Management of early-stage breast cancer: Are we headed in the right direction?
Bibliographic record
Abstract
284 Background: The understanding of breast cancer (BC) as a heterogeneous disease consisting of distinct subtypes based on variation in expression of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) has led to more personalized treatment. We postulated that with increased adoption of chemotherapy and targeted therapy for HER2 positive patients, the outcomes of ER/PR+, HER2- and of HER2+ subtypes of breast cancer would be similar. Methods: A chart review was performed of female patients >18 years old seen by a medical oncologist at an academic cancer centre in Toronto, Canada, between January 1, 2005 and December 31, 2006, for stage I-III invasive breast cancer. Clinical features, 5-year overall (OS) and relapse-free survival (RFS) of three BC subtypes were compared: ER/PR+, HER2- (hormone receptor positive, HR), HER2+ (HER2), and ER/PR-, HER2- (triple negative, TN). Results: Of 870 patient charts reviewed, 525 were analysed. There were 341 HR, 101 HER2 and 83 TN patients. TN patients were younger (p<0.001), and had higher stage (p<0.001) and higher histological grade tumors (p<0.001). The 5-year RFS and OS were: HR: 88.2% and 96.6%, HER2: 76.7% and 92%, TN: 79.8% and 83.9%. Chemotherapy was used in 41.1%, 84.2% and 83.1% of HR, HER2 and TN patients. Anthracycline plus taxane regimens were used in 48.6%, 52.9% and 68.1% of HR, HER2 and TN patients, respectively. Among HER2 patients, only 74.3% received trastuzumab. The 5-year RFS and OS for HER2 patients who received trastuzumab were 79.9% and 91.8%, and for those who did not: 69% and 91.6%. Conclusions: HR+ patients have an excellent outcome. Despite significant improvement in outcomes of HER2+ patients with early stage breast cancer, they still remain at higher risk of recurrence along with TN patients. Trastuzumab was underutilized among HER2+ patients in this cohort, which may have contributed to decreased 5 year RFS. Ongoing prospective follow up of early BC outcomes by breast cancer subtypes is important.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".