A case-control study of the joint effect of reproductive factors and radiation treatment for first breast cancer and risk of contralateral breast cancer in the WECARE study
Bibliographic record
Abstract
OBJECTIVE: To examined the impact of reproductive factors on the relationship between radiation treatment (RT) for a first breast cancer and risk of contralateral breast cancer (CBC). METHODS: The Women's Environmental Cancer and Radiation Epidemiology (WECARE) Study is a multi-center, population-based case-control study where cases are women with asynchronous CBC (N = 1521) and controls are women with unilateral breast cancer (N = 2211). Rate ratios (RR) and 95% confidence intervals (CI) were estimated using conditional logistic regression to assess the independent and joint effects of RT (ever/never and location-specific stray radiation dose to the contralateral breast [0, >0-<1Gy, ≥1Gy]) and reproductive factors (e.g., parity). RESULTS: Nulliparous women treated with RT (≥1Gy dose) were at increased risk of CBC compared with nulliparous women not treated with RT, although this relationship did not reach statistical significance (RR = 1.34, 95% CI 0.87, 2.07). Women treated with RT who had an interval pregnancy (i.e., pregnancy after first diagnosis and before second diagnosis [in cases]/reference date [in controls]) had an increased risk of CBC compared with those who had an interval pregnancy with no RT (RR = 4.60, 95% CI 1.16, 18.28). This was most apparent for women with higher radiation doses to the contralateral breast. CONCLUSION: Among young female survivors of breast cancer, we found some evidence suggesting that having an interval pregnancy could increase a woman's risk of CBC following RT for a first breast cancer. While sampling variability precludes strong interpretations, these findings suggest a role for pregnancy and hormonal factors in radiation-associated CBC.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".