CANDIED: A Pan-Canadian Cohort of Immune Checkpoint Inhibitor-Induced Insulin-Dependent Diabetes Mellitus
Bibliographic record
Abstract
Immune checkpoint inhibitor (ICI)-induced insulin-dependent diabetes mellitus (IDDM) is a rare but potentially fatal immune-related adverse event (irAE). In this multicentre retrospective cohort study, we describe the characteristics of ICI-induced IDDM in patients treated across five Canadian cancer centres, as well as their tumor response rates and survival. In 34 patients identified, 25 (74%) were male and 19 (56%) had melanoma. All patients received anti-programed death 1 (anti-PD1) or anti-programmed death ligand-1 (anti-PD-L1)-based therapy. From ICI initiation, median time to onset of IDDM was 2.4 months (95% CI 1.1–3.6). Patients treated with anti-PD1/PD-L1 in combination with an anti-cytotoxic T lymphocyte antigen 4 antibody developed IDDM earlier compared with patients on monotherapy (1.4 vs. 3.9 months, p = 0.05). Diabetic ketoacidosis occurred in 21 (62%) patients. Amongst 30 patients evaluable for response, 10 (33%) had a complete response and another 10 (33%) had a partial response. Median overall survival was not reached (95% CI NE; median follow-up 31.7 months). All patients remained insulin-dependent at the end of follow-up. We observed that ICI-induced IDDM is an irreversible irAE and may be associated with a high response rate and prolonged survival.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".