Sex Hormones, Insulin, and Insulin-like Growth Factors in Recurrence of High-Stage Endometrial Cancer
Bibliographic record
Abstract
BACKGROUND: The influence of sex hormone and insulin/insulin-like growth factor (IGF) axis signaling on endometrial cancer recurrence is unknown. We evaluated these pathways in a prospective cohort of Gynecologic Oncology Group (GOG)0210 trial endometrial adenocarcinoma patients. METHODS: , insulin (IR) and IGF-I receptors (IGF1R), phosphorylated IR/IGF1R (pIGF1R/pIR), and estrogen (ER) and progesterone receptors (PR) using qPCR and IHC. Serum concentrations of insulin, IGF-I, IGFBP-3, estradiol, estrone, and sex hormone binding globulin were measured. HRs and 95% confidence intervals (CI) for progression-free survival were calculated from Cox models adjusting for age, stage, and grade. RESULTS: Recurrence occurred in 280 (34%) cases during a median of 4.6 years of follow-up. ER positivity (HR, 0.67; 95% CI, 0.47-0.95), IR positivity (HR, 0.53; 95% CI, 0.29-0.98), and circulating IGF-I (highest vs. lowest quartile: HR, 0.66; 95% CI, 0.47-0.92) were inversely associated with recurrence risk. Circulating estradiol (highest vs. lowest tertile: HR, 1.55; 95% CI, 1.02-2.36) and pIGF1R/pIR positivity (HR, 1.40; 95% CI, 1.02-1.92) were associated with increased recurrence risk. CONCLUSIONS: Circulating estradiol and tumor tissue phosphorylated (activated) IGR1R/IR were independently associated with higher risk of recurrence in patients with endometrial cancer. IMPACT: This study may inform future clinical trials of endocrine-targeted adjuvant therapies in patients with endometrial cancer that could include baseline assessment of serum and tissue biomarkers of estradiol and insulin signaling pathways.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".