Breast Cancer Screening in High-Risk Patients during Pregnancy and Breastfeeding: A Systematic Review of the Literature
Bibliographic record
Abstract
There are currently no clear guidelines for high-risk breast cancer screening during the pregnancy and breastfeeding periods. The objective of this systematic review (SR) was to assess the available evidence pertaining to breast cancer screening recommendations in this population with the aim of supporting future guidelines. We performed a SR of the literature using the electronic databases MEDLINE and Embase. Predetermined inclusion and exclusion criteria were used during the abstract screening and full-text data extraction phases. We retrieved 2,274 abstracts after removal of duplicates, from which 16 studies were included based on predetermined eligibility criteria. Most of the studies found were narrative reviews and expert opinions. Clinical breast exam (CBE) was recommended by 12 studies during pregnancy and by 6 studies in the breastfeeding period. Mammography was recommended in the breastfeeding period by 2 studies. Magnetic resonance imaging was recommended in the breastfeeding period by 2 studies. Ultrasound was considered not appropriate for screening in this population. The information extracted from this SR is based primarily on expert opinion and anecdotal evidence, which explains the lack of standardized guidelines for high-risk breast cancer screening in this population. However, expert opinion may be a surrogate outcome for high-risk breast cancer screening recommendations in this subset of patients, and as such, may justify the clinical management to be tailored accordingly. This SR summarizes the evidence pertaining to high-risk breast cancer screening during pregnancy and breastfeeding, which could serve as a catalyst for future research on the topic.
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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 | 0.010 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".