Associations Between Prediagnostic Concentrations of Circulating Sex Steroid Hormones and Liver Cancer Among Postmenopausal Women
Bibliographic record
Abstract
Background and Aims In almost all countries, incidence rates of liver cancer (LC) are 100%‐200% higher in males than in females. However, this difference is predominantly driven by hepatocellular carcinoma (HCC), which accounts for 75% of LC cases. Intrahepatic cholangiocarcinoma (ICC) accounts for 12% of cases and has rates only 30% higher in males. Hormones are hypothesized to underlie observed sex differences. We investigated whether prediagnostic circulating hormone and sex hormone binding globulin (SHBG) levels were associated with LC risk, overall and by histology, by leveraging resources from five prospective cohorts. Approach and Results Seven sex steroid hormones and SHBG were quantitated using gas chromatography/tandem mass spectrometry and competitive electrochemiluminescence immunoassay, respectively, from baseline serum/plasma samples of 191 postmenopausal female LC cases (HCC, n = 83; ICC, n = 56) and 426 controls, matched on sex, cohort, age, race/ethnicity, and blood collection date. Odds ratios (ORs) and 95% confidence intervals (CIs) for associations between a one‐unit increase in log 2 hormone value (approximate doubling of circulating concentration) and LC were calculated using multivariable‐adjusted conditional logistic regression. A doubling in the concentration of 4‐androstenedione (4‐dione) was associated with a 50% decreased LC risk (OR = 0.50; 95% CI = 0.30‐0.82), whereas SHBG was associated with a 31% increased risk (OR = 1.31; 95% CI = 1.05‐1.63). Examining histology, a doubling of estradiol was associated with a 40% increased risk of ICC (OR = 1.40; 95% CI = 1.05‐1.89), but not HCC (OR = 1.12; 95% CI = 0.81‐1.54). Conclusions This study provides evidence that higher levels of 4‐dione may be associated with lower, and SHBG with higher, LC risk in women. However, this study does not support the hypothesis that higher estrogen levels decrease LC risk. Indeed, estradiol may be associated with an increased ICC risk.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".