Case–control study of inflammatory markers and the risk of endometrial cancer
Bibliographic record
Abstract
Chronic inflammation may be important in endometrial cancer etiology. Several established endometrial cancer risk factors, particularly obesity, are hypothesized to operate through this pathway by increasing proinflammatory cytokines such as tumor necrosis factor α (TNF-α), interleukin-6 (IL-6), and acute-phase protein C-reactive protein (CRP). This study sought to investigate the association between inflammatory markers and the risk of endometrial cancer (types I and II). We recruited 519 incident endometrial cancer cases and 964 frequency age-matched controls in this population-based case-control study in Alberta (Canada) from 2002 to 2006. Participants completed in-person interviews, were assessed for anthropometric measures, and provided 8-h fasting blood samples either preoperatively or postoperatively. Blood was analyzed for the concentrations of TNF-α, IL-6, and CRP by immunoassay. Endometrial cancer cases had consistently higher mean levels of TNF-α, IL-6, and CRP compared with controls in these predominantly postmenopausal women. After adjusting for age, all markers were associated with statistically significant increased risks for endometrial cancer; however, after multivariable adjustment, only the risk from CRP remained elevated (odds ratio=1.22, 95% confidence interval: 1.02-1.47). Similarly, upon stratification by cancer type, only CRP was associated positively with an increased risk for type I endometrial cancer (odds ratio=1.25, 95% confidence interval: 1.03-1.52). All markers were associated with an elevated risk for the more rare and aggressive type II cancers; however, these findings were statistically nonsignificant, likely because of the small number of cases in this group. In conclusion, we found epidemiologic evidence for an association between CRP and the risk of endometrial cancer, which was slightly stronger for type I cancer. No associations emerged for TNF-α and IL-6.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".