Implementing Integrated Genomic Risk Assessments for Breast Cancer: Lessons Learned from the eMERGE Study

Abstract

Objective: To develop and implement a pipeline for integrated breast cancer risk assessment using the BOADICEA model within the eMERGE study, incorporating polygenic risk scores (PRS), monogenic variants, family history, and clinical factors.

Materials and methods: A pipeline was deployed across ten eMERGE clinical sites, integrating data from REDCap surveys, PRS reports, monogenic reports, and pedigrees via CanRisk Application Programming Interface (API). The process included design, customization, technical implementation, testing, and refinement.

Results: The pipeline successfully generated integrated risk scores for >10,000 females. Of these, 3.6% were classified as high-risk (≥25% lifetime risk), and 0.9% harbored rare pathogenic variants in BRCA1, BRCA2, PALB2, or PTEN. High PRS only scores were identified in 5.6% of participants. Among those with high PRS, 34% also had high-risk based on integrated scores. API and User Interface (UI) results were highly concordant, with an average difference of 0.13%.

Discussion: Key challenges included integrating diverse data sources, handling missing data, and standardizing pedigree formats. Risk classification discrepancies highlighted the need for refined communication strategies.

Conclusion: This study demonstrates the feasibility of PRS-integrated breast cancer risk assessment in clinical settings but underscores challenges in data integration and risk communication. Future work should enhance recalibration for diverse populations and streamline workflows for risk interpretation and update.

Figure 1.. Swanlane diagram illustrating the overview of stakeholders and implementation activities.

Different colors/lanes represent distinct stakeholders. Each box indicates a specific task involved in the overall implementation process. Dashed boxes denote iterative processes.

Figure 2.. Finalized standard operating procedure (SOP) for the risk generation, review, validation, and return process.

The entire procedure is composed of multiple phases (different colors) and includes five checkpoints (diamond-shaped boxes). Phase 1: Before API query, the participant must have sex assigned as female at birth, 18 years and old, and provided baseline height and weight. If MeTree data are unavailable, the site’s research staff acknowledged its absence, and in such cases, the R⁴ extension generated a placeholder pedigree containing only healthy parents (father and mother). Other missing data (e.g. PRS) were permissible. For a successful API risk generation, the participant must have no prior breast cancer history recorded in the MeTree, and no monozygotic twins; Phase 2: Borderline cases were review. Sites then verified that data from Broad, Invitae, MeTree, and other sources was reviewed and approved before generating the GIRA report, which includes conditions beyond breast cancer risk. Phase 3: Sites implemented their own high-risk return protocols to communicate risk to participants and their healthcare providers. If additional information (e.g., from the EHR) revealed a prior history of breast cancer, sites were instructed not to return a high-risk breast cancer result.