Recommendations by Canadian urologists and radiation oncologists for the treatment of clinically localized prostate cancer
Bibliographic record
Abstract
OBJECTIVE: Previous work has shown that urologists and radiation oncologists prefer the treatment that they themselves deliver when treating clinically localized prostate cancer. Our objective was to determine whether Canadian radiation oncologists and urologists have similar biases in favour of the treatments that they themselves deliver for localized prostate cancer. METHODS: We developed a survey to poll the beliefs that Canadian radiation oncologists and urologists held toward prostate specific antigen (PSA) screening, survival benefits of treatment, recommendations for treatment of prostate cancer and the likelihood of side effects with each therapy. RESULTS: Urologists were more likely to recommend routine PSA screening for men up to age 70 (p < 0.001), while radiation oncologists were more likely to recommend PSA screening for men over age 80 (p < 0.04). More urologists felt that there was "definitely" a survival advantage with radical prostatectomy (RP) (60% v. 21%, p < 0.001). More radiation oncologists recommend external beam radiation therapy (EBRT) (p < 0.01) or brachytherapy (p < 0.03) to treat low-risk prostate cancer. More urologists than radiation oncologists recommend RP for intermediate-risk patients (98% v. 70%, p < 0.001). CONCLUSION: Most Canadian urologists and radiation oncologists recommend routine PSA screening for men aged 50 to 70. A significant preference was detected among both urologists and radiation oncologists for the treatment that they themselves deliver. While both urologists and radiation oncologists recommend prostatectomy for the treatment of low-risk localized prostate cancer, urologists are significantly less likely to recommend EBRT. Conversely, when patients present with intermediate-risk prostate cancer, radiation oncologists were significantly less likely than urologists to recommend a prostatectomy.
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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 | 0.006 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".