Management of Ductal Carcinoma In Situ: An Ontario Health (Cancer Care Ontario) Clinical Practice Guideline
Bibliographic record
Abstract
(1) Background: To make recommendations on the most effective therapy options for Ductal Carcinoma of the Breast (DCIS) patients; (2) Methods: MEDLINE, EMBASE, Cochrane Library, PROSPERO databases, and main relevant guideline websites were searched. Draft versions of the guideline went through formal internal and external reviews, with a final approval by the Program in Evidence Based Care and the DCIS Expert Panel. The Grading of Recommendations, Assessment, Development, and Evaluation approach was followed; (3) Results: Based on the current evidence from the systematic review and this guideline authors' clinical opinions, initial draft recommendations were developed to improve the management of patients with DCIS. After a comprehensive internal and external review process, ten recommendations and 27 qualifying statements were eventually made. This guideline includes recommendations for the primary treatment of DCIS with surgical treatment and/or radiation therapy and the management of DCIS after primary treatment for patients with DCIS, including DCIS with microinvasion (<1 mm through the duct); (4) Conclusions: The current guideline was created after a systematic review and a comprehensive internal and external review process. We believe this guideline provides valuable insights that will be useful in clinical decision making for health providers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".