Prenatal Biochemical Screening and a Woman’s Long-Term Risk of Cancer: A Population-Based Cohort Study
Bibliographic record
Abstract
BACKGROUND: Some hormones measured in pregnancy are linked to certain hormone-sensitive cancers. We investigated whether routine serum screening in pregnancy is associated with a woman's subsequent risk of hormone-sensitive cancer. METHODS: This population-based cohort study included women aged 12-55 years who underwent prenatal screening between 11 weeks + 0 days of gestation to 20 weeks + 6 days of gestation in Ontario, Canada, 1993-2011, where universal health care is available. The hazard ratio of newly diagnosed breast, ovarian, endometrial, and thyroid cancer-arising at 21 weeks + 0 days of gestation or thereafter-was estimated in association with an abnormally low (≤5th) or high (>95th) percentile multiple of the median (MoM) for alpha-fetoprotein (AFP), total human chorionic gonadotropin (hCG), unconjugated estriol, pregnancy-associated plasma protein A, and dimeric inhibin A. RESULTS: Among 677 247 pregnant women followed for a median of 11.0 years (interquartile range = 7.5-16.1), 7231 (1.07%) developed breast cancer, 515 (0.08%) ovarian cancer, 508 (0.08%) endometrial cancer, and 4105 (0.61%) thyroid cancer. In multivariable adjusted models, abnormally high hCG greater than the 95th percentile MoM was associated with a doubling in the risk of endometrial cancer (adjusted hazard ratio [aHR] = 1.98, 95% confidence interval [CI] = 1.33 to 2.95), and abnormally low AFP at the fifth percentile or less MoM conferred a moderately greater risk of thyroid cancer (aHR = 1.21, 95% CI = 1.07 to 1.38). Abnormally low pregnancy-associated plasma protein A at the fifth percentile or less MoM was not statistically significantly associated with breast cancer after multivariable adjustment (aHR = 1.19, 95% CI = 0.98 to 1.36). CONCLUSIONS: Women with abnormally high levels of serum hCG or low AFP in early pregnancy may be at a greater future risk of certain types of hormone-sensitive cancers.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".