Combining endocrine agents with chemotherapy: Which patients and what sequence?
Bibliographic record
Abstract
In metastatic breast cancer, attempts to improve response to therapy by combining hormones and chemotherapy began in the 1970s. Since then, several randomized trials comparing single-agent hormone therapy or chemotherapy versus sequential combinations of these agents have been performed. In the majority of those studies, an increased response rate or an increased time to progression was observed when chemotherapy was added to hormone therapy or when hormone therapy was added to chemotherapy. However, in few of those trials was the increased response rate statistically significant or the response duration significantly prolonged, and no studies reported an improvement in overall survival. Furthermore, the studies did not make the correct comparisons of 1) hormone therapy alone followed by chemotherapy alone versus hormone therapy and chemotherapy given concurrently or 2) chemotherapy alone followed by hormone therapy versus concurrent chemotherapy and hormone therapy. To truly be advantageous, concurrent treatment should provide an increased response rate and response duration compared with the added or overall response rate and response duration of the same agents used sequentially. In the adjuvant setting, the timing and sequencing of hormone therapy and chemotherapy also has not been studied well. However, it has been accepted widely that adjuvant chemotherapy should be completed before beginning tamoxifen. No trials examining concurrent versus sequential treatment have been performed with hormone therapy and chemotherapy in the premenopausal setting or with aromatase inhibitors and chemotherapy in postmenopausal women. Considering the demonstrated importance of the timing of chemotherapy and tamoxifen in the postmenopausal setting, these questions should be explored further.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".