Lifestyle, weight history, nutrition and breast cancer among non-gene carriers: a case-control study.
Bibliographic record
Abstract
Abstract Abstract #6084 We conducted a nested case-control study of 280 French-Canadian women with breast cancer who were non-gene carriers (BRCA) and 280 women without cancer who were also non-gene carriers. A validated lifestyle questionnaire and a food frequency questionnaire were administered to obtain relevant information. It was found that age at the time the subjects reached maximum body mass index (BMI) was significantly associated with breast cancer risk [OR=2.83; 95% CI: (2.34-2.81)]. In addition, a significant association was noted between maximum weight gain at age 20 years [OR=1.68; 95% CI: (1.10-2.58)], 30 years [OR=1.96; 95% CI: (1.46-3.06)], and 40 years [OR=2.50; 95% CI: (1.72-3.97)] and breast cancer risk. Women who smoked more than 9 pack-years of cigarettes had a higher risk of breast cancer [OR=1.59; 95% CI: (1.57-2.87)]. Subjects who engaged in moderate physical activity had a 52% decreased risk of breast cancer [OR=0.48; 95% CI: (0.31-0.74)], but this was not evident for vigorous physical activity. It was observed that total energy intake was significantly associated with breast cancer risk [OR=2.54; 95% CI: (1.67-3.84)]. Women who drank more than 8 cups of coffee per day had 40% more chance of developing breast cancer [OR=1.40 (95% CI: (1.09-2.24)]. Subjects who consumed more than 9 grams of alcohol (ethanol) per day had the highest risk of breast cancer [OR=1.55 (95% CI: (1.02-2.37)]. None of the other nutrients and dietary components was significantly associated with non-gene carrier breast cancer risk. This study suggests that BMI, maximum weight gain during the second, third and fourth decades, smoking, total energy intake, and high intake of both alcohol and coffee may increase the risk of breast cancer among non-gene carrier French-Canadian women, while moderate physical activities may reduce the risk. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 6084.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".