Pregnancy Outcomes in Survivors of Adolescent and Young Adult Breast Cancer: A Population-Based Cohort Study
Bibliographic record
Abstract
OBJECTIVES: To evaluate the association between adolescent and young adult (AYA) breast cancer (BC) and the adverse pregnancy outcomes of preterm birth, small for gestational age birth, cesarean delivery, and preeclampsia, and the effect of fertility treatment on this association. METHODS: weeks gestation between April 2006 to March 2018 were included. Modified Poisson regression generated risk ratios between AYA BC and adverse pregnancy outcomes, adjusted for maternal characteristics. Models were stratified by fertility treatment. RESULTS: Among 1 189 980 deliveries, 474 mothers had AYA BC history (exposed), while 1 189 506 had no cancer history (unexposed). AYA BC was associated with cesarean delivery (adjusted risk ratio [aRR] 1.26; 95% CI 1.14-1.39). There was no association between AYA BC and other adverse outcomes. Modelling cesarean delivery subtypes, AYA BC was associated with increased risk of planned (aRR 1.27; 95% CI 1.08-1.49) and unplanned cesarean delivery (aRR 1.41; 95% CI 1.20-1.66). An increased risk of cesarean delivery in exposed persisted among singleton pregnancies (aRR 1.27; 95% CI 1.15-1.41), but not in models stratified by mode of conception (fertility treatment: aRR 1.07; 95% CI 0.84-1.36; unassisted conception: aRR 1.30; 95% CI 1.16-1.46). CONCLUSIONS: A history of AYA BC did not confer an elevated risk of adverse pregnancy outcomes, except for planned and unplanned cesarean delivery. The risk of adverse pregnancy outcomes does not appear to be an indication for delayed pregnancy after AYA BC diagnosis.
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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 | 0.002 |
| 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 | 0.000 |
| 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".