# Using Modifiable Risk Factors to Predict Inferior Care and Survival after Breast Cancer Diagnosis: A Novel Approach to Addressing Health Disparities

> **NIH NIH K08** · UNIVERSITY OF PENNSYLVANIA · 2021 · $194,446

## Abstract

RESEARCH SUMMARY / ABSTRACT
Despite overall declines in breast cancer mortality in the United States, significant disparities in breast cancer
treatment and outcomes persist. Access-related, biological, psychosocial, and provider-specific factors
previously demonstrated to be associated with disparities after breast cancer diagnosis are, on the whole,
static systemic or individual features that are difficult or impossible to change. As an alternative approach to
addressing disparities in breast cancer, we propose creating a risk prediction model for Breast cancer Risk of
Inferior Survival and Care (BRISC) that incorporates dynamic, modifiable risk factors to identify women at
greatest risk for compromised care and worse survival after diagnosis with breast cancer. After development
and validation, we will use the BRISC model to conduct statistical simulations and costing activities to estimate
the improvement in value (i.e., outcomes achieved per health-care dollar spent) achieved via implementation of
high-impact, risk-modifying interventions to facilitate receipt of guideline-concordant breast cancer treatment.
Finally, we will develop a parsimonious, clinic-based data collection tool to be completed by patients and
providers for the purpose of operationalizing the BRISC model as a component of routine oncologic care.

## Key facts

- **NIH application ID:** 10462957
- **Project number:** 7K08CA241390-03
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Oluwadamilola M. Fayanju
- **Activity code:** K08 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $194,446
- **Award type:** 7
- **Project period:** 2021-08-06 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10462957

## Citation

> US National Institutes of Health, RePORTER application 10462957, Using Modifiable Risk Factors to Predict Inferior Care and Survival after Breast Cancer Diagnosis: A Novel Approach to Addressing Health Disparities (7K08CA241390-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10462957. Licensed CC0.

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