Adjuvant Endocrine Therapy for Early Breast Cancer: A Systematic Review of the Evidence for the 2014 Cancer Care Ontario Systemic Therapy Guideline
Bibliographic record
Abstract
BACKGROUND: Cancer Care Ontario's Program in Evidence-Based Care (pebc) recently created an evidence-based consensus guideline on the systemic treatment of early breast cancer. The evidence for the guideline was compiled using a systematic review to answer the question "What is the optimal systemic therapy for patients with early-stage, operable breast cancer, when patient and disease factors are considered?" The question was addressed in three parts: cytotoxic chemotherapy, endocrine treatment, and her2 (human epidermal growth factor receptor 2)-targeted therapy. METHODS: For the systematic review, the literature in the medline and embase databases was searched for the period January 2008 to May 2014. The Standards and Guidelines Evidence directory of cancer guidelines and the Web sites of major oncology guideline organizations were also searched. The basic search terms were "breast cancer" and "systemic therapy" (chemotherapy, endocrine therapy, targeted agents, ovarian suppression), and results were limited to randomized controlled trials (rcts), guidelines, systematic reviews, and meta-analyses. RESULTS: Several hundred documents that met the inclusion criteria were retrieved. Meta-analyses from the Early Breast Cancer Trialists' Collaborative Group encompassed many of the rcts found. Several additional studies that met the inclusion criteria were retained, as were other guidelines and systematic reviews. SUMMARY: The results of the systematic review constitute a comprehensive compilation of high-level evidence, which was the basis for the 2014 pebc guideline on systemic therapy for early breast cancer. The review of the evidence for systemic endocrine therapy (adjuvant tamoxifen, aromatase inhibitors, and ovarian ablation and suppression) is presented here; the evidence for chemotherapy and her2-targeted treatment-and the final clinical practice recommendations-are presented separately in this supplement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".