Ustekinumab for type 1 diabetes in adolescents: a multicenter, double-blind, randomized phase 2 trial
Bibliographic record
Abstract
Abstract Immunotherapy targeting the autoimmune process in type 1 diabetes (T1D) can delay the loss of β-cells but needs to have minimal adverse effects to be an adjunct to insulin in the management of T1D. Ustekinumab binds to the shared p40 subunit of interleukin (IL)-12 and IL-23, targeting development of T helper 1 cells and T helper 17 cells (TH1 and TH17 cells) implicated in the pathogenesis of T1D. We conducted a double-blind, randomized controlled trial of ustekinumab in 72 adolescents aged 12–18 years with recent-onset T1D. Treatment was well tolerated with no increase in adverse events. At 12 months, β-cell function, measured by stimulated C-peptide, was 49% higher in the intervention group (P = 0.02), meeting the prespecified primary outcome. Preservation of C-peptide correlated with the reduction of T helper cells co-secreting IL-17A and interferon-γ (TH17.1 cells, P = 0.04) and, in particular, with the reduction in a subset of TH17.1 cells co-expressing IL-2 and granulocyte–macrophage colony-stimulating factor (IL-2+ GM-CSF+ TH17.1 cells, P = 0.04). A significant fall in β-cell-targeted (proinsulin-specific) IL-17A-secreting T cells was also seen (P = 0.0003). Although exploratory, our data suggest a role for an activated subset of TH17.1 cells in T1D that can be targeted with minimal adverse effects to reduce C-peptide loss, which requires confirmation in a larger study. (International Standard Randomised Controlled Trial Number Registry: ISRCTN 14274380).
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".