312Long-term survival of women diagnosed with cancer during pregnancy or postpartum
Bibliographic record
Abstract
Abstract Background Cancer is the second leading cause of death in reproductive-aged women, and the incidence of pregnancy-associated cancer is rising. We assessed long-term survival of women diagnosed with cancer during pregnancy or postpartum. Methods A population-based retrospective cohort study included all reproductive-aged women (18-50 years) with a cancer diagnosis in Alberta, Canada, 2004 to 2016. Hazard ratios (HR) were calculated for all-cause and cancer-specific mortality, comparing 244 women who were diagnosed with cancer during pregnancy and 670 women diagnosed with cancer within one year postpartum, with 3,680 women diagnosed with cancer outside of these periods as the referent. Cox regression adjusted for age at cancer diagnosis, parity, cancer stage, and type of cancer. Results Rates of cancer in pregnancy and postpartum did not increase across the study period (trend p-value=0.49). Women diagnosed with cancer in pregnancy had an adjusted HR of 1.61 (95% CI 1.07-2.41) for all-cause mortality, 1.67 (95% CI 1.09-2.57) for cancer-specific mortality, relative to the referent. Those diagnosed with cancer postpartum did not have a greater risk of all-cause (HR = 1.10, 95% CI 0.80-1.50) or cancer-specific (HR = 1.15, 95% CI 0.82-1.60) mortality. Conclusions The risk of all-cause and cancer-specific mortality is increased in women diagnosed with cancer during pregnancy. Key messages Women diagnosed with cancer during pregnancy experience poorer survival than those diagnosed in postpartum or remote from a pregnancy. These findings should be used by physicians to guide care of women diagnosed with pregnancy-associated cancers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 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".