Long-term Mortality in Individuals Diagnosed With Cancer During Pregnancy or Postpartum
Bibliographic record
Abstract
Importance: Outcomes among patients with pregnancy-associated cancers (diagnosed during pregnancy or 1-year postpartum) other than breast cancer have received relatively little research attention. High-quality data from additional cancer sites are needed to inform the care of this unique group of patients. Objective: To assess mortality and survival in premenopausal women with pregnancy-associated cancers, with a particular focus on cancers other than those of the breast. Design, Setting, and Participants: This population-based retrospective cohort study included premenopausal women (aged 18-50 years) living in 3 Canadian provinces (Alberta, British Columbia, and Ontario) diagnosed with cancer between January 1, 2003, and December 31, 2016, with follow-up until December 31, 2017, or date of death. Data analysis occurred in 2021 and 2022. Exposures: Participants were categorized as being diagnosed with cancer during pregnancy (from conception to delivery), during the postpartum period (up to 1 year after delivery), or during a time that was remote from pregnancy. Main Outcomes and Measures: Outcomes were overall survival at 1 and 5 years and time from diagnosis to death due to any cause. Cox proportional hazard models were used to estimate mortality adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs), adjusting for age at cancer diagnosis, cancer stage, cancer site, and days from diagnosis to first treatment. Meta-analysis was used to pool results across all 3 provinces. Results: During the study period there were 1014, 3074, and 20 219 participants diagnosed with cancer during pregnancy, postpartum, and periods remote from pregnancy, respectively. One-year survival was similar across the 3 groups, but 5-year survival was lower among those diagnosed with cancer during pregnancy or postpartum. Overall, there was a greater risk of death due to pregnancy-associated cancer among those diagnosed during pregnancy (aHR, 1.79; 95% CI, 1.51-2.13) and postpartum (aHR, 1.49; 95% CI, 1.33-1.67); however, these results varied across cancer sites. Increased hazard of mortality was observed for breast (aHR, 2.01; 95% CI, 1.58-2.56), ovarian (aHR, 2.60; 95% CI, 1.12-6.03), and stomach (aHR, 10.37; 95% CI, 3.56-30.24) cancers diagnosed during pregnancy, and brain (aHR, 2.75; 95% CI, 1.28-5.90), breast (aHR, 1.61; 95% CI, 1.32-1.95), and melanoma (aHR, 1.84; 95% CI, 1.02-3.30) cancers diagnosed postpartum. Conclusions and Relevance: This population-based cohort study found that pregnancy-associated cancers had increased overall 5-year mortality, though not all cancer sites presented the same risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".