Impact of Diabetes and Metformin on Cardiovascular Outcomes in Prostate Cancer Patients Aged 66 and Older: The Role of Social Determinants of Health and Racial Disparities †
Bibliographic record
Abstract
Background: This study evaluated the impact of diabetes mellitus (DM) and its treatments on cardiovascular outcomes in prostate cancer (PC) patients aged 66 years and older, with or without androgen deprivation therapy (ADT) exposure. Methods: Using the SEER-Medicare database (2009–2017), two cohorts were created: Cohort 1 included all PC patients enrolled in Medicare Parts A and B; Cohort 2 was a subset of Cohort 1 receiving ADT and enrolled in Medicare Part D. Exposures were DM and DM medications. Outcomes included cardiovascular events (CVEs), cardiovascular mortality (CVm), PC-specific mortality (PCsm), and all-cause mortality, analyzed using multivariable Fine-Gray and Cox models. Results: Cohort 1 included 150,647 PC patients (32% with DM, median age 72). DM was associated with higher risk of CVE (subdistribution hazard ratio [sHR] 1.20, 95% CI 1.17–1.22), CVm (sHR 1.35, 1.28–1.43), and all-cause mortality (adjusted HR [aHR] 1.22, 1.19–1.26) (all p < 0.001). Non-Hispanic Blacks (NHBs) and patients from lower socioeconomic (SES) and education areas experienced comparable or worse outcomes. In Cohort 2 (n = 14,938), DM patients on non-metformin therapies had higher all-cause mortality (aHR 1.33, 1.11–1.25; p = 0.002) than those on metformin, particularly in NHB and low education groups. Sensitivity analyses with follow-up limited to two years showed consistent results as overall. Conclusions: Diabetic PC patients, especially NHB, lower SES and lower education subgroups, were associated with worse cardiovascular and all-cause mortality outcomes. Metformin may be associated with better outcomes in these populations, warranting further research on the disparities in PC and diabetes, and cardioprotective effects of DM medications across different subpopulations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".