Newly diagnosed type 2 diabetes may serve as a potential marker for pancreatic cancer
Bibliographic record
Abstract
Pancreatic cancer has an extremely highly case fatality. Diabetes is a well-established strong risk factor for pancreatic cancer. Compared with a nondiabetic population, we previously reported a 15- and 14-fold greater risk for detecting pancreatic cancer during the first year after diagnosing diabetes in adult women and men, respectively, which dropped during the second year to 5.4-fold and 3.5-fold, respectively, and stabilized around 3-fold for the rest of the 11-year follow-up in our historical cohort. The population attributable risk during the 11-year period was 13.3% and 14.1% in prevalent diabetic women and men, respectively. This means that one out of about every 8 patients diagnosed with pancreatic cancer has been previously diagnosed with diabetes. The globally high prevalence of diabetes and the aggravating implications of a delayed pancreatic cancer diagnosis call for newly-onset diabetes to be considered a potential marker for an underlying pancreatic cancer and addressed accordingly.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".