Active Surveillance for the Management of Localized Prostate Cancer (Cancer Care Ontario Guideline): American Society of Clinical Oncology Clinical Practice Guideline Endorsement
Bibliographic record
Abstract
PURPOSE: To endorse Cancer Care Ontario's guideline on Active Surveillance for the Management of Localized Prostate Cancer. The American Society of Clinical Oncology (ASCO) has a policy and set of procedures for endorsing clinical practice guidelines developed by other professional organizations. METHODS: The Active Surveillance for the Management of Localized Prostate Cancer guideline was reviewed for developmental rigor by methodologists. The ASCO Endorsement Panel then reviewed the content and the recommendations. RESULTS: The ASCO Endorsement Panel determined that the recommendations from the Active Surveillance for the Management of Localized Prostate Cancer guideline, published in May 2015, are clear, thorough, and based upon the most relevant scientific evidence. ASCO endorsed the Active Surveillance for the Management of Localized Prostate Cancer guideline with added qualifying statements. The Cancer Care Ontario recommendation regarding 5-alpha reductase inhibitors was not endorsed by the ASCO panel. RECOMMENDATIONS: For most patients with low-risk (Gleason score ≤ 6) localized prostate cancer, active surveillance is the recommended disease management strategy. Factors including younger age, prostate cancer volume, patient preference, and ethnicity should be taken into account when making management decisions. Select patients with low-volume, intermediate-risk (Gleason 3 + 4 = 7) prostate cancer may be offered active surveillance. Active surveillance protocols should include prostate-specific antigen testing, digital rectal examinations, and serial prostate biopsies. Ancillary radiologic and genomic tests are investigational but may have a role in patients with discordant clinical and/or pathologic findings. Patients who are reclassified to a higher-risk category (Gleason score ≥ 7) or who have significant increases in tumor volume on subsequent biopsies should be offered active therapy.
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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 | 0.011 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".