Oophorectomy in Premenopausal Patients with Estrogen Receptor-Positive Breast Cancer: New Insights into Long-Term Effects
Bibliographic record
Abstract
Approximately 80% of breast cancers are estrogen receptor-positive (ER+), and 68-80% of those occur in premenopausal or perimenopausal women. Since the introduction of tamoxifen for adjuvant endocrine therapy in women with non-metastatic ER+ breast cancer, subsequent trials have demonstrated an oncologic benefit with the addition of ovarian function suppression (OFS) to adjuvant endocrine therapy. Subsequently, therapies to either suppress or ablate ovarian function may be included in the treatment plan for patients that remain premenopausal or perimenopausal after upfront or adjuvant chemotherapy and primary surgery. One strategy for OFS, bilateral salpingo-oophorectomy (BSO), has lasting implications, and the routine recommendation for this strategy warrants a critical analysis in this population. The following is a narrative review of the utility of ovarian suppression or ablation (through either bilateral oophorectomy or radiation) in the context of adjuvant endocrine therapy, including selective estrogen receptor modulators (SERMs) and aromatase inhibitors (AIs). The long-term sequelae of bilateral oophorectomy include cardiovascular and bone density morbidity along with sexual dysfunction, negatively impacting overall quality of life. As gynecologists are the providers consulted to perform bilateral oophorectomies in this population, careful consideration of each patient's oncologic prognosis, cardiovascular risk, and psychosocial factors should be included in the preoperative assessment to assist in shared decision-making and prevent the lifelong adverse effects that may result from overtreatment.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".