Role of Bone-Modifying Agents in Metastatic Breast Cancer: An American Society of Clinical Oncology–Cancer Care Ontario Focused Guideline Update
Bibliographic record
Abstract
Purpose To update, in collaboration with Cancer Care Ontario (CCO), key recommendations of the American Society of Clinical Oncology (ASCO) guideline on the role of bone-modifying agents (BMAs) in metastatic breast cancer. This focused update addressed the new data on intervals between dosing and the role of BMAs in control of bone pain. Methods A joint ASCO-CCO Update Committee conducted targeted systematic literature reviews to identify relevant studies. Results The Update Committee reviewed three phase III noninferiority trials of dosing intervals, one systematic review and meta-analysis of studies of de-escalation of BMAs, and two randomized trials of BMAs in control of pain secondary to bone metastases. Recommendations Patients with breast cancer who have evidence of bone metastases should be treated with BMAs. Options include denosumab, 120 mg subcutaneously, every 4 weeks; pamidronate, 90 mg intravenously, every 3 to 4 weeks; or zoledronic acid, 4 mg intravenously every 12 weeks or every 3 to 4 weeks. The analgesic effects of BMAs are modest, and they should not be used alone for bone pain. The Update Committee recommends that the current standard of care for supportive care and pain management-analgesia, adjunct therapies, radiotherapy, surgery, systemic anticancer therapy, and referral to supportive care and pain management-be applied. Evidence is insufficient to support the use of one BMA over another. Additional information is available at www.asco.org/breast-cancer-guidelines and www.asco.org/guidelineswiki .
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".