Role of Herceptin<sup>®</sup> in Primary Breast Cancer: Views from North America and Europe
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Current therapeutic strategies for primary breast cancer aim to provide improvements in outcome with minimal toxicity to the patient. However, annual relapse rates of up to 12 to 13% during the first 10 years after treatment are seen, and although toxicity has been reduced, it remains a problem in a patient population that is largely asymptomatic. Thus, there is a clear need for more effective therapies. Amplification/overexpression of the human epidermal growth factor receptor-2 (HER2) is an early event in the development of a significant proportion of breast tumors. This abnormality has been shown to have a detrimental effect on prognosis, may predict the outcome of therapies such as tamoxifen and anthracyclines, and provides a target for the novel therapy, Herceptin. Herceptin is effective and well tolerated in the metastatic setting, making it an ideal candidate for use in adjuvant breast cancer therapy. This has led to the design of a number of trials that aim to provide conclusive evidence as rapidly as possible that Herceptin is well tolerated and effective in the adjuvant setting while also addressing the question of which regimen provides greatest benefit. This review describes these trials and explains how differences in practice between North America and Europe have influenced trial design.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it