Abstract 1029: The association of body mass index with risk of endometrial cancer subtypes: Pooled analysis in E2C2
Bibliographic record
Abstract
Abstract Excess body weight is a known risk factor for endometrial cancer but whether it differentially affects histological subtypes of endometrial cancer is unclear. The two proposed main subtypes are the “estrogen-dependent Type I” and “non estrogen-dependent and clinically aggressive Type II”. Little is known about risk factors for Type II tumors mainly because most epidemiologic studies lack sufficient cases to study these rare tumors separately. Here we examined the association between recent adult body mass index (BMI) and endometrial tumor subtypes in a pooled analysis of 25 studies in the Epidemiology of Endometrial Cancer Consortium (E2C2). Individual-level data from 10 cohort studies and 15 case-control studies provided a total of 14,409 endometrial cancer cases and 35,950 controls for this analysis. Cohort studies were analyzed using a nested case-control design. The majority of women were white (86%) and postmenopausal (83%). Endometrial cancer cases were classified into two subtypes: Type I (endometrioid adenocarcinomas, adenocarcinoma tubular, papillary adenocarcinomas, mucinous adenocarcinomas, adenocarcinomas with squamous metaplasia, n=13,286) and Type II (serous, squamous cell, small cell, mixed cell, n=1,123). The associations of BMI with the risk of tumor subtypes were evaluated by calculating odds ratios (OR) and 95% confidence intervals (95% CI) using polytomous logistic regression models. Potential confounders included in the analysis were age, race, parity, age at menarche, oral contraceptive (OC) use, menopausal hormone (PMH) use, and smoking status. BMI was positively associated with both Type I and Type II tumors, but the association was stronger for Type I than for Type II tumors (P value for the difference in OR between Type I and Type II was <0.0001). The OR associated with each five kg/m2 increase in BMI (OR5) was 1.58 (95% CI: 1.55, 1.62) for Type I and 1.35 (95% CI: 1.28, 1.42) for Type II. In the analysis of individual histologic types, the OR5 was lowest for serous tumors (1.28), moderate for mixed cell and clear cell (1.33-1.37), and highest for endometrioid tumors (1.60) and various adenocarcinoma groups (1.54-1.58). The associations of BMI with both Type I and II tumors were greater among postmenopausal women who never used PMH [OR5 = 1.84 (95% CI: 1.78, 1.89) for Type I and 1.48 (95% CI: 1.38, 1.58) for Type II] than among estrogen-only users [OR5 = 1.20 (95% CI: 1.13, 1.28) for Type I and 1.05 (95% CI: 0.87, 1.26) for Type II] or among estrogen-progestin users [OR5 = 1.33 (95% CI: 1.25, 1.41) for Type I and 1.12 (95% CI: 0.95, 1.33) for Type II]. Other known endometrial cancer risk factors such as OC use, parity, and smoking did not appear to modify the association between BMI and tumor subtype. In this large pooled analysis, we observed that BMI is a risk factor for all types of endometrial cancer, although, the association is consistently stronger for Type I than for Type II tumors. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1029. doi:1538-7445.AM2012-1029
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.016 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".