Prospective cohort of pre-diagnosis hormone exposure and post-diagnosis sex hormone levels with survival outcomes: Alberta Endometrial Cancer Cohort Study
Bibliographic record
Abstract
Purpose: To examine the associations between pre-diagnosis exogenous hormone exposure and endogenous sex hormone levels shortly after diagnosis with survival outcomes in endometrial cancer survivors. Methods: In this population-based cohort, females with endometrial cancer were followed from diagnosis to death or January 27, 2022. History of hormone exposure pre-diagnosis and sex-hormone levels shortly after diagnosis were obtained. The associations between hormone exposure and sex-hormone levels with disease-free survival (DFS) and overall survival (OS) were estimated using Cox proportional hazards regression by multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs). Results: During a median 16.9 years of follow-up (IQR = 15.5-18.1 years), 152 of the 540 participants had a recurrence and/or died. There were no statistically significant associations between exposure to hormonal contraception or menopausal hormone therapy before diagnosis and DFS or OS. Higher estrone levels post-diagnosis were associated with lower DFS (HR 1.56, 95% CI 1.04-2.34) and lower OS (HR 1.76, 95% CI 1.15-2.72). Lower DFS was also observed with higher estradiol levels (HR 1.56, 95% CI 1.02-2.41). Conclusion: There were no associations between pre-diagnosis hormonal contraception or menopausal hormone therapy use and endometrial cancer survival in our study. Endometrial cancer survivors with higher estrogen levels shortly after diagnosis had lower DFS and OS. Further research is needed to confirm these findings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".