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Abstract A029: Breast Cancer Screening During Reproductive Years in Women with Germline Pathogenic Variants: Gaps in Counseling and Practice

2025· article· en· W7113902448 on OpenAlexaffabout

Bibliographic record

VenueClinical Cancer Research · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsMcGill University
Fundersnot available
KeywordsBreast cancer screeningMammographyBreast cancerIncidence (geometry)CancerFamily historyGenetic counselingLogistic regression

Abstract

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Abstract Detection of germline pathogenic Variants (PVs) in BRCA1, BRCA2, and other genes that significantly elevate lifetime breast cancer (BC) risk are indications for early initiation of intensive screening. BRCA1/2 PVs guidelines recommend that magnetic resonance imaging (MRI) screening begin at age 25 and mammography screening at age 30. However, pregnancy, breastfeeding, and the postpartum period may complicate adherence due to patient concerns about MRI contrast, radiation exposure, logistical barriers, and limited guidance on timing. The incidence of BC peaks approximately 5 years postpartum, especially among women with a positive family history, and early-onset cancers are frequently aggressive, exacerbating the effects of delayed detection. We assessed screening and counseling practices during reproductive periods among women with or at risk for PVs to identify knowledge gaps and opportunities to improve surveillance. We conducted an anonymous survey from March 2023 through January 2025 distributed by Facing Our Risk of Cancer Empowered (FORCE) and social media platforms. Data were collected through a secure REDCap instrument and summarized with descriptive statistics and logistic regression. The Mayo Clinic Institutional Review Board deemed the study exempt. Among the 537 respondents (median age 43 years; 88.5% U.S. residents; 87.5% White), 66.2% were parous and 61.8% knew their family history of BC during pregnancy. Most women reported receiving counseling on screening breast examination, mammography, and MRI; however, 74-77% received no specific guidance about screening before, during, or after pregnancy and weaning. At the time of the survey, 89.9% had undergone BC screening, including 66.2% with annual mammography and 53.1% with annual MRI. Yet during pregnancy and breastfeeding, 69% reported not being screened. Parous women were more likely than nulliparous women to report screening (96.9% vs 85.6%,p<0.0001) and regular mammography (76.4% vs 57.2%,p<0.0001). Screening during pregnancy and breastfeeding was more common among the BRCA1/2 carriers than among carriers of other PVs. Breastfeeding affected screening behavior in 32% of the BRCA1/2 carriers versus 10.9% of other PV carriers, yet only 5.1% of PV carriers stopped breastfeeding to undergo imaging. After their last birth, many women postponed screenings for more than 3 years and only 20.5% received a mammogram within a year of their delivery. Overall, 28.8% of participants reported a history of cancer, of which 66.2% was BC. Approximately 20% of breast cancers reported were diagnosed within 3 years postpartum, with 8.6% occurring during lactation. Despite high rates of BC screening, most high-risk women received little counseling about imaging during pregnancy and breastfeeding, potentially contributing to delayed surveillance at a time of heightened BC risk. These findings highlight the need for targeted counseling, scheduling strategies to support MRI or other imaging during and after pregnancy, and development of novel early-detection tools such as blood or breastmilk biomarkers. Citation Format: Laura M. Pacheco-Spann, Sue Friedman, Diane Rose, William D. Foulkes, Zhihui Fang, Lauren E. Haydu, Mark E. Sherman. Breast Cancer Screening During Reproductive Years in Women with Germline Pathogenic Variants: Gaps in Counseling and Practice [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr A029.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.089
GPT teacher head0.494
Teacher spread0.405 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes2
Has abstractyes

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