Breast cancer survival among young women: a review of the role of modifiable lifestyle factors
Bibliographic record
Abstract
Almost 7% of breast cancers are diagnosed among women age 40 years and younger in Western populations. Clinical outcomes among young women are worse. Early age-of-onset increases the risk of contralateral breast cancer, local and distant recurrence, and subsequent mortality. Breast cancers in young women (BCYW) are more likely to present with triple-negative (TNBC), TP53-positive, and HER-2 over-expressing tumors than among older women. However, despite these known differences in breast cancer outcomes and tumor subtypes, there is limited understanding of the basic biology, epidemiology, and optimal therapeutic strategies for BCYW. Several modifiable lifestyle factors associated with reduced risk of developing breast cancer have also been implicated in improved prognosis among breast cancer survivors of all ages. Given the treatment-related toxicities and the extended window for late effects, long-term lifestyle modifications potentially offer significant benefits to BCYW. In this review, we propose a model identifying three main areas of lifestyle factors (energy imbalance, inflammation, and dietary nutrient adequacy) that may influence survival in BCYW. In addition, we provide a summary of mechanisms of action and a synthesis of previous research on each of these topics.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".