Analysis on detections of benign and malignant thyroid nodules and risk factors in adult women in China
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摘要:
目的 调查我国成年女性甲状腺结节患病情况及良/恶性的检出率，研究影响甲状腺结节分级的危险因素。 方法 于2018 — 2019年在山东、河南、河北和浙江省随机选择18～60岁妇女进行调查，调查内容包括膳食情况，体格检查，水样、盐样、尿样、血样等样本采集及甲状腺B超检查。 采用描述性研究、单因素logistic 回归和偏比例优势模型分析甲状腺结节检出情况及结节分级的影响因素。 结果 纳入研究的2 082人，其中无结节［甲状腺影像和数据报告系统（TI-RADS）1级］、良性结节（TI-RADS 2级）、可能是良性结节（TI-RADS 3级）、可疑或很可能是恶性结节（TI-RADS 4或5级）检出率分别为43.32%、21.23%、14.51%、20.94%。 偏比例优势模型结果显示，年龄、超重肥胖、有甲状腺疾病史对甲状腺结节良/恶性分级的影响有统计学意义（P<0.05）。 结论 年龄增大、超重和肥胖、有甲状腺疾病史是成年女性甲状腺结节良/恶性分级的危险因素，应对老年人、肥胖人群以及有甲状腺病史高危人群的甲状腺结节进行重点筛查。 -
关键词:
- 甲状腺结节 /
- 甲状腺影像和数据报告系统 /
- 偏比例优势模型 /
- 成年女性
Abstract:Objective To understand the detections of benign and malignant thyroid nodules and related factors in adult women in China. Methods Women aged 18−60 years were selected randomly in Shandong, Henan, Hebei and Zhejiang provinces for dietary investigation, physical examination, tests of iodine in water, salt, urine and blood, and ultrasonic examination of thyroid gland. The detection of thyroid nodule and related factors were analyzed by descriptive study, univariate Logistic regression analysis and partial proportional odds model. Results A total of 2082 women were included in this study. The detection rates of non-nodule (TI-RADS grade 1), benign nodule (TI-RADS grade 2), possible benign nodule (TI-RADS grade 3), and suspected or highly suspected malignant nodule (TI-RADS grade 4 or 5) were 43.32%, 21.23%, 14.51% and 20.94%, respectively. The results of the partial proportional odds model showed that age, overweight and obesity, and thyroid disease history had significant effects on the thyroid nodule grading (P<0.05). Conclusion Older age, overweight and obesity, and thyroid disease history are the risk factors for thyroid nodule grading in adult women. It is necessary to conduct screening of thyroid nodules in the elderly, obese population and high-risk population with thyroid disease history. -
表 1 纳入分析的变量与赋值
Table 1. Variables and assignments included in analysis
变 量 赋 值 进入方式 甲状腺结节分级 TI-RADS 1级=0，TI-RADS 2级=1，TI-RADS 3级=2，TI-RADS 4或5级=3 因变量（有序多分类变量） 年龄（岁） ≤35=0，36～45=1，＞45=2 哑变量，以第一类为参照组 体质指数（kg/m2） 体过轻=0，正常=1，超重=2，肥胖=3 哑变量，以第二类为参照组 职业 体力劳动者=0，,非体力劳动者=1 二分类变量 甲状腺家族病史 无=0，有=1 二分类变量 甲状腺疾病史 无=0，有=1 二分类变量 高血压 无=0，有=1 二分类变量 甲状腺肿大 无=0，有=1 二分类变量 总碘摄入量（μg/d） ＜85 =0，85～119 =1，120～600 =2，≥600 =3 哑变量，以第二类为参照组 尿碘（μg/L） ＜100 =0，100～199 =1，200～299 =2，≥300=3 哑变量，以第二类为参照组 血清碘（μg/L） ＜45 =0，45～90 =1，>90 =2 哑变量，以第二类为参照组 
