Hormonal factors in association with lung cancer among Asian women: A pooled analysis from the International Lung Cancer Consortium
Bibliographic record
Abstract
Abstract Two thousand sixty‐four lung cancer cases and 5342 controls were evaluated in this International Lung Cancer Consortium (ILCCO) pooled analysis on estrogen‐related hormonal factors and lung cancer in Asian women. Random effect of study site and fixed effect of age, smoking status, comprehensive smoking index and family history of lung cancer were adjusted for in the multivariable logistic regression models. We found that late onset of menarche conferred elevated odds of lung cancer with adjusted odds ratio (OR) of 1.24 (95% confidence interval [CI] = 1.05, 1.45) for 17 years or older, compared to 14 years or younger. Late onset of menopause at 55 years old or older was associated with lung cancer with OR = 1.24 (95% CI = 1.02, 1.51). Nonnatural menopause was associated with an OR of 1.39 (95% CI = 1.13, 1.71). More live births showed reversed association with lung cancer (ORs of 5 or more live births: 0.71 (95% CI = 0.60, 0.84), compared to 0‐2 live births (Ptrend < 0.001). A later first child delivery seemed associated with an increased susceptibility: OR of 21 to 25 years old: 1.23 (95% CI = 1.06, 1.40), 26 or older: 1.27 (95% CI = 1.06, 1.52), Ptrend = .010). The use of oral contraceptives appeared to be protective with an OR of 0.69 (95% CI = 0.57, 0.83). Stronger for adenocarcinoma than squamous cell carcinoma, these relationships were not clearly modified by smoking status, probably because of lower prevalence of smoking. This is a first and largest pooling study of lung cancer among Asian women and the results suggested potential roles of hormone‐related pathways in the etiology of this disease.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.011 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".