Sharing the responsibility of prostate cancer risk reduction
Bibliographic record
Abstract
Despite improvements in the detection and management of prostate cancer in recent years, the clinical and financial burden of this disease continues to grow. Prostate cancer remains the most frequently diagnosed cancer in men and a leading cause of cancer death worldwide, yet there is still ongoing uncertainty surrounding the value of early screening. Intuitively, earlier detection should result in earlier and more effective treatment of prostate cancer; however, this has yet to be supported by the evidence, emphasized by the recent conflicting reports on screening from the Prostate, Lung, Colorectal and Ovarian (PLCO) and European trials. Still, as with any cancer, a diagnosis of prostate cancer carries a significant burden, and exploring the cost-benefit of risk reduction remains worthwhile. With primary care physicians assuming an increasingly greater role in the management of benign prostatic hyperplasia (BPH) and lower urinary tract symptoms in general, urologists and primary care physicians are moving toward a more cooperative approach to the diagnosis and management of these conditions. This cooperation results in greater access to care and improved outcomes, as well as a reduced need for unnecessary surgical consultations. This supplement to the Canadian Urological Association Journal grew out of a series of meetings of the Prostate Cancer Collaborative Network (PCCN) – a multidisciplinary group of Canadian physicians dedicated to advancing the management of prostate cancer in Canada. Supported by an unrestricted educational grant from GlaxoSmithKline, the PCCN convened to explore new approaches to prostate cancer risk reduction. Along with their colleagues in the PCCN, Dr. Simon Tanguay discusses the shared roles of urology and primary care in the diagnosis and management of BPH, Dr. Yves Fradet provides a Canadian perspective on the burden of prostate disease, Dr. Larry Goldenberg reviews the role of 5-alpha reductase in prostate disease and Dr. Laurence Klotz addresses recent issues with Gleason grading. We hope this series of articles provides the reader with a comprehensive review of the current issues facing urologists, oncologists, radiation oncologists and primary care physicians involved in the management of prostate disease.
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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 | 0.024 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.007 | 0.015 |
| Insufficient payload (model declined to judge) | 0.078 | 0.041 |
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".