Abstract B113: Associations between risk factors and epithelial ovarian cancer survival by racial and ethnic group: an analysis from the ovarian cancer association consortium
Bibliographic record
Abstract
Abstract Background: Associations between lifestyle, hormonal and reproductive factors and survival for epithelial ovarian cancer (EOC) have been studied, however, reports lack stratification by racial and ethnic group. Through the Ovarian Cancer Association Consortium (OCAC), we analyzed associations between survival and EOC risk factors by racial and ethnic group across Asian, Hispanic, Native Hawaiian/Pacific Islander (NHPI) and Non-Hispanic White women with EOC to help inform associations with prognosis. Methods: Participants came from 15 eligible case-control studies from Australia, Canada, England, and the USA with hormonal factors (oral contraceptive use, postmenopausal hormone use, body mass index [BMI]), reproductive factors (age at menarche, parity, breastfeeding, tubal ligation, hysterectomy, endometriosis), smoking and family history. The 12,818 invasive EOC cases were reported as Asian and NHPI (n=908, including 98 NHPI); Hispanic (n=490); and White (n=11,420). Cox proportional hazards regression models estimated hazard ratios (HR) and 95% confidence intervals (95% CI) for risk of all-cause mortality with race and ethnicity as an exposure, and risk factors stratified by race and ethnicity. Models were stratified by study, 10-year age group and stage at diagnosis, and adjusted for age at diagnosis (continuous) and histology. The models with race and ethnicity as the exposure were additionally adjusted for BMI, smoking and postmenopausal hormone use. We assessed heterogeneity in the risk factor associations between racial and ethnic groups using the Wald test with an interaction term for race and ethnicity for each exposure. Results: The mean follow-up after a diagnosis of EOC was 6.1 years (standard deviation = 4.8), with 7512 deaths during the follow-up period (59% of EOC). Compared to White patients, NHPI women with EOC had an increased risk of mortality (HR=1.49, 95% CI=1.08-2.07). There was no statistically significant heterogeneity in associations between risk factors and EOC mortality across racial and ethnic groups. However, we observed differences by racial and ethnic groups for postmenopausal hormone therapy use with a pronounced inverse association for the combined Asian and NHPI group (HR=0.65, 95% CI 0.49-0.88), less so for White and Hispanic women (HR=0.90, 95% CI 0.84-0.95 and HR=0.81, 95% CI 0.57-1.14, respectively). High recent BMI (≥30 kg/m2 compared with <25) was associated with increased risk of mortality in Hispanic and White women only (HR=1.43, 95% CI 1.00-2.03 and HR=1.14, 95% CI 1.06-1.22, respectively). Current smoking was associated with higher mortality risk among White women (HR=1.15, 95% CI 1.07-1.25) but not in the other groups. Conclusions: We observed that compared with White women, NHPI women with EOC had a higher risk of mortality. The known association between postmenopausal hormone therapy use and reduced risk of mortality was particularly pronounced for the combined Asian and NHPI group. More work is needed to understand the disparity in mortality outcome for NHPI women with EOC. Citation Format: Nicola S. Meagher, Kami K. White, Lynne R. Wilkens, Penelope M. Webb, Anna H. Wu, Lauren C. Peres, Melissa A. Merritt. Associations between risk factors and epithelial ovarian cancer survival by racial and ethnic group: an analysis from the ovarian cancer association consortium [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr B113.
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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".