The Association of Obesity and Sistemic Arterial Hypertension with High-Grade Prostate Cancer: Our Experience
Bibliographic record
Abstract
Introduction: Prostate cancer (PCa) is the first most frequently diagnosed cancer and the second most common cause of cancer death worldwide. We hypothesized that the presence of obesity and systemic arterial hypertension (SAH), separately and combined, would be associated with increased High-grade PCa risk, since the initial diagnosis. Methods: We evaluated, in 133 patients undergoing prostate biopsy at our institution, the relationship between obesity (BMI 30) and SAH (systolic blood pressure 140, diastolic blood pressure 90) with High-grade PCa (Gleason score 7) at initial diagnosis. Men with urological surgery history, steroid therapy, chemotherapy, incomplete data, were excluded. Results:Obesity was significantly associated (OR 2.25, p < 0.05) with High-grade PCa since the initial diagnosis. Particularly, obesity in association with SAH, was significantly linked to aggressive PCa pre-treatment (OR 2.84, p < 0.05). SAH was not associated in our study with aggressive PCa in non-obese men. Conclusions:Obesity and SAH were significantly linked to aggressive PCa, at initial diagnosis, prior to hormonal or surgical therapy. Further larger studies should better clarify this relationship to support these associations and to evaluate future preventive and therapeutic strategies.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".