Selection of Optimal Adjuvant Chemotherapy and Targeted Therapy for Early Breast Cancer: ASCO Guideline Update
Bibliographic record
Abstract
PURPOSE The aim of this work is to update key recommendations of the ASCO guideline adaptation of the Cancer Care Ontario guideline on the selection of optimal adjuvant chemotherapy regimens for early breast cancer and adjuvant targeted therapy for breast cancer. METHODS An Expert Panel conducted a targeted systematic literature review guided by a signals approach to identify new, potentially practice-changing data that might translate into revised guideline recommendations. RESULTS The Expert Panel reviewed abstracts from the literature review and identified one article for inclusion that reported results of the phase III, open-label KATHERINE trial. In the KATHERINE trial, patients with stage I to III human epidermal growth factor receptor 2 (HER2)–positive breast cancer with residual invasive disease in the breast or axilla after completing neoadjuvant chemotherapy and HER2-targeted therapy were allocated to adjuvant trastuzumab emtansine (T-DM1; n = 743) or to trastuzumab (n = 743). Invasive disease–free survival was significantly higher in the T-DM1 group than in the trastuzumab arm (hazard ratio, 0.50; 95% CI, 0.39 to 0.64; P < .001), and risk of distant recurrence was lower in patients who received T-DM1 than in patients who received trastuzumab (hazard ratio, 0.60; 95% CI, 0.45 to 0.79). Grade 3 or higher adverse events occurred in 190 patients (25.7%) who received T-DM1 and in 111 patients (15.4%) who received trastuzumab. RECOMMENDATIONS Patients with HER2-positive breast cancer with pathologic invasive residual disease at surgery after standard preoperative chemotherapy and HER2-targeted therapy should be offered 14 cycles of adjuvant T-DM1, unless there is disease recurrence or unmanageable toxicity. Clinicians may offer any of the available and approved formulations of trastuzumab, including trastuzumab, trastuzumab and hyaluronidase-oysk, and available biosimilars. Additional information can be found at www.asco.org/breast-cancer-guidelines
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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 | 0.033 | 0.079 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".