Late distant recurrence prediction model in premenopausal women with ER-positive/HER 2-negative breast cancer: A multicenter retrospective study
The machine-learning model effectively stratified patients into distinct DR risk groups and highlighted the benefit of extended ET in high-risk patients. This model supports tailored decision-making regarding extended ET in premenopausal patients with ER-positive/HER2-negative breast cancer.
Authors
- Dasom Noh (ORCID: https://orcid.org/0009-0008-8021-2295)
- Soong June Bae (ORCID: https://orcid.org/0000-0002-0012-9694)
- Dong Seung Shin (ORCID: https://orcid.org/0000-0001-8915-8944)
- Janghee Lee
- Yeongyeong Son
- Jai Min Ryu
- Sunyoung Kwon
- Eunhye Kang
- Jong-Ho Cheun
- Sung Gwe Ahn
- Han-Byoel Lee
- Jun-Hee Lee
Institutions
- Ewha Womans University (KR)
- Seoul National University (KR)
- Yonsei University (KR)
- Seoul Metropolitan Government (KR)
- Soonchunhyang University Hospital Seoul (KR)
- Samsung Medical Center (KR)
- Seoul National University Hospital (KR)
- SNUH SMG-SNU Boramae Medical Center (KR)
- Gangnam Severance Hospital (KR)
- Pusan National University (KR)
- Sungkyunkwan University (KR)
Publication Details
- Journal
- The Breast
- Published
- 2026-02-14
- DOI
- https://doi.org/10.1016/j.breast.2026.104738
- Primary Topic
- Breast Cancer Treatment Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00