First-Line Treatment Options for Patients with HER-2–Negative Metastatic Breast Cancer: The Impact of Modern Adjuvant Chemotherapy
Bibliographic record
Abstract
The management of early breast cancer has evolved rapidly in recent years. Consequently, the range of first-line treatment options for metastatic breast cancer (MBC) is becoming increasingly complicated and therapy depends on a complex interaction of tumor, patient, and physician variables. Arguably one of the most important factors determining choice of first-line chemotherapy is prior adjuvant therapy. We have reviewed data from large, randomized clinical trials to identify the most effective regimens and help clinicians to select first-line treatment based on previous adjuvant therapy. In this review we provide recommendations on the most appropriate first-line therapy according to the type of previous adjuvant therapy. With such a wide array of treatment options available, none is likely to become the gold-standard first-line treatment for MBC. Furthermore, as increasing emphasis is placed on the quality as well as the duration of survival after development of MBC, treatment decisions should take into account tumor characteristics, toxicity, convenience, potential impact on quality of life, and patient preference, in addition to robust efficacy data.
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) | 0.002 | 0.001 |
| 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".