Role of urinary leukocytes in the risk stratification of prostate cancer using nonlinear stacking learning strategy: a bi-cohort diagnostic study
Within a stacking ensemble-based risk stratification framework primarily optimized for predictive performance, urinary leukocytes provide a clinically meaningful auxiliary signal that improves discrimination and net benefit in specific PSA-defined subgroups. These findings support the use of UL as a complementary inflammation-related marker in PCa risk assessment, while interpretability is best understood at the level of base learners and original clinical features rather than the full ensemble model.
Authors
- Chunguang Yang (ORCID: https://orcid.org/0000-0002-3882-4940)
- Hao Zhu (ORCID: https://orcid.org/0000-0003-2809-1111)
- Mengzhe Cheng
- Zhenchun Ran
- Shou Xia
- Xinglong Wu
Institutions
- Xi'an Polytechnic University (CN)
- Cohu (United States) (US)
- Hubei University of Science and Technology (CN)
- Tongji Hospital (CN)
- Artificial Intelligence in Medicine (Canada) (CA)
- Huazhong University of Science and Technology (CN)
- Wuhan Institute of Technology (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2026-03-02
- DOI
- https://doi.org/10.3389/fonc.2026.1762494
- Primary Topic
- Prostate Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Huazhong University of Science and Technology
- Tongji University
- Tongji Medical College, Huazhong University of Science and Technology