Risk factors for thyroid cancer: A prospective cohort study
Bibliographic record
Abstract
Given the higher incidence rate of thyroid cancer among women compared to men and evidence that smoking and alcohol consumption may be inversely related to thyroid cancer risk, we examined thyroid cancer risk in association with menstrual, reproductive and hormonal factors, and cigarette and alcohol consumption, in a prospective cohort study of 89,835 Canadian women aged 40-59 at recruitment who were enrolled in the National Breast Screening Study (NBSS). Linkages to national cancer and mortality databases yielded data on cancer incidence and deaths from all causes, respectively, with follow-up ending between 1998 and 2000. Cox proportional hazards models (using age as the time scale) were used to estimate hazard ratios and 95% confidence intervals for the association between each of the potential risk factors and risk of thyroid cancer overall and by the main histologic subtypes. During a mean of 15.9 years of follow-up, we observed 169 incident thyroid cancer cases. There was no evidence of altered overall thyroid cancer risk with any of the menstrual, reproductive, or hormonal factors. There was evidence of a decreased risk of papillary thyroid cancer among women with 5 or more live births (vs. nulliparous). Age at which smoking commenced, duration of smoking, number of cigarettes smoked per day, pack-years of smoking and alcohol consumption were not associated with altered thyroid cancer risk. The present study provides little support for associations with hormonal factors, smoking, or alcohol consumption, but there is a need for additional prospective data.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".