Methodological Biases in Estimating the Relationship Between Alcohol Consumption and Breast Cancer: The Role of Drinker Misclassification Errors in Meta‐Analytic Results
Bibliographic record
Abstract
BACKGROUND: While alcohol consumption has been linked to breast cancer in women, few studies have controlled for possible biases created by including former or occasional drinkers in the abstainer reference group. We explored the potential for such misclassification errors as sources of bias in estimates of the alcohol-breast cancer relationship. METHODS: Meta-analyses of population case-control, hospital case-control, and cohort studies to examine relationships between level of alcohol use and breast cancer morbidity and/or mortality in groups of studies with and without different misclassification errors. RESULTS: Of 60 studies identified, only 6 were free of all misclassification errors. The abstainer reference group was biased by the inclusion of former drinkers in 49 studies, occasional drinkers (<10 g ethanol [EtOH] per week) in 22 and by both these groups in 18. Occasional drinkers were also mixed with light or hazardous-level drinkers in 22 studies. Unbiased estimates of the odds ratio (OR) for breast cancer were 1.011 (95% confidence interval [CI]: 0.891 to 1.148) among former drinkers (n = 11) and 1.034 (95% CI: 1.003 to 1.064) among occasional drinkers (n = 17). Hazardous-level drinking (>20 g < 41 g EtOH/d) was not significantly associated with breast cancer in studies with occasional drinker bias. However, in studies free from occasional drinker bias, the OR for breast cancer was 1.085 (95% CI: 1.015 to 1.160) for low-level (<21 g/d) drinkers (n = 17), 1.374 (95% CI: 1.319 to 1.431) for hazardous-level drinkers (n = 26), and 1.336 (95% CI: 1.228 to 1.454) for harmful-level (>40 g/d) drinkers (n = 9). CONCLUSIONS: While the great majority of studies of the alcohol-breast cancer link include misclassification errors, only misclassification of occasional drinkers was found to bias risk estimates significantly. Estimates based on error-free studies confirmed that low, hazardous and harmful levels of alcohol use each significantly increase the risk of breast cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".