Abstract PS1-11-08: Integrative modeling of multimodal real-world data for improved risk stratification of first-line CDK4/6 inhibitor outcomes in patients with estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer

Clinical Cancer Research 2026

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Authors: Francisco Sánchez-Vega, Subhiksha Nandakumar, Gráinne H. Long, Walid Khaled Chatila, Sameet Sreenivasan, Maureen Carey, Mohamed Reda Keddar, Jessica Davies, Matthew Zatzman, M. Miller, Elza C. de Bruin, Sajan Khosla
+7 more N. Ceglia, Hannah Lees, Fatema Nagib, Yixuan Gong, Mark T.A. Donoghue, Nicholaus Schultz, S. Shah
DOI: 10.1158/1557-3265.sabcs25-ps1-11-08
Cited by: 0

Abstract

Abstract Background: CDK4/6 inhibitor in combination with endocrine therapy is a cornerstone of treatment for hormone receptor-positive metastatic breast cancer. We developed a machine learning model that used clinical, genomic, and transcriptomic features to stratify patients based on response to first-line CDK4/6 inhibitor treatment and identify predictors of response. Methods: Patients with ER-positive/HER2-negative metastatic breast cancer, biopsy samples from before or

Fields of Study & Subjects

Advanced Breast Cancer Therapies Breast Cancer Treatment Studies Cancer Genomics and Diagnostics

Publication details

Journal / source
Clinical Cancer Research
Volume
32
Issue
4_Supplement
Pages
PS1–11
Publication date
17 February 2026
Language
EN