Obstetrical and Perinatal Outcomes in Female Survivors of Childhood and Adolescent Cancer: A Population-Based Cohort Study
Bibliographic record
Abstract
BACKGROUND: The likelihood of pregnancy and risk of obstetrical or perinatal complications is inadequately documented in female survivors of pediatric cancer. METHODS: We assembled a population-based cohort of female survivors of cancer diagnosed at age 21 years and younger in Ontario, Canada, between 1985 and 2012. Survivors were matched 1:5 to women without prior cancer. Multivariable Cox proportional hazards and modified Poisson models assessed the likelihood of a recognized pregnancy and perinatal and maternal complications. RESULTS: A total of 4062 survivors were matched to 20 308 comparisons. Median (interquartile range) age was 11 (4-15) years at cancer diagnosis and 25 (19-31) years at follow-up. By age 30 years, the cumulative incidence of achieving a recognized pregnancy was 22.3% (95% confidence interval [CI] = 20.7% to 23.9%) among survivors vs 26.6% (95% CI = 25.6% to 27.3%) among comparisons (hazard ratio = 0.80, 95% CI = 0.75 to 0.86). A lower likelihood of pregnancy was associated with a brain tumor, alkylator chemotherapy, cranial radiation, and hematopoietic stem cell transplantation. Pregnant survivors were as likely as cancer-free women to carry a pregnancy >20 weeks (relative risk [RR] = 1.01, 95% CI = 0.98 to 1.04). Survivors had a higher relative risk of severe maternal morbidity (RR = 2.31, 95% CI = 1.59 to 3.37), cardiac morbidity (RR = 4.18, 95% CI = 1.89 to 9.24), and preterm birth (RR = 1.57, 95% CI = 1.29 to 1.92). Preterm birth was more likely in survivors treated with hematopoietic stem cell transplantation (allogenic: RR = 8.37, 95% CI = 4.83 to 14.48; autologous: RR = 3.72, 95% CI = 1.66 to 8.35). CONCLUSIONS: Survivors of childhood or adolescent cancer are less likely to achieve a pregnancy and, once pregnant, are at higher risk for severe maternal morbidity and preterm birth.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".