Efficacy of Fulvestrant in Women with Hormone-Resistant Metastatic Breast Cancer (mBC): A Canadian Province Experience
Bibliographic record
Abstract
Introduction: Fulvestrant has demonstrated efficacy in hormone receptor positive (HR+) metastatic breast cancer (mBC), both in first-and second-line settings. In clinical practice, however, fulvestrant has been used as a later-line therapy. This study assessed the efficacy of fulvestrant in women with mBC in early-versus later-line therapy. Methods: This retrospective cohort study assessed Saskatchewan women with HR+ mBC who received fulvestrant between 2003–2019. A multivariate Cox proportional survival analysis was performed. Results: One hundred and eighty-six women with a median age of 63.5 years were identified—178 (95.6%) had hormone-resistant mBC, 57.5% had visceral disease, and 43.0% had received chemotherapy before fulvestrant. 102 (54.8%) women received ≤2-line-therapy, and 84 (45.2%) received ≥3 line-therapy before fulvestrant. The median time to progression (TTP) was 12 months in the early-treatment vs. 6 months in the later-treatment group, p = 0.015. Overall survival (OS) from the start of fulvestrant was 26 months in the early-treatment group vs. 16 months in the later-treatment group, p = 0.067. On multivariate analysis, absence of visceral metastasis, HR: 0.70 (0.50–0.99), was significantly correlated with better TTP, whereas post-fulvestrant chemotherapy, HR: 0.32 (0.23–0.47), clinical benefit from fulvestrant, HR: 0.44 (0.30–0.65), and absence of visceral metastasis, HR: 0.70 (0.50–0.97), were correlated with better OS. Conclusions: Fulvestrant has demonstrated efficacy as both early-and later-line therapy in hormone-resistant mBC. Our results show that women with clinical benefit from fulvestrant, who received post-fulvestrant chemotherapy, or had non-visceral disease, had better survival.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".