Mortality After Incident Cancer in People With and Without Type 2 Diabetes
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Bibliographic record
Abstract
OBJECTIVE: Type 2 diabetes is associated with an increased risk of several types of cancer and with reduced survival after cancer diagnosis. We examined the hypotheses that survival after a diagnosis of solid-tumor cancer is reduced in those with diabetes when compared with those without diabetes, and that treatment with metformin influences survival after cancer diagnosis. RESEARCH DESIGN AND METHODS: Data were obtained from >350 U.K. primary care practices in a retrospective cohort study. All individuals with or without diabetes who developed a first tumor after January 1990 were identified and records were followed to December 2009. Diabetes was further stratified by treatment regimen. Cox proportional hazards models were used to compare all-cause mortality from all cancers and from specific cancers. RESULTS: Of 112,408 eligible individuals, 8,392 (7.5%) had type 2 diabetes. Cancer mortality was increased in those with diabetes, compared with those without (hazard ratio 1.09 [95% CI 1.06-1.13]). Mortality was increased in those with breast (1.32 [1.17-1.49]) and prostate cancer (1.19 [1.08-1.31]) but decreased in lung cancer (0.84 [0.77-0.92]). When analyzed by diabetes therapy, mortality was increased relative to nondiabetes in those on monotherapy with sulfonylureas (1.13 [1.05-1.21]) or insulin (1.13 [1.01-1.27]) but reduced in those on metformin monotherapy (0.85 [0.78-0.93]). CONCLUSIONS: This study confirmed that type 2 diabetes was associated with poorer prognosis after incident cancer, but that the association varied according to diabetes therapy and cancer site. Metformin was associated with survival benefit both in comparison with other treatments for diabetes and in comparison with a nondiabetic population.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it