Filling the Gap after CDK4/6 Inhibitors: Novel Endocrine and Biologic Treatment Options for Metastatic Hormone Receptor Positive Breast Cancer
Bibliographic record
Abstract
The rise of cyclin-dependent kinase (CDK)4/6 inhibitors has rapidly reshaped treatment algorithms for hormone receptor (HR)-positive metastatic breast cancer, with endocrine treatment (ET) plus a CDK4/6-inhibitor currently representing the standard of care in the first line setting. However, treatment selection for those patients experiencing progression while on ET + CDK4/6-inhibitors remains challenging due to the suboptimal activity or significant toxicities of the currently available options. There is also a paucity of data regarding the efficacy of older regimens, such as everolimus + exemestane, post-CDK4/6 inhibition. In this setting of high unmet need, several clinical trials of novel drugs have recently reported encouraging results: the addition of the AKT-inhibitor capivasertib to fulvestrant demonstrated a significant improvement in progression-free survival (PFS); the oral selective estrogen receptor degrader (SERD) elacestrant prolonged PFS compared to traditional ET in a phase 3 trial, particularly among patients with detectable ESR1 mutations; finally, PARP inhibitors are available treatment options for patients with pathogenic BRCA1/2 germline mutations. Overall, a plethora of novel endocrine and biologic treatment options are finally filling the gap between first-line ET and later line chemotherapy. In this review article, we recapitulate the activity of these novel treatment options and their potential role in future treatment algorithms.
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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".