Bibliographic record
Abstract
PURPOSE OF REVIEW: Although neoadjuvant therapy (NAT) has become a popular approach in the systemic management of breast cancer, several important clinical questions remain unanswered. In this article, we review the literature pertaining to these questions and discuss the management strategies based on our findings. RECENT FINDINGS: Currently, the optimal duration of NAT is unclear. At this time, there is no compelling data to support the extension of traditional neoadjuvant chemotherapy regimens. In patients with triple-negative breast cancer, pathologic complete response may be prognostic and the appropriate use of neoadjuvant chemotherapy is crucial to achieve improved survival. In human epidermal growth factor receptor 2 (HER2)-positive disease, it is reasonable to consider dual blockade with trastuzumab and pertuzumab in combination with a taxane in the neoadjuvant setting. Finally, there is currently no evidence to support the use of further adjuvant chemotherapy in those patients with residual disease after NAT. SUMMARY: There remain many unanswered questions with the use of neoadjuvant chemotherapy in breast cancer, and further randomized clinical trials are needed. The results of these trials will permit the clinicians to develop 'personalized' treatment approaches, thus giving women the best chance of survival.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".