Clinical Practice Guidelines in Breast Cancer
Bibliographic record
Abstract
Background: A number of clinical practice guidelines (cpgs) concerning breast cancer (bca) screening and management are available. Here, we review the strengths and weaknesses of cpgs from various professional organizations and consensus groups with respect to their methodologic quality, recommendations, and implementability. Methods: Guidelines from four groups were reviewed with respect to two clinical scenarios: adjuvant ovarian function suppression (ofs) in premenopausal women with early-stage estrogen receptor-positive bca, and use of sentinel lymph node biopsy (slnb) after neoadjuvant chemotherapy (nac) for locally advanced bca. Guidelines from the American Society of Clinical Oncology (asco); Cancer Care Ontario's Program in Evidence Based Care (cco's pebc); the U.S. National Comprehensive Cancer Network (nccn); and the St. Gallen International Breast Cancer Consensus Conference were reviewed by two independent assessors. Guideline methodology and applicability were evaluated using the agree ii tool. Results: The quality of the cpgs was greatest for the guidelines developed by asco and cco's pebc. The nccn and St. Gallen guidelines were found to have lower scores for methodologic rigour. All guidelines scored poorly for applicability. The recommendations for ofs were similar in three guidelines. Recommendations by the various organizations for the use of slnb after nac were contradictory. Conclusions: Our review demonstrated that cpgs can be heterogeneous in methodologic quality. Low-quality cpg implementation strategies contribute to low uptake of, and adherence to, bca cpgs. Further research examining the barriers to recommendations-such as intrinsic guideline characteristics and the needs of end users-is required. The use of bca cpgs can improve the knowledge-to-practice gap and patient outcomes.
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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 | 0.080 | 0.281 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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".