Fertility preservation in breast cancer patients: IVF and embryo cryopreservation after ovarian stimulation with tamoxifen
Bibliographic record
Abstract
BACKGROUND: Breast cancer chemotherapy commonly causes premature ovarian failure and infertility. Because increased estrogen levels are thought to be potentially risky in breast cancer patients, natural cycle IVF (NCIVF) has been used to preserve fertility and treat infertility in these women. METHODS: Twelve women with breast cancer received 40-60 mg tamoxifen for 6.9 +/- 0.6 days beginning on days 2-3 of their menstrual cycle (15 cycles), and had IVF (TamIVF) with either fresh embryo transfer (six cycles) or cryopreservation (nine cycles). They were compared to a retrospective control group (n = 5) who had natural cycle IVF (NCIVF, nine cycles). RESULTS: Cycle cancellation was significantly less frequent in TamIVF, compared with NCIVF (1/15 versus 4/9, P < 0.05). Compared with NCIVF, TamIVF patients had a greater number of mature oocytes (1.6 +/- 0.3 versus 0.7 +/- 0.2, P = 0.03) and embryos (1.6 +/- 0.3 versus 0.6 +/- 0.2, P = 0.02) per initiated cycle. TamIVF resulted in the generation of embryo(s) in every patient (12/12) while only three out of five patients had an embryo following NCIVF. Two out of six patients in TamIVF, and 2/5 in NCIVF conceived. One patient in the TamIVF group delivered a set of twins. After a mean follow up of 15 +/- 3.6 months (range 3-54), none of the patients had a recurrence of cancer. CONCLUSIONS: Tamoxifen stimulation appears to result in a higher number of embryos and may provide a safe method of IVF and fertility preservation in breast cancer patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".