Reproductive Outcomes in Young Breast Cancer Survivors Treated (15–39) in Ontario, Canada
Bibliographic record
Abstract
We conducted a population-based, retrospective, matched-cohort study to examine the impact of breast cancer diagnosis and treatment on fertility outcomes. Relative risks of infertility, childbirth, premature ovarian insufficiency (POI; age < 40) and early menopause (age < 45) were calculated using modified Poisson regression. Our primary cohort included young women (15-39) with early stage BC diagnosed 1995-2014. Five cancer-free patients were matched to each BC patient by birth year and census subdivision. The BC cohort was further divided by treatment with chemotherapy vs. no chemotherapy treatment. 3903 BC patients and 19,515 cancer-free women. BC patients treated with chemotherapy were at increased risk of infertility (RR 1.81; 95% CI 1.60-2.04), and POI (RR 6.25; 95% CI 5.15-7.58) and decreased childbirth (RR 0.85; 95% CI 0.75-0.96), compared to women without cancer. BC patients who did not receive chemotherapy were also at increased risk of infertility (RR 1.80 95% CI 1.48-2.18) and POI (RR 2.12 95% CI 1.37-3.28). All young BC survivors face an increased risk of diagnosed infertility and POI relative to women without cancer, independent of chemotherapy. These results emphasize the importance of pre-treatment fertility counselling for young women diagnosed with BC.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 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".