Metformin use and all-cause and prostate-cancer-specific mortality among diabetic men.
Bibliographic record
Abstract
5007 Background: To evaluate the association between cumulative duration of metformin use after prostate cancer diagnosis and all-cause and prostate cancer-specific mortality among diabetic patients. Methods: We used a population-based retrospective cohort design. Data were obtained from several Ontario health care administrative databases. Within a cohort of men over the age of 66 with incident diabetes who subsequently developed prostate cancer, we examined the effect of duration of anti-diabetic medication exposure, after prostate cancer diagnosis, on all-cause and prostate cancer-specific mortality. Crude and adjusted hazard ratios were calculated using a time-varying Cox proportional hazard model to estimate effects. Results: The cohort consisted of 3,837 patients. Median age (interquartile range IQR) at diagnosis of prostate cancer was 75 (72-79) years. During a median (IQR) follow up of 4.64 (2.7-7.1) years, 1,343 (35%) died, and 291 patients died of prostate cancer (7.6%). Cumulative duration of metformin treatment, after prostate cancer diagnosis, was associated with a significant decreased risk of prostate cancer-specific and all-cause mortality in a dose-dependent fashion. The adjusted hazard ratio, for prostate cancer-specific mortality was 0.76 (95% confidence interval, 0.64-0.89) for each additional six months of metformin use. The association with all-cause mortality was also significant but declined over-time from a HR of 0.76 in the first 6 months to 0.93 between 24-30 months. There was no relationship between cumulative use of other anti-diabetic drugs and either outcome. Conclusions: Increased cumulative duration of metformin exposure after prostate cancer diagnosis was associated with decreases in both all-cause and prostate-cancer-specific mortality among diabetic men.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".