Medical radiation exposure and breast cancer risk: Findings from the Breast Cancer Family Registry
Bibliographic record
Abstract
Moderate to high-dose radiotherapy is known to increase the risk of breast cancer. Uncertainties remain about the effects of low-dose chest X-rays, particularly in individuals at increased genetic risk. We analyzed case-control data from the Breast Cancer Family Registry. Self-reported data on therapeutic and diagnostic radiation exposures to the chest were available for 2,254 breast cancer cases and 3,431 controls (1,556 unaffected sisters and 1,875 unrelated population controls). We used unconditional logistic regression analyses to estimate odds ratios (OR) and 95% confidence intervals (CI) associated with radiation exposure, after adjusting for age, study center, country of birth, and education. Increased risks for breast cancer were found for women who had radiotherapy for a previous cancer (OR=3.55, CI=1.47-8.54) and diagnostic chest X-rays for tuberculosis (OR=2.49, CI=1.82-3.40) or pneumonia (OR=2.19, CI=1.38-3.47). Risks were highest for women with a large number of exposures at a young age or exposed in earlier calendar years. There was no evidence of increased risk associated with other diagnostic chest X-rays (not including tuberculosis or pneumonia), both in women with and without indicators of increased genetic risk (i.e., diagnosed at age <40 years or family history of breast cancer). Given the widespread and increasing use of medical diagnostic radiation, continued surveillance of breast cancer risk is warranted, particularly in women at specific genetic risk, such as those carrying mutations in BRCA1 or BRCA2.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".