RealRisks for Breast Cancer Risk Assessment

(FHIR Trial)

Overseen By Katherine Crew, MD, MS

Age: 18+

Sex: Female

Trial Phase: Academic

Sponsor: Columbia University

Disqualifiers: History of breast cancer, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Approved in 1 Jurisdiction This treatment is already approved in other countries

Compensation: Varies

Number of Visits: 1

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial aims to determine if combining patient-generated health data with electronic health records enhances the accuracy of breast cancer risk predictions. The study targets women at high risk of developing invasive breast cancer within the next 5 to 10 years, identified through specific medical models. Participants will use an enhanced tool called RealRisks, featuring interactive elements and educational modules on breast cancer prevention. Women aged 35 to 74, who have never had breast cancer, speak English or Spanish, and have a high predicted risk, are suitable candidates for this trial. As an unphased trial, it offers participants the chance to contribute to innovative research that could improve breast cancer risk prediction for future patients.

Will I have to stop taking my current medications?

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

What prior data suggests that this method is safe for breast cancer risk assessment?

Research has shown that RealRisks helps people understand their chances of developing breast cancer. It uses the information provided to estimate this risk. Users have found it useful for learning about breast cancer risk and prevention options.

No reports indicate that RealRisks causes harm. It primarily provides information and aids in decision-making. As it is not a medicine or medical procedure, it does not carry the same risks as those treatments.

Participants in other studies of RealRisks have not reported serious side effects, suggesting it is safe to use. However, it is important to use the tool as directed and consult a healthcare provider if any concerns arise. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about the RealRisks trial because it offers a novel approach to breast cancer risk assessment. Unlike traditional methods that rely solely on clinical consultations, RealRisks empowers participants with interactive tools, like risk communication games and personalized family history analysis. This approach not only helps in understanding one's risk but also actively involves individuals in their healthcare decisions through modules on chemoprevention and genetic testing. The goal is to enhance patient activation and provide immediate feedback on outcomes, potentially leading to more informed and proactive health management.

What evidence suggests that the RealRisks method is effective for breast cancer risk assessment?

Research has shown that RealRisks, the tool under study in this trial, can help people better understand their chances of developing breast cancer. In one study, users of RealRisks gained a clearer understanding of their breast cancer risk. Another study found that RealRisks altered how people perceived their risk of breast cancer. The tool uses details like age, medical history, and genetic factors to provide personalized risk assessments. It also allows users to interact with their health records and update information, which can enhance the accuracy of risk predictions. ^{1 6 7 8 9}

Who Is on the Research Team?

Rita Kukafka, DrPH, MA

Principal Investigator

Columbia University

Are You a Good Fit for This Trial?

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.

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

Able to sign informed consent.

Exclusion Criteria

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

I have had breast cancer before.

Timeline for a Trial Participant

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

What Are the Treatments Tested in This Trial?

Interventions

• RealRisks

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.

How Is the Trial Designed?

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.

Who Is Running the Clinical Trial?

Columbia University

Lead Sponsor

Trials

1,529

Recruited

2,832,000+

National Institute on Minority Health and Health Disparities (NIMHD)

Collaborator

Trials

473

Recruited

1,374,000+

Published Research Related to This Trial

In a study of 35,921 women aged 40-84 who underwent mammography screening, the BRCAPRO, Gail, Tyrer-Cuzick, and BCSC models showed similar moderate predictive accuracy for breast cancer risk over 6 years, with the Gail model performing slightly better.

All models had lower predictive accuracy for aggressive breast cancer subtypes, suggesting that incorporating more genetic and nongenetic factors could enhance risk prediction for these specific types.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Performance of Breast Cancer Risk-Assessment Models in a Large Mammography Cohort. McCarthy, AM., Guan, Z., Welch, M., et al.[2021]

In a study involving 15,732 women with a median follow-up of 11.1 years, the BOADICEA and IBIS models were found to be well-calibrated for predicting breast cancer risk, while the BRCAPRO and BCRAT models significantly underpredicted risk.

The results indicate that models incorporating multigenerational family history, like BOADICEA and IBIS, are more effective in predicting breast cancer risk, suggesting potential for improved accuracy with hybrid models that combine different risk factors.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

10-year performance of four models of breast cancer risk: a validation study. Terry, MB., Liao, Y., Whittemore, AS., et al.[2020]

The manual adaptation of Claus tables for breast cancer risk assessment was validated with a study of 8,824 women over an average follow-up of 9.71 years, showing accurate predictions of breast cancer incidence with an observed-to-expected ratio of 1.05.

