Data from Hyperemesis Gravidarum and the Potential for Cancer: A Longitudinal Cohort Study over Three Decades
Bibliographic record
Abstract
AbstractBackground: Our objective was to assess whether hyperemesis gravidarum is associated with the risk of endodermal, mesodermal, and ectodermal human chorionic gonadotropin (hCG) receptor+ cancer in women. Methods: We performed a longitudinal cohort study of 1,343,040 women who were pregnant between 1989 and 2019 in Quebec, Canada. We identified women with and without hyperemesis gravidarum and followed them over time to capture incident cancers, grouped by embryonic germ cell layer of origin and organ hCG receptor positivity. We used time-varying Cox regression to model hazard ratios (HR) and 95% confidence intervals (CI) for the association between hyperemesis gravidarum and cancer onset, adjusted for maternal age, comorbidity, multiple gestation, fetal congenital anomaly, socioeconomic deprivation, and time period. Results: Women with hyperemesis gravidarum had a greater risk of endodermal cancer compared with no hyperemesis gravidarum (5.8 vs. 4.8 per 10,000 person-years; HR, 1.36; 95% CI, 1.17–1.57), but not mesodermal or ectodermal cancer. Severe hyperemesis with metabolic disturbance was more strongly associated with cancer from the endodermal germ layer (HR, 1.97; 95% CI, 1.51–2.58). The association between hyperemesis gravidarum and endodermal cancer was driven by bladder (HR, 2.49; 95% CI, 1.37–4.53), colorectal (HR, 1.41; 95% CI, 1.08–1.84), and thyroid (HR, 1.43; 95% CI, 1.09–1.64) cancer. Conclusions: Women with hyperemesis gravidarum have an increased risk of cancers arising from the endodermal germ cell layer, particularly bladder, colorectal, and thyroid cancers. Impact: Future studies identifying the pathways linking hyperemesis gravidarum with endodermal tumors may help improve the detection and management of cancer in women.
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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 | 0.002 |
| 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) | 0.002 | 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".