Sex differences in obesity related cancer incidence in relation to type 2 diabetes diagnosis (ZODIAC-49)
Bibliographic record
Abstract
BACKGROUND: Diabetes and obesity seem to be partly overlapping risk factors for the development of obesity-related cancer (mainly breast, prostate and colorectal cancer) in patients with type 2 diabetes (T2DM). In the general population, women have a lower risk for obesity-related cancer compared to men. Previous studies involving cardiovascular disease have shown that T2DM eliminates a female advantage of lower CVD risk in the general population compared to men. It is unclear whether the same could be true for obesity-related cancer. This study aimed to this investigate obesity-related cancer incidence in women and men known with T2DM as compared to the Dutch general population. METHODS: This study included 69,583 patients with T2DM selected from a prospective primary care cohort, which was linked to the Dutch National Cancer Registry to obtain cancer specific data. Obesity-related cancers included liver, kidney, colorectal, gallbladder, pancreas, ovarian, endometrial, advanced prostate cancer, post-menopausal breast cancer and oesophageal adenocarcinoma. Primary outcome was sex-stratified, age and year of cancer diagnosis adjusted standardized incidence ratios (SIRs) for three time periods: 5 years before, the year after diagnosis and the next 4 years after T2DM diagnosis. The Dutch general population was used as reference group. RESULTS: Women with T2DM were at an increased risk for obesity-related cancer compared to women in the general population already 5 years before diabetes diagnosis (SIR 1.77; 95%CI: 1.63-1.91). In both men and women, there was a peak in obesity-related cancer incidence following diabetes diagnosis (SIR: 1.38; 95%CI 1.11-1.64 and SIR: 2.21; 95%CI 1.94-2.30, respectively). From the second to the fifth year after diabetes diagnosis the obesity-related cancer incidence was higher in women compared to women in the general population (SIR: 2.12; 95%CI 1.94-2.30). CONCLUSIONS: Women with T2DM seem to have a substantially higher obesity-related cancer risk. As opposed to men, in women this risk was already increased years before diabetes diagnosis. These results could imply that a relative advantage of women in the general population with regard to cancer risk is lost in women with T2DM.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.003 | 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".