Pregnancy outcomes and risk of endometrial cancer: A pooled analysis of individual participant data in the Epidemiology of Endometrial Cancer Consortium
Bibliographic record
Abstract
A full-term pregnancy is associated with reduced endometrial cancer risk; however, whether the effect of additional pregnancies is independent of age at last pregnancy is unknown. The associations between other pregnancy-related factors and endometrial cancer risk are less clear. We pooled individual participant data from 11 cohort and 19 case-control studies participating in the Epidemiology of Endometrial Cancer Consortium (E2C2) including 16 986 women with endometrial cancer and 39 538 control women. We used one- and two-stage meta-analytic approaches to estimate pooled odds ratios (ORs) for the association between exposures and endometrial cancer risk. Ever having a full-term pregnancy was associated with a 41% reduction in risk of endometrial cancer compared to never having a full-term pregnancy (OR = 0.59, 95% confidence interval [CI] 0.56-0.63). The risk reduction appeared the greatest for the first full-term pregnancy (OR = 0.78, 95% CI 0.72-0.84), with a further ~15% reduction per pregnancy up to eight pregnancies (OR = 0.20, 95% CI 0.14-0.28) that was independent of age at last full-term pregnancy. Incomplete pregnancy was also associated with decreased endometrial cancer risk (7%-9% reduction per pregnancy). Twin births appeared to have the same effect as singleton pregnancies. Our pooled analysis shows that, while the magnitude of the risk reduction is greater for a full-term pregnancy than an incomplete pregnancy, each additional pregnancy is associated with further reduction in endometrial cancer risk, independent of age at last full-term pregnancy. These results suggest that the very high progesterone level in the last trimester of pregnancy is not the sole explanation for the protective effect of pregnancy.
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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 | 0.035 | 0.062 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.038 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".