FHIR-Enhanced RealRisks to Improve Accuracy of Breast Cancer Risk Assessments

Completed · Not applicable

Conditions studied: Breast Cancer

In brief

Electronic health records (EHRs) are an increasingly common source for populating risk models, but whether used to populate validated risk assessment models or to de-facto build risk prediction models, EHR data presents several challenges. The purpose of this study is to assess how the integration of patient generated health data (PGHD) and EHR data can generate more accurate risk prediction models, advance personalized cancer prevention, improve digital access to health data in an equitable manner, and advance policy goals for Patient Generated Health Data (PGHD) and EHR interoperability.

Key facts

Study ID

NCT05810025

Run by

Columbia University

People needed

70

Starts

2023-05-01

Expected to finish

2025-12-31

Last updated by the study team

2026-02-11

Who can join

Age: 35 and older, up to 74. Sex: female. Healthy volunteers: accepted.

You may qualify if…

• Women, age 35-74 years
• High-risk defined as 5-year invasive breast cancer risk ≥1.7% or 10 risk ≥20% according to the BCSC or GAIL models
• English- or Spanish-speaking
• Able to sign informed consent.

You may not qualify if…

• Women with a personal history of breast cancer
• Women who previously participated in a sub-study (Aim 1) of the awarded grant.

Where it is running

• Columbia University Irving Medical Center — New York, New York, United States

Full record on ClinicalTrials.gov

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