Ovulation Induction for Infertility the Risk of Breast Cancer: A Population-Based Case-Control Study [11B]
Bibliographic record
Abstract
INTRODUCTION: There is a well-established interplay between reproductive hormone levels and breast cancer. Questions remain in regards to the potential ovulation-inducing fertility treatments, which elevate serum estrogen and progesterone to supraphysiologic levels the treatment period, to affect breast tumorigenesis. METHODS: A population-based case-control study using the Clinical Practice Research Datalink (CPRD) was performed. All cases of breast cancer occurring between 1995-2013 were matched with 10 age-matched controls. Cases and controls were assessed for exposure to clomiphene or in-vitro fertilization (IVF) via their clinical records. Odds ratios and 95% confidence intervals for each exposure were computed using multivariate logistic regression, adjusted for smoking, alcohol use, BMI, oral contraceptive use, hormone replacement therapy and oophorectomy. RESULTS: The study population consisted of 27,026 cases of breast cancer and their matched controls, with 1,717 subjects having a history of clomiphene exposure and 1,137 subjects having a history of IVF. Ever-exposure to clomiphene was significantly associated with breast cancer, OR 1.34 95% CI [1.26-1.44]. IVF-exposure was similarly associated with breast cancer, OR 1.52 95% CI [1.40-1.65]. The stratified analysis indicated clomiphene was associated with pre-menopausal cancers (OR 1.59 95% CI [1.47-1.73]) but not post-menopausal malignancies (OR 0.94 95% CI [0.83-1.06]). IVF was associated with both pre- and post-menopausal cancers. CONCLUSION: Ovulation induction with clomiphene citrate and gonadotropins increases the risk of breast cancer. Women should be advised of this elevated risk understanding the associated implications.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".