An Overview of Long-Acting GnRH Agonists in Premenopausal Breast Cancer Patients: Survivorship Challenges and Management
Bibliographic record
Abstract
Managing breast cancer in premenopausal women poses unique challenges due to its considerable effect on both morbidity and mortality. Goserelin, a gonadotropin-releasing hormone agonist, has emerged among the various modalities as a preferred option for ovarian function suppression, owing to its efficacy in reducing ovarian estrogen production in premenopausal women with hormone receptor-positive breast cancer. Recent studies have affirmed the efficacy and safety of long-acting (LA) goserelin 10.8 mg every 12 weeks, offering comparable outcomes to monthly injections. This flexibility enables personalized treatment approaches, potentially enhancing patient satisfaction. Off-label utilization of goserelin LA surged during the coronavirus disease pandemic, prompting initiatives to broaden its use for breast cancer treatment. Switching to goserelin LA can streamline treatment, boost adherence, and optimize resource utilization. With the recent approval of goserelin 10.8 mg LA by Health Canada on 6 May 2024, for use in breast cancer, Canada is the latest to join over 60 countries worldwide to expand the accepted indications for goserelin LA and ensure its availability to potentially enhance healthcare delivery, patient care, and breast cancer outcomes. Goserelin LA offers premenopausal patients a means to more effectively manage the constraints imposed by breast cancer treatment and its impact on survivorship.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".