Prognostic value of an MRI-derived recurrence assay in women with hormone receptor–positive, HER2-negative breast cancer: A retrospective, multi-center analysis.

M Matthew P. Goetz Q Qinmei Xu V Vincent Reid H Hari Trivedi R Rohan Isaac (Emory University School of Medicine, Atlanta, GA) D David Zahrieh (Mayo Clinic Rochester, Rochester, MN) T Tanya L. Hoskin (Mayo Clinic Rochester, Rochester, MN) J Jordan Campbell (Mayo Clinic Rochester, Rochester, MN) V Vignesh Kannan B Bradley Feiger (SimBioSys, Inc., Chicago, IL) D Daniel Cook (SimBioSys, Inc., Chicago, IL) J Joseph R. Peterson (SimBioSys, Inc., Chicago, IL) J Judy Caroline Boughey (Mayo Clinic Rochester, Rochester, MN) H Haruka Itakura (Stanford University School of Medicine, Stanford, CA)

Abstract

560 Background: Patients (pts) with early stage hormone receptor-positive, human epidermal growth factor receptor 2-negative (HR+/HER2-) breast cancer (BC) remain at both short and long term risk of recurrence. While clinico-pathological and gene-based biomarkers provide insight into early and late recurrence risk, additional prognostic tools are needed. We previously developed (Saha et al. Clin Cancer Res , 2025) a new breast MRI image-based artificial intelligence prognostic tool (TumorSight Risk) composed of both radiographic and clinical information. Here we sought to validate this tool in an independent cohort. Methods: In this multi-center, blinded, prospective/retrospective validation study, we sought to validate the 5-year recurrence-free survival (RFS) according to pre-defined risk scores (0-100) and categories (“high” or “low”) via pre-specified cutoff (≥47) for pts with HR+/HER2- BC. Kaplan-Meier and Cox regression analyses were then used to assess the unadjusted and adjusted association between risk category/score and the 5-year RFS. Results: 2,129 pts with HR+/HER2- BC diagnosed between January 1, 2010, and December 31, 2024, who underwent breast MRI prior to surgery (no neoadjuvant therapy) were included from four institutions. Median age was 57 years, 16% were Black, 15% had grade 3 disease, 93% were clinical T1 or T2, and 85%/15% were clinical N0/N1. At a median follow up of 6.24 years, the unadjusted hazard ratio (HR) for RFS comparing low (n=1808) and high risk (n=321) pts was 2.71 (95% CI = 1.95 – 3.76, p = 3x10 -9 ). The estimated 5 year RFS rate according to risk score (low and high) was 95.5% (95% CI: 94.63 – 96.3%) and 89.6% (95% CI = 86.4 – 92.6%) while the 10 year RFS estimates were 88.9% (95% CI = 86.5 - 90.9%) and 69.6% (95% CI = 59.1 – 77.9%). Univariate subgroup analysis demonstrated that the risk score was prognostic by age (< 50 vs. ≥50 years), pathologic nodal status, grade, and surgery type, regardless of chemo-, endocrine, or radiation therapy administration. The observed continuous risk score was strongly associated with risk of recurrence, with a 22% increase in relative risk per 10-unit change in risk score (0-100), translating to a 2.4% (95% CI = 1.2 – 4.5%) and 25.5% (95% CI = 15.4 – 40.4%) risk of recurrence at 5-years for pts at the lowest (0-9) versus highest (90-100) risk score. The prognostic association between risk score and RFS remained after adjusting for pathologic T- and N-stage, grade, age, race, and treatment (p = 0.002). Conclusions: TumorSight Risk is a new image-based biomarker for HR+/HER2- BC that provides prognostic information independent of standard clinico-pathological parameters. Given the ready availability of breast MRI in most pts with BC, TumorSight Risk may be a convenient tool for estimating risk for recurrence.

Article Details

Volume / Issue Vol. 44, Issue 16_suppl
Published June 01, 2026
Pages 560-560
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (14)

M

Matthew P. Goetz

Q

Qinmei Xu

V

Vincent Reid

H

Hari Trivedi

R

Rohan Isaac

Emory University School of Medicine, Atlanta, GA

D

David Zahrieh

Mayo Clinic Rochester, Rochester, MN

T

Tanya L. Hoskin

Mayo Clinic Rochester, Rochester, MN

J

Jordan Campbell

Mayo Clinic Rochester, Rochester, MN

V

Vignesh Kannan

B

Bradley Feiger

SimBioSys, Inc., Chicago, IL

D

Daniel Cook

SimBioSys, Inc., Chicago, IL

J

Joseph R. Peterson

SimBioSys, Inc., Chicago, IL

J

Judy Caroline Boughey

Mayo Clinic Rochester, Rochester, MN

H

Haruka Itakura

Stanford University School of Medicine, Stanford, CA