Development and validation of an integrative 54 biomarker-based risk identification model for multi-cancer in 42,666 individuals: a population-based prospective study to guide advanced screening strategies
This is the first population-based prospective study in a large Chinese cohort that leverage multi-scale data including biomarkers for multi-cancer risk prediction. Our effective risk stratification model not only enhances early cancer detection but also lays the foundation for the targeted application of advanced screening methods, including but not limited to multi-omics technologies and endoscopy. These findings support precision prevention strategies and the optimal allocation of healthcare resources.
Authors
- Zhenqiu Liu (ORCID: https://orcid.org/0000-0002-5244-6894)
- Linyao Lu (ORCID: https://orcid.org/0000-0001-8849-6626)
- Huangbo Yuan (ORCID: https://orcid.org/0000-0002-7065-2974)
- Kelin Xu (ORCID: https://orcid.org/0000-0002-6788-4256)
- Zhixi Su (ORCID: https://orcid.org/0000-0002-4881-1238)
- Renjia Zhao (ORCID: https://orcid.org/0000-0002-1908-8941)
- Xingdong Chen (ORCID: https://orcid.org/0000-0003-3763-160X)
- Chen Suo (ORCID: https://orcid.org/0000-0002-5274-4584)
- Ming‐Chi Lu (ORCID: https://orcid.org/0000-0001-9051-0351)
- Yanfeng Jiang (ORCID: https://orcid.org/0000-0003-4976-6333)
- Jin Li (ORCID: https://orcid.org/0000-0001-9201-2321)
- Shuo Wang (ORCID: https://orcid.org/0000-0003-4297-9897)
- Rui Liu (ORCID: https://orcid.org/0000-0002-1642-1243)
- Weimin Ye (ORCID: https://orcid.org/0000-0002-6859-4648)
- Qiye He (ORCID: https://orcid.org/0000-0002-7990-8606)
- Ziyu Yuan (ORCID: https://orcid.org/0000-0003-1434-0383)
- Ruilin Chen
- Tiejun Zhang
Institutions
- Fudan University (CN)
- Karolinska Institutet (SE)
- Shanghai Public Health Clinical Center (CN)
- Sinotech Genomics (China) (CN)
- Yiwu Science and Technology Research Institute (CN)
- Huashan Hospital (CN)
- Qilu Hospital of Shandong University (CN)
- Taizhou University (CN)
Publication Details
- Journal
- Biomarker Research
- Published
- 2025-08-11
- DOI
- https://doi.org/10.1186/s40364-025-00812-z
- Citations
- 4
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 5.44
Funders
- National Natural Science Foundation of China
- Fudan University
- Centers for Disease Control and Prevention