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Record W2935692316 · doi:10.1093/jbi/wby015

Breast Cancer Screening in High-Risk Patients during Pregnancy and Breastfeeding: A Systematic Review of the Literature

2019· review· en· W2935692316 on OpenAlexaff
Nanxi Zha, Mostafa Alabousi, Peri Abdullah, Vivianne Freitas, Rhys Linthorst, Narry Muhn, Abdullah Alabousi

Bibliographic record

VenueJournal of Breast Imaging · 2019
Typereview
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsUniversity of TorontoYork UniversityMcMaster University
Fundersnot available
KeywordsBreastfeedingMedicineBreast cancerMammographyPopulationSystematic reviewFamily medicineBreast cancer screeningMEDLINEGynecologyBreast feedingPregnancyObstetricsCancerPediatricsEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.249
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.289
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations7
Published2019
Admission routes1
Has abstractyes

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