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表 2 研究对象甲状腺结节检出情况
Table 2. Prevalence of thyroid nodules in study subjects
项目 调查人数 TI-RADS 1级 TI-RADS 2级 TI-RADS 3级 TI-RADS 4或5级 人数 构成比（%） 人数 构成比（%） 人数 构成比（%） 人数 构成比（%） 年龄组（岁） ≤35 469 247 28.07 112 25.93 48 16.67 62 14.90 36～45 629 293 33.30 116 26.85 90 31.25 130 31.25 ＞45 918 340 38.63 204 47.22 150 52.08 224 53.85 职业 体力劳动者 693 312 35.74 147 34.51 94 33.22 140 33.73 非体力劳动者 1304 561 64.26 279 65.49 189 66.78 275 66.27 甲状腺家族病史 有 102 48 5.46 12 2.77 8 2.80 34 8.17 无 1912 831 94.54 421 97.23 278 97.20 382 91.83 甲状腺疾病史 有 184 55 6.24 45 10.44 15 5.26 69 16.59 无 1829 826 93.76 386 89.56 270 94.74 347 83.41 BMI（kg/m2） 过轻 45 30 3.34 11 2.50 3 1.01 1 0.23 正常 895 435 48.39 183 41.59 101 33.89 176 40.55 超重 693 272 30.26 147 33.41 118 39.60 156 35.94 肥胖 438 162 18.02 99 22.50 76 25.50 101 23.27 高血压 否 1600 712 79.38 329 75.81 242 81.48 317 73.21 是 461 185 20.62 105 24.19 55 18.52 116 26.79 甲状腺肿大 否 2 022 881 97.89 437 99.09 294 97.67 410 95.79 是 48 19 2.11 4 0.91 7 2.33 18 4.21 总碘摄入量(μg/d) ＜85 60 28 3.18 12 2.77 9 3.14 11 2.64 85～119 116 52 5.90 22 5.08 13 4.53 29 6.95 120～600 1462 640 72.64 298 68.82 222 77.35 302 72.42 >600 380 161 18.27 101 23.33 43 14.98 75 17.99 尿碘（μg/L） ＜100 326 153 17.83 69 16.51 19 6.62 85 20.43 100～199 533 240 27.97 107 25.60 64 22.30 122 29.33 200～299 161 75 8.74 23 5.50 34 11.85 29 6.97 ≥300 959 390 45.45 219 52.39 170 59.23 180 43.27 血清碘（μg/L） ＜45 51 26 2.91 14 3.20 3 1.02 8 1.87 45～90 1 882 810 90.60 402 91.99 275 93.86 395 92.29 >90 119 58 6.49 21 4.81 15 5.12 25 5.84 注：TI-RADS. 甲状腺影像和数据报告系统
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表 3 甲状腺结节良/恶性分级影响因素的单因素logistic 回归分析结果
Table 3. Logistic regression analysis on risk factors for thyroid nodules grading (univariate analysis)
变量 哑变量 因变量 β 标准误 Wald χ2值 P值 OR值 95% 可信区间 比例优势假定 下限 上限 χ2值 P值 年龄组（岁） 36～45 0.362 0.115 9.990 0.002 1.436 1.147 1.797 8.594 0.072 ＞45 0.681 0.107 40.838 <0.001 1.976 1.604 2.435 BMI 过轻 −0.907 0.324 7.854 0.005 0.404 0.214 0.761 11.114 0.085 超重 0.343 0.093 13.682 <0.001 1.409 1.175 1.691 肥胖 0.405 0.107 14.460 <0.001 1.499 1.217 1.848 职业 0.076 0.086 0.774 0.379 1.079 0.911 1.277 0.096 0.953 甲状腺家族病史 3 0.695 0.218 10.179 0.001 2.003 1.307 3.068 21.976 <0.001 2 0.284 0.207 1.879 0.170 1.328 0.885 1.992 1 −0.145 0.204 0.509 0.476 0.865 0.580 1.289 甲状腺疾病史 3 0.941 0.164 33.108 <0.001 2.563 1.860 3.531 21.798 <0.001 2 0.501 0.156 10.300 0.001 1.650 1.215 2.240 1 0.658 0.168 15.400 <0.001 1.932 1.390 2.683 高血压 3 0.308 0.124 6.143 0.013 1.361 1.067 1.736 6.747 0.034 2 0.094 0.110 