Breast cancer risk following Hodgkin lymphoma radiotherapy in relation to menstrual and reproductive factors
Bibliographic record
Abstract
BACKGROUND: Women treated with supradiaphragmatic radiotherapy (sRT) for Hodgkin lymphoma (HL) at young ages have a substantially increased breast cancer risk. Little is known about how menarcheal and reproductive factors modify this risk. METHODS: We examined the effects of menarcheal age, pregnancy, and menopausal age on breast cancer risk following sRT in case-control data from questionnaires completed by 2497 women from a cohort of 5002 treated with sRT for HL at ages <36 during 1956-2003. RESULTS: Two-hundred and sixty women had been diagnosed with breast cancer. Breast cancer risk was significantly increased in patients treated within 6 months of menarche (odds ratio (OR) 5.52, 95% confidence interval (CI) (1.97-15.46)), and increased significantly with proximity of sRT to menarche (Ptrend<0.001). It was greatest when sRT was close to a late menarche, but based on small numbers and needing reexamination elsewhere. Risk was not significantly affected by full-term pregnancies before or after treatment. Risk was significantly reduced by early menopause (OR 0.55, 95% CI (0.35-0.85)), and increased with number of premenopausal years after treatment (Ptrend=0.003). CONCLUSION: In summary, this paper shows for the first time that sRT close to menarche substantially increases breast cancer risk. Careful consideration should be given to follow-up of these women, and to measures that might reduce their future breast cancer risk.
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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 | 0.002 |
| 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 | 0.000 | 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".