Epidemiologic factors that predict long-term survival following a diagnosis of epithelial ovarian cancer
Bibliographic record
Abstract
Various epidemiologic factors have been shown to influence the risk of ovarian cancer development. Given the high fatality associated with this disease, it is of interest to evaluate the association of prediagnostic hormonal, reproductive, and lifestyle exposures with ovarian cancer-specific survival. We included 1421 patients with invasive epithelial ovarian cancer diagnosed in Ontario, Canada. Clinical information was obtained from medical records and prediagnostic exposure information was collected by telephone interview. Survival status was determined by linkage to the Ontario Cancer Registry. Proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for ovarian cancer-specific mortality associated with each exposure. Analyses were stratified by histologic subtype to further investigate the associations of risk factors on ovarian cancer-specific mortality. After a mean follow-up of 9.48 years (range 0.59–20.32 years), 655 (46%) women had died of ovarian cancer. Parity (ever) was associated with a significant 29% decreased mortality risk compared with nulliparity (HR=0.71; 95% CI 0.54–0.93; P =0.01). There was a borderline significant association between ever use of oestrogen-containing hormone replacement therapy (HRT) and mortality (HR=0.79; 95% CI 0.62–1.01; P =0.06). A history of cigarette smoking was associated with a significant 25% increased risk of death compared with never smoking (HR=1.25; 95% CI 1.01–1.54; P =0.04). Women with a greater cumulative number of ovulatory cycles had a significantly decreased risk of ovarian cancer-specific death (HR=0.63; 95% CI 0.43–0.94; P =0.02). Increasing BMI (kg m −2 ) 5 years before diagnosis was associated with an increased risk of death (HR=1.17; 95% CI 1.07–1.28; P =0.0007). Other hormonal or lifestyle factors were not significantly associated with ovarian cancer-specific mortality. Parity, ovulatory cycles, smoking, and BMI may affect survival following the diagnosis of ovarian cancer. Whether or not oestrogen-containing HRT use is beneficial for survival requires further evaluation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".