An Interpretable Machine-Learning Model for Predicting Occult Central Lymph Node Metastasis in Papillary Thyroid Cancer
This is the first study to identify RET fusion positivity as an independent OLNM risk factor in cN0 PTC. The developed RF model demonstrates moderate predictive performance for OLNM risk and provides a framework for integrating clinical, sonographic, and molecular data, and is deployed as a web calculator (https://predictingoccultlymphnodemetastasis.shinyapps.io/web3/).
Authors
- Xianglan Zhu
- Qiuli Li (ORCID: https://orcid.org/0000-0002-0664-0725)
- Yongyan Zhang (ORCID: https://orcid.org/0000-0001-6777-7808)
- Ke Jiang (ORCID: https://orcid.org/0000-0003-3808-111X)
- Yin Li (ORCID: https://orcid.org/0000-0002-4754-2814)
- Yin Li (ORCID: https://orcid.org/0000-0002-7102-323X)
- Jiahe Tian (ORCID: https://orcid.org/0000-0001-8656-0276)
- Sheng Yang (ORCID: https://orcid.org/0000-0001-7367-0388)
- Ang Hu (ORCID: https://orcid.org/0000-0003-2853-2984)
- Ruonan Liu (ORCID: https://orcid.org/0000-0002-7949-8969)
- Zhongyu Wang (ORCID: https://orcid.org/0009-0004-2672-1559)
Institutions
- Guiyang Medical University (CN)
- Sun Yat-sen University (CN)
- Sun Yat-sen Memorial Hospital (CN)
- Affiliated Hospital of Guizhou Medical University (CN)
- Sun Yat-sen University Cancer Center (CN)
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- The Journal of Clinical Endocrinology & Metabolism
- Published
- 2025-11-23
- DOI
- https://doi.org/10.1210/clinem/dgaf636
- Citations
- 2
- Primary Topic
- Thyroid Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 2.59