Diagnostic Chest X-Rays and Breast Cancer Risk before Age 50 Years for <i>BRCA1</i> and <i>BRCA2</i> Mutation Carriers
Bibliographic record
Abstract
BACKGROUND: The effects of low-dose medical radiation on breast cancer risk are uncertain, and few studies have included genetically susceptible women, such as those who carry germline BRCA1 and BRCA2 mutations. METHODS: We studied 454 BRCA1 and 273 BRCA2 mutation carriers ages younger than 50 years from three breast cancer family registries in the United States, Canada, and Australia/New Zealand. We estimated breast cancer risk associated with diagnostic chest X-rays by comparing mutation carriers with breast cancer (cases) with those without breast cancer (controls). Exposure to chest X-rays was self-reported. Mammograms were not considered in the analysis. RESULTS: After adjusting for known risk factors for breast cancer, the ORs for a history of diagnostic chest X-rays, excluding those for tuberculosis or pneumonia, were 1.16 [95% confidence interval (CI), 0.64-2.11] for BRCA1 mutations carriers and 1.22 (95% CI, 0.62-2.42) for BRCA2 mutations carriers. The OR was statistically elevated for BRCA2 mutation carriers with three to five diagnostic chest X-rays (P = 0.01) but not for those with six or more chest X-rays. Few women reported chest fluoroscopy for tuberculosis or chest X-rays for pneumonia; the OR estimates were elevated, but not statistically significant, for BRCA1 mutation carriers. CONCLUSIONS: Our findings do not support a positive association between diagnostic chest X-rays and breast cancer risk before the ages of 50 years for BRCA1 or BRCA2 mutation carriers. IMPACT: Given the increasing use of diagnostic imaging involving higher ionizing radiation doses, further studies of genetically predisposed women are warranted.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".