Antidiabetic agents and cancer outcomes: Are there differences between agents?
Bibliographic record
Abstract
There is substantial evidence of the elevated risk of cancer among individuals with type 2 diabetes. Very little is known, however, about the role that antidiabetic therapies play in this relationship. The objective of this program of research was to examine whether there is a therapeutic risk associated with antidiabetic therapies that increase circulating insulin levels, such as sulfonylureas and exogenous insulin, or a therapeutic benefit associated with antidiabetic therapies that reduce insulin resistance, such as metformin and the glitazones. This objective was achieved through four related population-based cohort studies using the administrative databases from Saskatchewan Health. The first study looked at the effect of the older antidiabetic therapies metformin and sulfonylureas on cancer mortality. The focus of the second study was to explore more closely the effect of metformin and sulfonylurea by using a time-varying Cox regression to define drug exposures. The third study looked more closely at the effect of exogenous insulin therapy and cancer mortality, and the last study focused on the more recently available antidiabetic therapy the glitazones and cancer mortality. We found that individuals with type 2 diabetes exposed to sulfonylurea monotherapy had a significantly increased risk of cancer-related mortality, compared to patients exposed to metformin. We also observed a dose-response gradient with exogenous insulin therapy and cancer mortality, whereby individuals exposed to higher levels of insulin had a higher risk of cancer mortality. In the last study, we found that the newer class of antidiabetic therapies, the glitazones, were associated with a decreased risk of cancer mortality. These finding add further support that antidiabetic therapies may play a moderating role in the relationship between type 2 diabetes and cancer outcomes. However, it is unclear whether the increased risk of cancer mortality we observed was related to a toxic effect of sulfonylureas and exogenous insulin or a protective effect of metformin and glitazones, or due to some unmeasured effect related to both choice of drug therapy and cancer risk. Future research should incorporate a non-diabetes control cohort for comparison and examine the more proximal outcome measure cancer incidence.
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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 | 0.011 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".