Real-world experience with CDK4/6 inhibitors in the first-line palliative setting for HR+/HER2- advanced breast cancer.
Bibliographic record
Abstract
e13066 Background: CDK4/6 inhibitors paired with aromatase inhibitors (AIs) have redefined the first-line treatment for metastatic breast cancer, as evidenced by several pivotal trials. Although progression-free survival (PFS) has been consistent across these studies, notable differences in overall survival (OS) have been observed. Our study evaluates the real-world efficacy of palbociclib and ribociclib, in combination with AIs, for hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) advanced breast cancer at our institution. Methods: We retrospectively reviewed charts of adult patients with advanced metastatic breast cancer at a single academic center from January 1, 2015, to December 1, 2022. We extracted relevant clinical data to estimate the median PFS and OS associated with palbociclib and ribociclib. Results: Among 75 patients analyzed, the majority were female (98.7%) and postmenopausal (77.3%). Palbociclib was prescribed to 74.7%, while 52.0% presented with de novo stage IV disease. Those on ribociclib were significantly younger (median age 57.6 vs. 67.5 years; p = 0.013) and more likely premenopausal (42.1% vs. 5.4%; p < 0.001). Median PFS for palbociclib was 20.3 months (95% CI: 14.8-46.0), with an OS of 37.2 months (20.3 months to not reached). Median PFS and OS for ribociclib were not reached. The differences in PFS and OS between the drugs were not statistically significant (PFS log-rank p = 0.1; OS log-rank p = 0.2). Conclusions: Our real-world analysis suggests a non-significant trend towards improved PFS and OS for ribociclib over palbociclib when used with AIs for treating HR+/HER2- advanced breast cancer, potentially influenced by the younger age of patients on ribociclib. Further research with larger cohorts and extended follow-up is warranted to substantiate these observations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 source (direct Gemma or distilled Codex), 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".