Risk-stratified Distant Metastatic Thyroid Cancer with Clinicopathological Factors and BRAF/TERT Promoter Mutations.

Xian Cheng, Ying Zhou, Shichen Xu, Huixin Yu, Jing Wu, Jiandong Bao, Li Zhang
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Abstract

Objective: To assess the prognostic value of clinicopathological factors as well as BRAF and TERT promoter mutations in predicting distant metastasis in patients with papillary thyroid cancer.

Design: The status of BRAF and TERTp mutations were available in 1,208 thyroid cancer patients who received thyroidectomy at Jiangyuan Hospital Affiliated to Jiangsu Institute of Nuclear Medicine from January 2008 to December 2021. Based on inclusion criteria, 99 distant metastasis thyroid cancers (DM-TCs) and 1055 patients without DM (Non-DM-TCs) were retrospectively reviewed.

Results: After univariate and multivariate analyses, a risk model was established for DM prediction based on factors: T3/T4 stage, lymph node metastasis (LNM) number over 5, and BRAF/TERT mutations (TLBT). It was defined based on the number of TLBT factors: low risk (no risk factor, n=896), intermediate risk (1 risk factor, n=199), and high risk (≥2 risk factors, n=59). Notably, compared with patients with low and intermediate risks, patients assigned to high TLBT risk have a shorter time of DM disease-free survival. Except for gene mutation, other factors were also included in the 2015 American Thyroid Association (ATA) risk guideline. Comparing with the ATA risk category, this risk model showed a better performance in predicting DM-TCs.

Conclusions: This study proposes a TLBT risk classifier consisting of T3/T4 stages, LNM (n>5), and BRAF+TERTp mutations for predicting DM-TCs. TLBT risk stratification may help clinicians make personalized treatment management and follow-up strategies.

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具有临床病理因素和BRAF/TERT启动子突变的风险分层远距转移性癌症。
目的:评估临床病理因素以及BRAF和TERT启动子突变在预测癌症远处转移中的预后价值。设计:对2008年1月至2021年12月在江苏省核医学研究所附属江源医院接受甲状腺切除术的1208例甲状腺癌症患者进行BRAF和TERTp突变检测。根据纳入标准,对99例远处转移甲状腺癌(DM TC)和1055例无DM(非DM TC)患者进行了回顾性分析。结果:经过单因素和多因素分析,建立了基于以下因素的糖尿病预测风险模型:T3/T4分期、5以上淋巴结转移(LNM)数和BRAF/TERT突变(TLBT)。它是根据TLBT因素的数量定义的:低风险(无风险因素,n=896)、中等风险(1个风险因素,n=199)和高风险(≥2个危险因素,n=59)。值得注意的是,与低风险和中风险患者相比,TLBT高风险患者的DM无病生存时间更短。除基因突变外,其他因素也被纳入2015年美国甲状腺协会(ATA)风险指南。与ATA风险类别相比,该风险模型在预测DM-TCs方面表现出更好的性能。结论:本研究提出了一种由T3/T4期、LNM(n>5)和BRAF+TERTp突变组成的TLBT风险分类器,用于预测DM-TCs。TLBT风险分层可以帮助临床医生制定个性化的治疗管理和随访策略。
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