Endometriosis-associated ovarian cancer: A ten-year cohort study of women living in the Estrie Region of Quebec, Canada
Bibliographic record
Abstract
OBJECTIVES: Endometriosis has been believed to increase the risk of developing ovarian cancer, but recent data supporting this hypothesis are lacking. The aim of this study was to verify whether the incidence of endometriosis, ovarian cancer and the both increased during the last 10 years among women living in the Estrie region of Quebec. METHODS: We collected data of women diagnosed with endometriosis, ovarian cancer or both, between 1997 and 2006, from a population living in the Estrie region of Quebec. We performed this retrospective cross-sectional study from the CIRESSS (Centre Informatisé de Recherche Evaluative en Services et Soins de Santé) system, the database of the CHUS (Centre Hospitalier Universitaire of Sherbrooke), Sherbrooke, Canada. RESULTS: Among the 2854 identified patients, 2521 had endometriosis, 292 patients had ovarian cancer and 41 patients had both ovarian cancer and endometriosis. We showed a constant increase in the number of ovarian cancer (OC) between 1997 and 2006 (r2 = 0.557, P = 0.013), which is not the case for endometriosis (ENDO) or endometriosis-associated ovarian cancer (EAOC). The mean age +/- SD was 40.0 +/- 9.9 and 53.9 +/- 11.4 for patients having ENDO and OC, respectively. Mean age of women with EAOC was 48.3 +/- 10.8, suggesting an early onset of ovarian cancer in women having endometriosis of about 5.5 years average, P = 0.003. Women with ENDO were at increased risk for developing OC (Rate Ratio [RR] = 1.6; 95% Confidence Interval [CI] = 1.12-2.09). Pathological analyses showed the predominance of endometrioid type (24.4%) and clear-cell type (21.9%) types in EAOC compared to OC, P = 0.0070 and 0.0029, respectively. However, the serous type is the most widespread in OC (44.5%) in comparison to EAOC (19.51%), P = 0.0023. CONCLUSION: Our findings highlight that the number of cases of ovarian cancer is constantly increasing in the last ten years and that endometriosis represents a serious risk factor which accelerates its apparition by about 5.5 years.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".