The effect of warfarin on the risk of prostate cancer
Bibliographic record
Abstract
14524 Background: The anticancer activity of oral anticoagulants has been a matter of debate for several years. Recent evidence suggests that prolonged treatment with warfarin may be associated with a reduced incidence of newly diagnosed urogenital cancer during long-term follow-up of patients with venous thromboembolism. The aim of this study was to assess whether exposure to warfarin was associated with reduced risk of prostate cancer in a large population-based cohort. Methods: We conducted a matched case-control study nested within the population of beneficiaries of the Saskatchewan Prescription Drug Plan aged 50 years and older from 1981–2002 with no history of cancer since 1967. New cases of prostate cancer diagnosed between 1981 and 2002 were identified using the linked Saskatchewan Cancer Agency registry. Six controls per case matched on age, gender, and sampling time were randomly selected. The cumulative exposure to warfarin in the five years preceding the cancer diagnosis was assessed. Prescription counts were used to define warfarin exposure. Exposure in the year immediately preceding the cancer diagnosis was excluded to control for detection bias. Conditional logistic regression analysis was used to assess confounding by other drugs such as nonsteroidal anti-inflammatory medications. Results: Among 11502 cases and 69012 controls, 7.4% of cases and 7.1% of controls had a history of any warfarin use. Compared to men who had never used warfarin, adjusted odds ratio (OR) for prostate cancer among ever-users in the 5 year period was 0.94 (95% confidence interval (CI), 0.86–1.03). In those who accumulated 1, 2, 3 and 4 years of warfarin use, the adjusted ORs were 1.01 (95% CI, 0.89–1.16), 1.00 (95% CI, 0.82–1.23), 0.81 (95% CI, 0.60–1.09), and 0.80 (95% CI, 0.65–0.99), respectively (p-trend=0.03). Conclusion: Our results suggest that cumulative use of warfarin of at least 4 years may be associated with a reduced risk of prostate cancer. However, confounding by other determinants of prostate cancer associated with warfarin use is possible. Nonetheless, confirmation of these findings by prospective studies may provide the evidence necessary to consider the use of warfarin in prostate cancer prevention. No significant financial relationships to disclose.
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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 | 0.007 |
| 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".