您的位置:山东大学 -> 科技期刊社 -> 《山东大学学报(医学版)》

山东大学学报 (医学版) ›› 2022, Vol. 60 ›› Issue (10): 57-61.doi: 10.6040/j.issn.1671-7554.0.2022.0876

• 临床医学 • 上一篇    下一篇

超声引导下细针穿刺和BRAFV600E分子检测在甲状腺癌诊断中的价值

刘燕,曹广磊,陈丽   

  1. 山东大学齐鲁医院内分泌科, 山东 济南 250012
  • 发布日期:2022-09-30
  • 通讯作者: 陈丽. E-mail:chenli3@email.sdu.edu.cn

Ultrasound-guided fine needle aspiration biopsy and BRAFV600E molecular detection in the diagnosis of thyroid cancer

LIU Yan, CAO Guanglei, CHEN Li   

  1. Department of Endocrinology, Qilu Hospital of Shandong University, Jinan 250012, Shandong, China
  • Published:2022-09-30

摘要: 目的 探讨超声引导下细针穿刺细胞学检查(FNAB)和鼠类肉瘤滤过性毒菌致癌同源体B1(BRAF)V600E(BRAFV600E)分子检测在甲状腺癌诊断中的价值。 方法 回顾性分析2019年1月至2021年12月304例甲状腺结节的患者,并行FNAB细胞病理和BRAFV600E分子检测。以术后病理诊断为金标准,分为FNAB组(n=138)和FNAB联合BRAFV600E组(n=166),采用受试者工作特征曲线(ROC)和曲线下面积(AUC)评估两组的诊断效能,同时分析细胞病理分类Bethseda Ⅰ、Ⅲ~Ⅴ类结节的超声特点。 结果 304例患者中诊断为甲状腺癌的患者为278例,其中277例甲状腺乳头状癌,1例甲状腺髓样癌,诊断为良性病变的26例。两组中Bethseda Ⅰ、Ⅲ~Ⅴ类的结节有53个,超声特点以钙化(28.3%)和结节大小<1 cm(45.3%)为主。依据术后病理结果,FNAB细胞病理诊断组的效能评估:敏感性为93.9%,特异性为57.1%,AUC为0.824。FNAB细胞病理联合BRAFV600E组的效能评估:敏感性为98.0%,特异性为84.2%, AUC为0.911,且AUC联合分析>AUCFNAB结论 FNAB细胞病理联合BRAFV600E基因检测对甲状腺癌的诊断效能优于单独应用FNAB。

关键词: 细针穿刺, 鼠类肉瘤滤过性毒菌致癌同源体B1, 甲状腺癌, 细胞病理, 甲状腺结节

Abstract: Objective To investigate the value of ultrasound-guided fine needle aspiration biopsy(FNAB)and molecular detection of v-raf murine sarcoma viral oncogenic homolog B1(BRAF)V600E(BRAFV600E)in the diagnosis of thyroid carcinoma. Methods This study retrospectively analyzed 304 patients with thyroid nodules during Jan. 2019 and Dec. 2021. FNAB cytopathology and BRAFV600E molecular testing were performed. With postoperative pathological diagnosis as the gold standard, the patients were divided into FNAB group(n=138)and FNAB combined with BRAFV600E group(n=166). The receiver operating characteristic(ROC)curve and area under the curve(AUC)were used to evaluate the diagnostic efficacy of the two groups. The ultrasound characteristics of Bethseda I and III-V nodules were also analyzed. Results Among the 304 patients, 278 were diagnosed with thyroid carcinoma, including 277 papillary thyroid cancer, 1 medullary thyroid cancer, and 26 benign lesions. There were 53 nodules with uncertain cell diagnosis, and the characteristics of ultrasonography were calcification(28.3%)and nodular size < 1 cm(45.3%)was dominant. According to the postoperative pathological results, efficacy evaluation of FNAB group was as follows: the sensitivity, specificity, and AUC were 93.9%, 57.1% and 0.824, respectively. Efficacy evaluation of FNAB combined with BRAFV600E group was as follows: the sensitivity, specificity, and AUC were 98.0%, 84.2% and 0.911, respectively. And AUC combined analysis> AUCFNAB. Conclusion The diagnostic efficiency of FNAB combined with BRAFV600E is higher than that of FNAB alone.

