外科理论与实践2026，Vol.31Issue(4)：279-286,8.DOI:10.16139/j.1007-9610.2026.04.01
从病例规模到学习型体系:甲状腺肿瘤学科建设的路径与展望
From case volume to learning systems:pathways and prospects for thyroid oncology discipline development
摘要
Abstract
In recent years,the incidence of thyroid cancer in China has risen steadily,rendering it one of the most rapidly increasing solid malignancies nationwide.Relative to Western populations,China confronts a"dual disease burden":a substantial cohort of patients with low-risk papillary thyroid carcinoma coexists alongside pressing clinical needs for effective management of advanced and high-risk disease.Consequently,implementing risk-stratified management for low-risk patients—while delivering intensified,multimodal therapeutic strategies for high-risk cases—has emerged as a pivotal challenge in advancing thyroid oncology in China.This article presented a systematic review of the evolution of thyroid tumor disciplines in China,synthesizing cutting-edge domestic and international research evidence alongside recent institutional innovations at Fudan University Shanghai Cancer Center.It underscored four critical enablers of discipline advancement:(1)high-quality,standardized clinical databases and biobanks as foundational infrastructure;(2)artificial intelligence(AI)-driven enhancements in data curation,dynamic risk stratification,and longitudinal care coordination;(3)neoadjuvant therapy as an integral pillar of precision medicine for locally advanced or high-risk thyroid cancer;and(4)robust multidisciplinary collaboration and scalable national research networks as essential organizational frameworks for investigating rare and aggressive subtypes.Looking ahead,China is well positioned to adapt proven translational research paradigms from lung and breast cancer—particularly those grounded in learning health systems—to establish a data-informed,multidisciplinary collaboration,and iteratively refined learning health system of precision medicine,thereby contributing a distinctive,evidence-based Chinese model for optimized diagnosis and treatment for thyroid cancer.关键词
甲状腺癌/精准诊疗/数据库/人工智能/多学科协作/学习型医疗体系Key words
Thyroid cancer/Precision medicine/Database/Artificial intelligence(AI)/Multidisciplinary collaboration/Learning health system分类
医药卫生引用本文复制引用
王宇..从病例规模到学习型体系:甲状腺肿瘤学科建设的路径与展望[J].外科理论与实践,2026,31(4):279-286,8.基金项目
国家科技重大专项(四大慢病重大专项)(2024ZD0525600) （四大慢病重大专项）
国家自然科学基金(82473361) （82473361）
上海市科学技术委员会上海市2025年度科技产业高质量发展计划(25SF1900700) （25SF1900700）
上海申康医院发展中心上海临床队列项目(SHDC2025CCS028) （SHDC2025CCS028）
上海申康医院发展中心促进市级医院临床技能与临床创新三年行动计划(SHDC2020CR6003) （SHDC2020CR6003）
上海申康医院发展中心诊疗技术推广及优化管理项目(SHDC22025203) （SHDC22025203）
上海市抗癌协会翱翔计划(SACA-AX202404) （SACA-AX202404）
上海市徐汇区卫生健康委员会、徐汇区科学技术委员会院地合作项目(生命健康领域)(25XHYD-11) （生命健康领域）
