Endocrine therapy and related issues in hormone receptor-positive early breast cancer: a roundtable discussion by the breast cancer therapy expert group (BCTEG)
Bibliographic record
Abstract
PURPOSE: Management of breast cancer is a rapidly evolving field, and, although evidence-based guidelines are available for clinicians to provide direction on critical issues in patient care, clinicians often left to address these issues in the context of community practice situations with their patients. These include the patient's comorbid conditions, actual versus perceived benefit of treatments, patient's compliance as well as financial/reimbursement issues, and long-term tolerability of therapy. METHODS: A meeting of global oncology experts was convened in January 2017 with the belief that there is a gap in clinical practice guidance on several fundamental issues in breast cancer care, particularly in the community setting, where oncologists may encounter multiple tumor types. The goal was to discuss some of the most important questions in this area and provide some guidance for practicing oncologists. RESULTS: Topics addressed included risk of contralateral breast cancer recurrence in patients with estrogen receptor-positive early breast cancer who have undergone 5 years of adjuvant endocrine therapy, adverse events associated with endocrine therapy and their management, emergent data on adjuvant bisphosphonate therapy and its apparent benefit in reducing breast cancer recurrence, recent findings of extended adjuvant endocrine therapy trials, and the use of currently available genomic biomarker tests as a means of further informing treatment decisions. CONCLUSIONS: A summary of the discussion on these topics and several 'expert opinion statements' are provided herein in an effort to convey the collective insights of the panel as it relates to current standard 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 | 0.053 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.021 | 0.021 |
| 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".