samples have been developed to routinely monitor beta cell mass after islet transplantation in type 1 diabetes (T1D). They may also have utility in new onset or T1D prevention trials as an alternative to mixed meal tolerance tests measuring AUC C-peptide. We examined if a composite score using stimulated C-peptide was equivalent to fasting C-peptide in estimating beta cell mass in new onset T1D and reflected changes in AUC C-peptide over time. BETA-2 (fasting C-peptide, glucose, insulin dose, HbA1c) and BETA-2stim (using C-peptide AUC) were calculated in 1312 individuals from the TOMI dataset (median (IQR) age 16y (12, 24); 42% F). The dataset comprises 3200 participants within 100 days of diagnosis across 22 studies. Studies meeting their primary end point were deemed positive. BETA-2 and BETA-2stim were strongly correlated (R2=0.96, p<0.0001) and showed good agreement using Bland-Altman plots. Both BETA-2 and BETA-2stim showed changes over time which mirrored those for AUC C-peptide, but both composite scores showed differences between active and control participants in positive studies by 3 months while differences in AUC C-peptide were not seen until 6 months (Fig1). Composite scores using fasting C-peptide may provide a simple, sensitive and practical tool to monitor beta cell mass without complex stimulation tests in new onset diabetes. Disclosure A.Carr: None. K.S.Collins: None. S.Karpen: None. E.Atabakhsh: None. A.Lam: None. P.Taylor: None. C.Dayan: Advisory Panel; AstraZeneca, Consultant; Provention Bio, Sanofi, Avotres Inc., Other Relationship; Dompé, Merck & Co., Inc. P.A.Senior: Advisory Panel; Novo Nordisk Canada Inc., Consultant; Novo Nordisk Canada Inc., Bayer Inc., Viatris Inc., Vertex Pharmaceuticals Incorporated, ViaCyte, Inc., Insulet Corporation.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.006 |
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".