Multimodal recurrence risk prediction model for HR+/HER2- early breast cancer following adjuvant chemo-endocrine therapy: integrating pathology image and clinicalpathological features
Our multimodal recurrence risk prediction model is a practical and reliable tool that enhances the predictive power of existing systems relying solely on clinicopathological parameters. It offers improved recurrence risk prediction for HR+/HER2- EBC patients following adjuvant C-ET, supporting personalized treatment and better patient outcomes.
Authors
- Yiman Li (ORCID: https://orcid.org/0000-0003-0595-3401)
- Ji‐Long Chen (ORCID: https://orcid.org/0000-0002-4274-0563)
- Xun‐Xi Lu (ORCID: https://orcid.org/0000-0002-5118-0377)
- Yuhao Yi (ORCID: https://orcid.org/0000-0001-6036-0276)
- Wenchuan Zhang (ORCID: https://orcid.org/0000-0001-9632-6424)
- Jie Chen (ORCID: https://orcid.org/0000-0003-2780-5426)
- Xiaoyan Wu (ORCID: https://orcid.org/0000-0002-8054-4109)
- Min Zhu (ORCID: https://orcid.org/0000-0001-6614-606X)
- Xiaorong Zhong
- Hong Bu (ORCID: https://orcid.org/0000-0001-7472-6443)
Institutions
- Sichuan University (CN)
- West China Hospital of Sichuan University (CN)
Publication Details
- Journal
- Breast Cancer Research
- Published
- 2025-03-28
- DOI
- https://doi.org/10.1186/s13058-025-01968-0
- Citations
- 9
- Primary Topic
- Breast Cancer Treatment Studies
- Type
- article
- Field-Weighted Citation Impact
- 8.43
Funders
- Sichuan University
- West China Hospital, Sichuan University