Key words: Fine needle aspiration biopsy, V-raf murine sarcoma viral oncogene homolog B1, Thyroid carcinoma, Cytopathology, Thyroid nodule

中图分类号: 

  • R581
[1] Grani G, Sponziello M, Pecce V, et al. Contemporary thyroid nodule evaluation and management [J]. J Clin Endocrinol Metab, 2020, 105(9): 2869-2952.
[2] Sajisevi M, Caulley L, Eskander A, et al. Evaluating the rising incidence of thyroid cancer and thyroid nodule detection modes: a multinational, multi-institutional analysis [J]. JAMA Otolaryngol Head Neck Surg, 2022, 4: e221743. doi: 10.1001/jamaoto.
[3] Ahmadi S, Pappa T, Kang AS, et al. Point of care measurement of body mass index and thyroid nodule malignancy risk assessment [J]. Frontiers in endocrinology, 2022, 13: 824226. doi: 10.3389/fendo.2022.824226.
[4] Chen B, Xie Z, Duan X. Thyroid cancer incidence trend and association with obesity, physical activity in the United States [J]. BMC Public Health, 2022, 22(1): 1333-1345.
[5] Chen W, Zheng R, Baade PD, et al. Cancer statistics in China, 2015 [J]. CA Cancer J Clin, 2016, 66(2): 115-132.
[6] Kim J, Gosnell E, Roman SA. Geographic influences in the global rise of thyroid cancer [J]. J Clin Endocrinol Metab, 2020, 16(1): 17-29.
[7] Kitahara CM, Sosa JA. The changing incidence of thyroid cancer [J]. Nat Rev Endocrinol, 2016, 12(11): 646-653.
[8] Livhits M, Zhu C, Kuo E, et al. Effectiveness of molecular testing techniques for diagnosis of indeterminate thyroid nodules: a randomized clinical trial [J]. JAMA Oncol, 2021, 7(1): 70-77.
[9] 张旭东, 陈瑞雪, 王洁. BRAF基因突变与肿瘤[J]. 中国细胞生物学学报, 2017, 39(5): 668-674. ZHANG Xudong, CHEN Ruixue, WANG Jie. BRAF gene mutation in tumor [J]. Chinese Journal of Cell Biology, 2017, 39(5): 668-674.
[10] Abdullah M, Junit S, Ng K, et al. Papillary thyroid cancer: genetic alterations and molecular biomarker investigations [J]. Int J Med Sci, 2019, 16(3): 450-460.
[11] Cibas E, Ali SZ. The Bethesda system for reporting thyroid cytopathology [J]. Thyroid, 2009, 19(11): 1159-1165.
[12] Miranda-Filho A, Lortet-Tieulent J, Bray F, Cao B, et al. Thyroid cancer incidence trends by histology in 25 countries: a population-based study [J]. Lancet Diabetes Endocrinol, 2021, 9(4): 225-234.
[13] Sciuto R, Romano L, Rea S, et al. Natural history and clinical outcome of differentiated thyroid carcinoma: a retrospective analysis of 1503 patients treated at a single institution [J]. Ann Oncol, 2009, 20(10): 1728-1735.
