Cigarette smoking and breast cancer risk: A long latency period?
Bibliographic record
Abstract
The association between cigarette smoking and breast cancer risk remains unclear. Few studies have examined cigarette smoking of very long duration as there may not have been a sufficient number of long-term smokers in studies conducted before the 1980s. Therefore, we examined the association between smoking and breast cancer risk using data from participants in a randomized controlled trial of screening for breast cancer involving 89,835 women aged 40-59 years at recruitment and with up to 40 years of smoking duration at that time. Women with breast cancer diagnosed through 31 December 1993 were identified by linkage to the Canadian Cancer Database. Cox proportional hazards models were used to estimate rate ratios (RRs) and 95% confidence intervals (CIs). During an average of 10.6 years of follow-up, we observed 2,552 incident cases of breast cancer. We found a positive association between cigarette smoking and breast cancer risk, driven mainly by women who had smoked for several decades and who, therefore, had commenced smoking many years earlier. Relative to never-smokers, women who had smoked 40 years or more and 20 cigarettes/day or more were at the highest risk (RR = 1.83, 95% CI 1.29-2.61); for women who had commenced smoking 40 years or more before assessment (a measure of smoking latency rather than duration and intensity), the RR was 1.22 (95% CI 0.99-1.59). Our findings suggest that smoking of very long duration and high intensity may be associated with increased risk of breast cancer.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".