New Model Helps Oncologists Spot High-Risk Periods in Metastatic Breast Cancer

Researchers at the University of North Carolina have developed a tool that uses routinely collected clinical data to help oncologists identify when patients with metastatic breast cancer are entering a high-risk period near the end of life. The regression-based model, described in a study published in JCO Oncology Practice, was led by Dr. Emily Ray, a medical oncologist at UNC Lineberger Comprehensive Cancer Center.

The tool draws on information already recorded in a patient's electronic health record — including lab results, vital signs, breast cancer subtype and medications — to estimate the probability that a patient with metastatic breast cancer will die within 30 or 90 days. It is derived from a national oncology database of real-world patient data, and unlike existing tools that combine multiple cancer types, it is built specifically for breast cancer.

"The variables most closely correlated with increased risk align with signals clinicians already recognize, like worsening liver function, increased heart rate, rising needs for pain medication and declining ability to care for oneself at home," Ray said. "Any clinician could tell you those are signs that a patient is getting sicker, but sometimes we still miss them and don't do enough to prepare patients and families."

Ray said the tool is intended to prompt earlier conversations about care needs and preferences, and the team now plans further studies on how best to integrate it into routine oncology practice.