Digital Biomarkers to Improve Prediction and Understanding of Chronic Post-Surgical Pain following Breast Cancer Surgery

American Cancer Society Research Grant, #IRG-21-136-36-IRG

5/1/2025 – 12/31/2026

Madelyn R. Frumkin, PhD (Dartmouth College)

Devan Jones (CTBH)

The goal of the study is to capture and validate digital biomarkers of risk and resiliency for chronic post-surgical pain (CPSP) after breast cancer surgery. Excluding skin cancer, breast cancer is the most common malignancy in women worldwide. Although most patients survive breast cancer, CPSP is reported by up to 35% of patients, limiting quality of life and increasing risk of chronic opioid use. Several models have been developed to predict CPSP after breast cancer surgery. However, most have poor to modest discriminative ability and high risk of bias, limiting opportunities for prevention.

Dr. Frumkin’s research has demonstrated the feasibility and prognostic utility of leveraging digital health data to improve prediction of CPSP. Smartphone-based assessment of subjective symptoms reduces recall bias and facilitates development of novel features unavailable from traditional, one-time assessments (e.g., symptom dynamics). Additionally, smartphones and wearable devices collect objective data on physical activity, sleep, and physiological reactivity—factors that are hypothesized to play an important role in CPSP but have thus far been assessed primarily via self-report, which shows very poor agreement with objective monitoring.

This study will adopt a mixed-methods, user-centered design approach to develop, test, and refine a digital health application for perioperative monitoring in breast cancer patients. The app will collect both ecological momentary assessments (EMA) and passive digital health data to capture real-time, in-the-moment data regarding patients’ physical and psychological states. In Aim 1, we will use an iterative, user-centered design process to develop a smartphone application that addresses the preferences, needs, and perceived barriers of perioperative monitoring in patients undergoing breast cancer surgery. In Aim 2, we will pilot the app in patients undergoing surgery to assess feasibility and acceptability. In Aim 3, we will develop a pipeline for extraction of candidate digital biomarkers. We will additionally collect outcome data to preliminarily examine associations between CPSP and candidate digital biomarkers.

Breast cancer accounts for 1 in 3 new cancer diagnoses in women. Although treatment is often curative, up to 35% of patients report persistent pain at least 3 months after breast cancer surgery, and 10-18% of opioid-naïve patients report new-onset persistent opioid use. Prevention of CPSP is therefore critical to promoting survivorship.