Coronary Artery Disease in Young Women After Radiation Therapy for Breast Cancer
Bibliographic record
Abstract
Radiation therapy (RT) for breast cancer increases risk of coronary artery disease (CAD). Women treated for left- vs right-sided breast cancer receive greater heart radiation exposure, which may further increase this risk. The risk of radiation-associated CAD specifically among younger breast cancer survivors is not well defined. The purpose of this study was to report CAD risk among participants in the Women’s Environmental Cancer and Radiation Epidemiology Study. A total of 1,583 women who were <55 years of age when diagnosed with breast cancer between 1985 and 2008 completed a cardiovascular health questionnaire. Risk of radiation-associated CAD was evaluated by comparing women treated with left-sided RT with women treated with right-sided RT using multivariable Cox proportional hazards models. Effect modification by treatment and cardiovascular risk factors was examined. In total, 517 women who did not receive RT and 94 women who had a pre-existing cardiovascular disease diagnosis were excluded, leaving 972 women eligible for analysis. Their median follow-up time was 14 years (range 1-29 years). The 27.5-year cumulative incidences of CAD for women receiving left- vs right-sided RT were 10.5% and 5.8%, respectively (P = 0.010). The corresponding HR of CAD for left- vs right-sided RT in the multivariable Cox model was 2.5 (95% CI: 1.3-4.7). There was no statistically significant effect modification by any factor evaluated. Young women treated with RT for left-sided breast cancer had over twice the risk of CAD compared with women treated with RT for right-sided breast cancer. Laterality of RT is independently associated with an increased risk of CAD and should be considered in survivorship care of younger breast cancer patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".