0.727 0.394 1.098 0.886 1.362 1 0.179 0.108 2.777 0.096 1.196 0.969 1.477 甲状腺肿大 3 0.858 0.303 8.011 0.005 2.359 1.302 4.274 10.551 0.005 2 0.711 0.293 5.893 0.015 2.035 1.147 3.611 1 0.164 0.299 0.303 0.582 1.179 0.656 2.116 总碘摄入量 ＜85 −0.155 0.292 0.282 0.596 0.856 0.483 1.519 10.700 0.098 (μg/d) 120～600 −0.034 0.176 0.037 0.847 0.967 0.684 1.365 ≥600 −0.070 0.194 0.132 0.716 0.932 0.637 1.363 尿碘(μg/L) ＜100 3 0.172 0.163 1.120 0.290 1.188 0.863 1.635 69.006 <0.001 ＜100 2 −0.135 0.150 0.811 0.368 0.874 0.652 1.172 ＜100 1 −0.077 0.141 0.296 0.587 0.926 0.702 1.221 [200～299] 3 −0.301 0.230 1.719 0.190 0.740 0.472 1.161 [200～299] 2 0.182 0.185 0.962 0.327 1.199 0.834 1.724 [200～299] 1 −0.063 0.180 0.121 0.728 0.939 0.660 1.338 ≥300 3 −0.251 0.132 3.592 0.058 0.778 0.601 1.009 ≥300 2 0.070 0.113 0.381 0.537 1.072 0.859 1.338 ≥300 1 0.178 0.109 2.668 0.102 1.195 0.965 1.480 血清碘（μg/L） ＜45 −0.403 0.269 2.254 0.133 0.668 0.395 1.131 4.764 0.312 >90 −0.153 0.175 0.770 0.380 0.858 0.609 1.208
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表 4 甲状腺结节良/恶性分级影响因素的偏比例优势模型分析
Table 4. Partial proportional odds model analysis on thyroid nodules grading(multivariable analysis）
变量 虚拟
变量因变量 参数
估计标准误 Wald χ2值 P值 OR值 95% 可信区间 下限 上限 截距 3 −2.010 0.111 329.329 <0.001 截距 2 −1.223 0.104 139.113 <0.001 截距 1 −0.328 0.100 10.788 0.001 年龄组（岁） 36～45 0.282 0.118 5.744 0.017 1.326 1.053 1.669 ＞45 0.570 0.110 26.953 <0.001 1.769 1.426 2.193 体质指数 体重过轻 −0.788 0.322 5.988 0.014 0.455 0.242 0.855 超重 0.335 0.098 11.708 <0.001 1.397 1.154 1.692 肥胖 0.375 0.112 11.282 <0.001 1.454 1.169 1.81 甲状腺疾病史 3 0.961 0.174 30.686 <0.001 2.614 1.861 3.672 2 0.499 0.166 9.071 0.003 1.647 1.190 2.278 1 0.683 0.177 14.914 <0.001 1.980 1.400 2.801
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[1] 范雪, 唐钰姣, 巴妍·谢开, 等. 健康体检人群超声检查乳腺结节与甲状腺结节发病率的相关性[J]. 影像研究与医学应用,2020,4(12):129–131. DOI:10.3969/j.issn.2096−3807.2020.12.085.Fan X, Tang YJ, Bayan XK, et al. Correlation between breast nodule and thyroid nodule incidence by ultrasonography in healthy people[J]. J Imag Res Med Appl, 2020, 4(12): 129–131. DOI: 10.3969/j.issn.2096−3807.2020.12.085. [2] 王东梅, 周茜, 霍煜廷, 等. 甲状腺结节的影响因素研究进展[J]. 中国普通外科杂志,2018,27(5):635–641. DOI:10.3978/j.issn.1005−6947.2018.05.017.Wang DM, Zhou Q, Huo YT, et al. Research progress of influential factors for thyroid nodules[J]. Chin J Gen Surg, 2018, 27(5): 635–641. DOI: 10.3978/j.issn.1005−6947.2018.05.017. [3] 孙可欣, 郑荣寿, 张思维, 等. 2015年中国分地区恶性肿瘤发病和死亡分析[J]. 