This method provided reliable risk predictions across all age groups, including women in their forties, indicating its effectiveness for individualized risk assessment in clinical settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Breast cancer risk assessment in 8,824 women attending a family history evaluation and screening programme. Evans, DG., Ingham, S., Dawe, S., et al.[2022]

Breast cancer risk assessment helps estimate the likelihood of developing the disease and can identify specific genetic risks, such as BRCA1 or BRCA2 mutations, which is crucial for guiding management strategies.

Recent advancements in risk assessment have led to effective prevention options like Tamoxifen chemoprevention and tailored management for mutation carriers, emphasizing the need for a combination of models and clinical judgment for accurate counseling.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Application of breast cancer risk prediction models in clinical practice. Domchek, SM., Eisen, A., Calzone, K., et al.[2016]

The new CARE model for estimating breast cancer risk in African American women provided higher risk estimates compared to the widely used Breast Cancer Risk Assessment Tool, suggesting it may be more accurate for this population.

In a comparison using eligibility data from the STAR trial, the CARE model identified 30.3% of African American women at a 5-year invasive breast cancer risk of at least 1.66%, significantly higher than the 14.5% identified by the Breast Cancer Risk Assessment Tool.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Projecting individualized absolute invasive breast cancer risk in African American women. Gail, MH., Costantino, JP., Pee, D., et al.[2022]

Citations

1.

pmc.ncbi.nlm.nih.gov

pmc.ncbi.nlm.nih.gov/articles/PMC12099428/

User Comprehension and EHR Integration of the ...

Overall, participants demonstrated an improved understanding of breast cancer risk after using RealRisks. However, challenges were noted for ...

2.

pmc.ncbi.nlm.nih.gov

pmc.ncbi.nlm.nih.gov/articles/PMC9532364/

Patient and Provider Web-Based Decision Support for ...

In an initial pilot study with a pretest-posttest design, exposure to RealRisks was associated with a significant improvement in breast cancer risk perceptions ...

3.

bmccancer.biomedcentral.com

bmccancer.biomedcentral.com/articles/10.1186/s12885-024-13408-x

The breast cancer genetic testing experience: probing the ...

Within RealRisks, a user interface displays their electronic health record (EHR) data to patients, allowing them to review, add and modify their ...

4.

jmir.org

jmir.org/2015/7/e165/

Why Breast Cancer Risk by the Numbers Is Not Enough

Perceived 5-year and lifetime breast cancer risk ranged from 0-100%. After interacting with RealRisks, the difference in perceived and estimated ...

5.

researchgate.net

researchgate.net/figure/RealRisks-dashboard-view_fig1_317078773

RealRisks dashboard view | Download Scientific Diagram

Breast cancer outcomes were personalized based on individual clinical characteristics (e.g., age, medical history), genomic risk factors (e.g., BRCA1/2), race ...

6.

realrisks.dbmi.columbia.edu

realrisks.dbmi.columbia.edu/

RealRisks

Learn about what goes into breast cancer risk. Take a survey to find out your risk and complete an interactive exercise to find out what risk means and how it ...

7.

pmc.ncbi.nlm.nih.gov

pmc.ncbi.nlm.nih.gov/articles/PMC11428070/

A retrospective translational science case study - PMC

This case study investigates the development of RealRisks and Breast Cancer Risk Navigation (BNAV), decision support tools for breast cancer risk assessment,

8.

rtihs.org

rtihs.org/sites/default/files/31263%20Vanegas%202017%20Usability%20testing%20of%20a%20web-based%20decision%20aid%20for%20breast%20cancer%20risk%20assessment%20among%20multi-ethnic%20women.pdf

Usability Testing of a Web-Based Decision Aid for Breast ...

RealRisks is designed to improve users' accuracy of risk perception while presenting them with information about breast cancer risk and chemoprevention options ...

9.

researchgate.net

researchgate.net/figure/Schema-of-the-RealRisks-decision-aid_fig1_280123230

Schema of the RealRisks decision aid.

This case study investigates the development of RealRisks and Breast Cancer Risk Navigation (BNAV), decision support tools for breast cancer risk assessment, ...