Molecular Phenotype of Breast Cancer According to Time Since Last Pregnancy in a Large Cohort of Young Women
Bibliographic record
Abstract
BACKGROUND: The increase in breast cancer risk during pregnancy and postpartum is well known; however, the molecular phenotype of breast cancers occurring shortly after pregnancy has not been well studied. Given this, we investigated whether nulliparity and the time interval since pregnancy among parous women affects the breast cancer phenotype in young women. MATERIALS AND METHODS: We examined molecular phenotype in relation to time since pregnancy in a prospective cohort of 707 young women (aged ≤40 years) with breast cancer. Parity was ascertained from study questionnaires. Using tumor histologic grade on central review and biomarker expression, cancers were categorized as luminal A- or B-like, HER2 enriched, and triple negative. RESULTS: Overall, 32% were luminal A-like, 41% were luminal B-like, 9% were HER2 enriched, and 18% were triple negative. Although, numerically, patients diagnosed >5 years after pregnancy had more luminal A-like subtypes than women with shorter intervals since pregnancy, there was no evidence of a relationship between these intervals and molecular subtypes once family history of breast cancer and age at diagnosis were considered. CONCLUSION: Distribution of breast cancer molecular phenotype did not differ significantly among young women by parity or time interval since parturition when important predictors of tumor phenotype such as age and family history were considered. IMPLICATIONS FOR PRACTICE: Distribution of breast cancer molecular phenotype did not differ among parous young women by time interval since pregnancy. The implication of these findings for clinical practice suggests that pregnancy-associated breast cancers may be seen up to 5 years beyond parturition.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".