Impact of Pregnancy on Breast Cancer Features and Prognosis
Bibliographic record
Abstract
Background: pregnancy-associated breast cancer (PABC) affects one in 3000 pregnancies, often presenting with aggressive features. Methods: We retrospectively evaluated a cohort of 282 young BC patients (≤45 years old) treated between 1995 and 2019, dividing them into three groups: nulliparous women, women with PABC (diagnosed within 2 years since last pregnancy) and women with BC diagnosed > 2 years since last pregnancy. This last group was further stratified according to the time between pregnancy and BC. The analysis encompassed histological factors (tumor size, histotype, grading, nodal involvement, multifocality, lympho-vascular invasion, hormone receptor expression, Ki-67 index, and HER2 expression), type of surgery and recurrence. Results: Age at diagnosis was younger in nulliparous than in parous women (p < 0.001). No significant differences were noticed regarding histological characteristics and recurrences. At univariate analysis, nodal involvement (OR = 2.4; p < 0.0001), high tumor grade (OR = 2.6; p = 0.01), and lympho-vascular invasion (OR = 2.3; p < 0.05), but not pregnancy (OR = 0.8; p = 0.30), influenced DFS negatively. Multivariate analysis confirmed nodal involvement as the only negative independent prognostic factor for a worse DFS (OR = 2.4; p = 0.0001). Conclusions: in our experience, pregnancy is not an independent adverse prognostic factor for BC DFS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".