Perceptions of Active Surveillance and Treatment Recommendations for Low-risk Prostate Cancer
Bibliographic record
Abstract
BACKGROUND: With the growing concerns about overtreatment in prostate cancer, the extent to which radiation oncologists and urologists perceive active surveillance (AS) as effective and recommend it to patients are unknown. OBJECTIVE: To assess opinions of radiation oncologists and urologists about their perceptions of AS and treatment recommendations for low-risk prostate cancer. RESEARCH DESIGN: National survey of specialists. PARTICIPANTS: Radiation oncologists and urologists practicing in the United States. MEASURES: A total of 1366 respondents were asked whether AS was effective and whether it was underused nationally, whether their patients were interested in AS, and treatment recommendations for low-risk prostate cancer. Pearson's χ test and multivariate logistic regression were used to test for differences in physician perceptions on AS and treatment recommendations. RESULTS: Overall, 717 (52.5%) of physicians completed the survey with minimal differences between specialties (P=0.92). Although most physicians reported that AS is effective (71.9%) and underused in the United States (80.0%), 71.0% stated that their patients were not interested in AS. For low-risk prostate cancer, more physicians recommended radical prostatectomy (44.9%) or brachytherapy (35.4%); fewer endorsed AS (22.1%). On multivariable analysis, urologists were more likely to recommend surgery [odds ratio (OR): 4.19; P<0.001] and AS (OR: 2.55; P<0.001), but less likely to recommend brachytherapy (OR: 0.13; P<0.001) and external beam radiation therapy (OR: 0.11; P<0.001) compared with radiation oncologists. CONCLUSIONS AND RELEVANCE: Most prostate cancer specialists in the United States believe AS effective and underused for low-risk prostate cancer, yet continue to recommend the primary treatments their specialties deliver.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".