Patterns of Care and Treatment Trends for Canadian Men with Localized Low-Risk Prostate Cancer: An Analysis of Provincial Cancer Registry Data
Bibliographic record
Abstract
BACKGROUND: Many prostate cancers (pcas) are indolent and, if left untreated, are unlikely to cause death or morbidity in a man's lifetime. As a result of testing for prostate-specific antigen, more such cases are being identified, leading to concerns about "overdiagnosis" and consequent overtreatment of pca. To mitigate the risks associated with overtreatment (that is, invasive therapies that might cause harm to the patient without tangible benefit), approaches such as active surveillance are now preferred for many men with low-risk localized pca (specifically, T1/2a, prostate-specific antigen ≤ 10 ng/mL, and Gleason score ≤ 6). Here, we report on patterns of care and treatment trends for men with localized low-risk pca. RESULTS: The provinces varied substantially with respect to the types of primary treatment received by men with localized low-risk pca. From 2010 to 2013, many men had no record of surgical or radiation treatment within 1 year of diagnosis-a proxy for active surveillance; the proportion ranged from 53.3% in Nova Scotia to 80.8% in New Brunswick. Among men who did receive primary treatment, the use of radical prostatectomy ranged from 12.0% in New Brunswick to 35.9% in Nova Scotia. The use of radiation therapy (external-beam radiation therapy or brachytherapy) ranged from 4.1% in Newfoundland and Labrador to 17.6% in Alberta. Treatment trends over time suggest an increase in the use of active surveillance. The proportion of men with low-risk pca and no record of surgical or radiation treatment rose to 69.9% in 2013 from 46.1% in 2010 for all provinces combined. CONCLUSIONS: The provinces varied substantially with respect to patterns of care for localized low-risk pca. Treatment trends over time suggest an increasing use of active surveillance. Those findings can further the discussion about the complex care associated with pca and identify opportunities for improvement in clinical practice.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.017 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".