A predictive model for L-T4 dose in postoperative DTC after RAI therapy and its clinical validation in two institutions
The constructed SVR model can effectively predict the L-T4 dose for postoperative DTC after RAI therapy, thus shortening the time to achieve TSH target level and improving the quality of life for DTC patients.
Authors
- Qian Su (ORCID: https://orcid.org/0000-0001-5749-4636)
- Wengui Xu (ORCID: https://orcid.org/0000-0001-6669-1471)
- Jianjing Liu
- Libo Zhang (ORCID: https://orcid.org/0000-0002-8705-0435)
- Xiaofeng Li (ORCID: https://orcid.org/0000-0002-4115-3287)
- Yan Li (ORCID: https://orcid.org/0000-0002-6857-9464)
- Jie Fu (ORCID: https://orcid.org/0000-0001-5864-3488)
- Dong Dai (ORCID: https://orcid.org/0000-0003-1278-5581)
- Ziyang Wang (ORCID: https://orcid.org/0000-0003-1656-0638)
- Xiaoying Ma
- Xue-Yao Liu
- Guo-Tao Yin
- Yuan-Fang Yue
- Zhao Yang
- Li-Na Tong
Institutions
- Tianjin Medical University Cancer Institute and Hospital (CN)
- Qilu Hospital of Shandong University (CN)
Publication Details
- Journal
- Frontiers in Endocrinology
- Published
- 2024-08-20
- DOI
- https://doi.org/10.3389/fendo.2024.1425101
- Citations
- 4
- Primary Topic
- Salivary Gland Tumors Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 2.29
Funders
- National Natural Science Foundation of China
- Tianjin Medical University