The association between body mass index and molecular subtypes in endometrial carcinoma
Bibliographic record
Abstract
Objective: This study aims to investigate the relationship between body mass index (BMI) and molecular subtypes of endometrial carcinoma using an immunohistochemistry (IHC)-based classification approach. Methods: We analyzed a consecutive series of endometrial cancer cases undergoing surgical staging in southern Alberta (2019-2021). Molecular classification was determined through IHC-based molecular typing, incorporating p53 and mismatch repair (MMR), and further characterized with the addition of ER and PR. BMI associations with molecular classification were assessed using t-tests. Hormone receptor status was further examined in a separate cohort of MMRd endometrial cancer patients undergoing surgical staging at Foothills Medical Centre (Alberta, Canada). Results: . While there were no significant BMI differences between FIGO grade 1 and grade 2/3 tumours in the pNSMP or MMRd, a trend toward higher BMI in grade 1 tumours versus grade 2/3 tumours in the MMRd was observed (p = 0.13). A separate cohort of 53 MMRd endometrial carcinomas revealed that FIGO grade 1 tumours were associated with higher BMI (p < 0.05) and more frequent ER/PR expression compared to grade 2/3 tumours (p < 0.05). Conclusions: This study suggests an association between obesity and NSMP endometrial carcinoma. The relationship between BMI and low-grade MMRd endometrial carcinomas with increased ER/PR expression warrants further exploration.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".