[14] Collet JF, Lacave R, Hugonin S, et al. BRAF V600E detection in cytological thyroid samples: a key component of the decision tree for surgical treatment of papillary thyroid carcinoma [J]. Head Neck, 2016, 38(7): 1017-1021.
[15] Hay ID, McConahey WM, Goellner JR. Managing patients with papillary thyroid carcinoma: insights gained from the Mayo Clinics experience of treating 2,512 consecutive patients during 1940 through 2000[J]. Trans Am Clin Climatol Assoc, 2002, 113: 241-260.
[16] 杨粒芝, 孙霄, 商蒙蒙, 等. 基于中国版甲状腺影像报告与数据系统的甲状腺结节恶性风险预测模型[J]. 山东大学学报(医学版), 2022, 60(6): 64-69. YANG Lizhi, SUN Xiao, SHANG Mengmeng, et al. C-TIRADS-based nomogram for malignant risk prediction of thyroid nodules [J]. Journal of Shandong University(Health Sciences), 2022, 60(6): 64-69.
[17] Haugen BR, Alexander EK, Bible KC, et al. 2015 American thyroid association management guidelines for adult patients with thyroid nodules and differentiated thyroid cancer: the American thyroid association guidelines task force on thyroid nodules and differentiated thyroid cancer [J]. Thyroid, 2016, 26(1): 1-133.
[18] Alexander EK, Doherty GM, Barletta JA. Management of thyroid nodules [J]. Lancet Diabetes Endocrinol, 2022, 10(7): 540-548.
[19] Alexander EK, Doherty GM, Barletta JA. Diagnosis of thyroid nodules [J]. Lancet Diabetes Endocrinol, 2022, 10(7): 533-539.
[20] Xing M, Tufano RP, Tufaro AP, et al. Detection of BRAF mutation on fine needle aspiration biopsy specimens: a new diagnostic tool for papillary thyroid cancer [J]. J Clin Endocrinol Metab, 2004, 89(6): 2867-2872.
[21] Xing M, Alzahrani AS, Carson KA, et al. Association between BRAF V600E mutation and mortality in patients with papillary thyroid cancer [J]. JAMA, 2013, 309(14): 1493-1501.
[22] Poulikakos PI, Sullivan RJ, Yaeger R. Molecular pathways and mechanisms of BRAF in cancer therapy [J]. Clin Cancer Res, 2022, 29: clincanres.2138.2021. doi: 10.1158/1078-0432.CCR-21-2138.
[23] Nikiforov YE, Nikiforova MN. Molecular genetics and diagnosis of thyroid cancer [J]. Nat Rev Endocrinol, 2011, 7(10): 569-580.
[24] Grogan RH, Mitmaker EJ, Clark OH. The evolution of biomarkers in thyroid cancer-from mass screening to a personalized biosignature [J]. Cancers(Basel), 2010, 2(2): 885-912.
[25] Li C, Lee KC, Schneider EB, et al. BRAF V600E mutation and its association with clinicopathological features of papillary thyroid cancer: a meta-analysis [J]. J Clin Endocrinol Metab, 2012, 97(12): 4559-4570.
[26] Zatelli MC, Trasforini G, Leoni S, et al. BRAF V600E mutation analysis increases diagnostic accuracy for papillary thyroid carcinoma in fine-needle aspiration biopsies [J]. Eur J Endocrinol, 2009, 161(3): 467-473.
