RealRisks for Breast Cancer Risk Assessment

(FHIR Trial)

Recruiting in Palo Alto (17 mi)

Overseen by Rita Kukafka, DrPH, MA

Age: 18+

Sex: Female

Travel: May Be Covered

Time Reimbursement: Varies

Trial Phase: Academic

Recruiting

Sponsor: Columbia University

Disqualifiers: History of breast cancer, others

No Placebo Group

Approved in 1 Jurisdiction

Trial Summary

What is the purpose of this trial?

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.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications.

How does the RealRisks treatment for breast cancer risk assessment differ from other treatments?

The RealRisks treatment is unique because it focuses on assessing individual breast cancer risk using various models, which helps guide prevention and screening decisions. Unlike standard treatments that directly target cancer, this approach emphasizes personalized risk evaluation to inform potential preventive measures. ^{1 2 3 4 5}

Eligibility Criteria

This trial is for women aged 35-74 who are at high risk of breast cancer, with a predicted 5-year invasive risk of ≥1.7% or lifetime risk ≥20%. Participants must speak English or Spanish and be able to give informed consent. Women with a personal history of breast cancer or those who took part in a related sub-study cannot join.

Inclusion Criteria

I am a woman aged between 35 and 74.

I speak English or Spanish.

My risk of developing invasive breast cancer is high according to risk models.

Exclusion Criteria

I was part of the initial study group for this research.

I have had breast cancer before.

Trial Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Pre-Study Evaluation

Participants undergo pre-study evaluations including user evaluations to refine FHIR-enhanced RealRisks

2 weeks

Intervention

Participants self-administer FHIR-enhanced RealRisks with access to risk communication games, family history pedigree, and modules on chemoprevention and genetics testing

2 weeks

1 visit (virtual)

Follow-up

Participants are monitored for accuracy of breast cancer risk perception and patient activation

2 weeks

Treatment Details

Interventions

• RealRisks (Behavioral)

Trial Overview The study is testing 'RealRisks', which combines patient health data from electronic records and patient-generated info to improve the accuracy of breast cancer risk assessments, aiming to personalize prevention strategies and enhance digital health data access.

Participant Groups

Group I: FHIR-Enhanced RealRisks Experimental Treatment 1 Intervention

Participants will self-administer FHIR-enhanced RealRisks with access to risk communication games, family history pedigree and modules on chemoprevention and genetics testing, if relevant to them based on their risk and family history. The investigators are interested in gaining short-term feedback on patient activation and other patient reported outcomes, which will be assessed before and within 2 weeks after using RealRisks.

Find a Clinic Near You

Research Locations Nearby Select from list below to view details:

Columbia University Irving Medical Center New York, NY

Who Is Running the Clinical Trial?

Columbia University Lead Sponsor

National Institute on Minority Health and Health Disparities (NIMHD) Collaborator

References

1. United States pubmed.ncbi.nlm.nih.gov

Performance of Breast Cancer Risk-Assessment Models in a Large Mammography Cohort. [2021] Several breast cancer risk-assessment models exist. Few studies have evaluated predictive accuracy of multiple models in large screening populations.

2. England pubmed.ncbi.nlm.nih.gov

10-year performance of four models of breast cancer risk: a validation study. [2020] Independent validation is essential to justify use of models of breast cancer risk prediction and inform decisions about prevention options and screening. Few independent validations had been done using cohorts for common breast cancer risk prediction models, and those that have been done had small sample sizes and short follow-up periods, and used earlier versions of the prediction tools. We aimed to validate the relative performance of four commonly used models of breast cancer risk and assess the effect of limited data input on each one's performance.

3. Netherlands pubmed.ncbi.nlm.nih.gov

Breast cancer risk assessment in 8,824 women attending a family history evaluation and screening programme. [2022] Accurate individualized breast cancer risk assessment is essential to provide risk-benefit analysis prior to initiating interventions designed to lower breast cancer risk and start surveillance. We have previously shown that a manual adaptation of Claus tables was as accurate as the Tyrer-Cuzick model and more accurate at predicting breast cancer than the Gail, Claus model and Ford models. Here we reassess the manual model with longer follow up and higher numbers of cancers. Calibration of the manual model was assessed using data from 8,824 women attending the family history evaluation and screening programme in Manchester UK, with a mean follow up of 9.71 years. After exclusion of 40 prevalent cancers, 406 incident breast cancers occurred, and 385.1 were predicted (O/E = 1.05, 95 % CI 0.95-1.16) using the manual model. Predictions were close to that of observed cancers in all risk categories and in all age groups, including women in their forties (O/E = 0.99, 95 % CI 0.83-1.16). Manual risk prediction with use of adjusted Claus tables and curves with modest adjustment for hormonal and reproductive factors was a well-calibrated approach to breast cancer risk estimation in a UK family history clinic.

4. United States pubmed.ncbi.nlm.nih.gov

Application of breast cancer risk prediction models in clinical practice. [2016] Breast cancer risk assessment provides an estimation of disease risk that can be used to guide management for women at all levels of risk. In addition, the likelihood that breast cancer risk is due to specific genetic susceptibility (such as BRCA1 or BRCA2 mutations) can be determined. Recent developments have reinforced the clinical importance of breast cancer risk assessment. Tamoxifen chemoprevention as well as prevention studies such as the Study of Tamoxifen and Raloxifene are available to women at increased risk of developing breast cancer. In addition, specific management strategies are now defined for BRCA1 and BRCA2 mutation carriers. Risk may be assessed as the likelihood of developing breast cancer (using risk assessment models) or as the likelihood of detecting a BRCA1 or BRCA2 mutation (using prior probability models). Each of the models has advantages and disadvantages, and all need to be interpreted in context. We review available risk assessment tools and discuss their application. As illustrated by clinical examples, optimal counseling may require the use of several models, as well as clinical judgment, to provide the most accurate and useful information to women and their families.

5. United States pubmed.ncbi.nlm.nih.gov

Projecting individualized absolute invasive breast cancer risk in African American women. [2022] The Breast Cancer Risk Assessment Tool of the National Cancer Institute (NCI) is widely used for counseling and determining eligibility for breast cancer prevention trials, although its validity for projecting risk in African American women is uncertain. We developed a model for projecting absolute risk of invasive breast cancer in African American women and compared its projections with those from the Breast Cancer Risk Assessment Tool.