[27] Kim SW, Lee JI, Kim JW, et al. BRAFV600E mutation analysis in fine-needle aspiration cytology specimens for evaluation of thyroid nodule: a large series in a BRAFV600E-prevalent population [J]. J Clin Endocrinol Metab, 2010, 95(8): 3693-3700.
[1] 杨粒芝,孙霄,商蒙蒙,郭鲁,时丹丹,李杰. 基于中国版甲状腺影像报告与数据系统的甲状腺结节恶性风险预测模型[J]. 山东大学学报 (医学版), 2022, 60(6): 64-69.
[2] 庄大勇,贺青卿,李小磊,周鹏,岳涛,徐婧. 达芬奇机器人在儿童及青少年甲状腺癌中的应用[J]. 山东大学学报 (医学版), 2021, 59(1): 45-48.
[3] 柴佳威,朱坤兵,李亚琼,王甜甜. 隐匿性甲状腺癌:1例病例报道和文献回顾[J]. 山东大学学报 (医学版), 2021, 59(1): 83-87.
[4] 孙志刚,张晨宇,田兴松,王甜甜. 巨大甲状腺低分化癌1例[J]. 山东大学学报 (医学版), 2019, 57(11): 110-114.
[5] 于娜,郭情情,孙梅,盛燕,马增香,秦莹莹. 甲状腺癌术后行IVF/ICSI-ET助孕临床结局[J]. 山东大学学报 (医学版), 2018, 56(9): 54-58.
[6] 李进叶,宋歌声,宋吉清,王大伟,靳先文,张成琪. 宝石能谱CT与常规超声对甲状腺结节良恶性诊断价值的对照分析[J]. 山东大学学报(医学版), 2016, 54(3): 81-86.
[7] 刘言训, 刘佳, 张涛, 王璐, 薛付忠, 王萍. 基于纵向监测队列的2型糖尿病与甲状腺结节的关联性[J]. 山东大学学报(医学版), 2015, 53(8): 83-86.
[8] 何东添, 李晓平, 李尚仁. 多层螺旋CT对比彩色多普勒超声在甲状腺微小结节鉴别诊断中的应用[J]. 山东大学学报(医学版), 2014, 52(Z1): 140-141.
[9] 姜丽丽, 马喆, 马楚云, 何远流, 陶国伟, 刘村, 耿群, 汤婷婷, 王音. 声脉冲辐射力成像技术对甲状腺良、恶性结节的鉴别诊断价值[J]. 山东大学学报(医学版), 2014, 52(10): 72-76.
[10] 李建周,刘欣,张凌云,金勇君. 术前血清TSH浓度与分化型甲状腺癌的相关性研究[J]. 山东大学学报(医学版), 2011, 49(1): 10-13.
[11] 乔令艳1, 宋心红2, 林海燕2, 高聆3, 赵家军1. 健康人群中甲状腺结节患病情况调查[J]. 山东大学学报(医学版), 2010, 48(8): 5-.
[12] . 甲状腺结节的临床分析[J]. 山东大学学报(医学版), 2009, 47(8): 14-17.
[13] 刘延鹏,丁向东,刘萍,杨月香,潘祥林 . 全身热化疗治疗甲状腺癌多发性骨转移[J]. 山东大学学报(医学版), 2007, 45(9): 968-969.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] 索东阳,申飞,郭皓,刘力畅,杨惠敏,杨向东. Tim-3在药物性急性肾损伤动物模型中的表达及作用机制[J]. 山东大学学报 (医学版), 2020, 1(7): 1 -6 .
[2] 马青源,蒲沛东,韩飞,王超,朱洲均,王维山,史晨辉. miR-27b-3p调控SMAD1对骨肉瘤细胞增殖、迁移和侵袭作用的影响[J]. 山东大学学报 (医学版), 2020, 1(7): 32 -37 .
[3] 张宝文,雷香丽,李瑾娜,罗湘俊,邹容. miR-21-5p靶向调控TIMP3抑制2型糖尿病肾病小鼠肾脏系膜细胞增殖及细胞外基质堆积[J]. 山东大学学报 (医学版), 2020, 1(7): 7 -14 .
[4] 付洁琦,张曼,张晓璐,李卉,陈红. Toll样受体4抑制过氧化物酶体增殖物激活受体γ加重血脂蓄积的分子机制[J]. 山东大学学报 (医学版), 2020, 1(7): 24 -31 .
[5] 龙婷婷,谢明,周璐,朱俊德. Noggin蛋白对小鼠脑缺血再灌注损伤后学习和记忆能力与齿状回结构的影响[J]. 山东大学学报 (医学版), 2020, 1(7): 15 -23 .
[6] 李宁,李娟,谢艳,李培龙,王允山,杜鲁涛,王传新. 长链非编码RNA AL109955.1在80例结直肠癌组织中的表达及对细胞增殖与迁移侵袭的影响[J]. 山东大学学报 (医学版), 2020, 1(7): 38 -46 .
[7] 徐玉香,刘煜东,张蓬,段瑞生. 101例脑小血管病患者脑微出血危险因素的回顾性分析[J]. 山东大学学报 (医学版), 2020, 1(7): 67 -71 .
[8] 丁祥云,于清梅,张文芳,庄园,郝晶. 胰岛素样生长因子II在84例多囊卵巢综合征患者颗粒细胞中的表达和促排卵结局的相关性[J]. 山东大学学报 (医学版), 2020, 1(7): 60 -66 .
[9] 肖娟,肖强,丛伟,李婷,丁守銮,张媛,邵纯纯,吴梅,刘佳宁,贾红英. 两种甲状腺超声数据报告系统诊断效能的比较[J]. 山东大学学报 (医学版), 2020, 1(7): 53 -59 .
[10] 史爽,李娟,米琦,王允山,杜鲁涛,王传新. 胃癌miRNAs预后风险评分模型的构建与应用[J]. 山东大学学报 (医学版), 2020, 1(7): 47 -52 .