中国肿瘤,2019,28(1):1–11. DOI:10.11735/j.issn.1004−0242.2019.01.A001.Sun KX, Zheng RS, Zhang SW, et al. Report of cancer incidence and mortality in different areas of China, 2015[J]. China Cancer, 2019, 28(1): 1–11. DOI: 10.11735/j.issn.1004−0242.2019.01.A001. [4] 申淑霞, 刘书芳, 杨改景, 等. 超声TI-RADS分级对甲状腺结节良恶性的诊断价值[J]. 临床医学,2021,41(3):66–68. DOI:10.19528/j.issn.1003−3548.2021.03.028.Shen SX, Liu SF, Yang GJ, et al. Diagnostic value of ultrasonic TI-RADS grading for benign and malignant thyroid nodules[J]. Clin Med, 2021, 41(3): 66–68. DOI: 10.19528/j.issn.1003−3548.2021.03.028. [5] 赖晓英, 欧阳平, 朱宏, 等. 甲状腺结节检出情况及影响因素: 10年309 576例体检人群分析[J]. 南方医科大学学报,2020,40(2):268–273. DOI:10.12122/j.issn.1673−4254.2020.02.20.Lai XY, Ouyang P, Zhu H, et al. Detection rate of thyroid nodules in routine health check-up and its influencing factors: a 10-year survey of 309 576 cases[J]. J South Med Univ, 2020, 40(2): 268–273. DOI: 10.12122/j.issn.1673−4254.2020.02.20. [6] 田春园, 卜野, 纪春磊, 等. 黑龙江省中老年人群甲状腺结节流行病学特征及其影响因素[J]. 中华地方病学杂志,2020,39(5):347–352. DOI:10.3760/cma.j.cn231583−20200407−00076.Tian CY, Bu Y, Ji CL, et al. Epidemiological characteristics and influencing factors of thyroid nodule in middle-aged and elderly people in Heilongjiang province[J]. Chin J Endemiol, 2020, 39(5): 347–352. DOI: 10.3760/cma.j.cn231583−20200407−00076. [7] 惠嘉丽, 艾祝宁. 健康体检人群甲状腺结节的检出率及影响因素研究[J]. 贵州医药,2021,45(2):288–289. DOI:10.3969/j.issn.1000−744X.2021.02.057.Hui JL, Ai ZN. Study on the detection rate and influencing factors of thyroid nodules in healthy people[J]. Guizhou Med J, 2021, 45(2): 288–289. DOI: 10.3969/j.issn.1000−744X.2021.02.057. [8] 中国肥胖问题工作组. 中国成人超重和肥胖症预防与控制指南(节录)[J]. 营养学报,2004,26(1):1–4. DOI:10.3321/j.issn:0512−7955.2004.01.001.Working Group on Obesity in China. Guidelines for the prevention and control of overweight and obesity in chinese adults[J]. Acta Nutr Sin, 2004, 26(1): 1–4. DOI: 10.3321/j.issn:0512−7955.2004.01.001. [9] 中国高血压防治指南修订委员会, 高血压联盟(中国), 中华医学会心血管病学分会, 等. 中国高血压防治指南(2018年修订版)[J]. 中国心血管杂志,2019,24(1):24–56. DOI:10.3969/j.issn.1007−5410.2019.01.002.China Hypertension Prevention and Treatment Guidelines Revision Committee, CHL, Chinese Society of Cardiology, et al. 2018 Chinese guidelines for the management of hypertension writing group of 2018[J]. Chin J Cardiovasc Med, 2019, 24(1): 24–56. DOI: 10.3969/j.issn.1007−5410.2019.01.002. [10] 王海燕, 刘列钧, 李淑华, 等. 适合缺碘及高碘地区水碘检测的方法研究[J]. 中国地方病学杂志,2007,26(3):333–336. DOI:10.3760/cma.j.issn.1000−4955.2007.03.035.Wang HY, Liu LJ, Li SH, et al. Determination of iodine in drinking water by As3+-Ce4+ catalytic spectrophotometry[J]. Chin J Endemiol, 2007, 26(3): 333–336. DOI: 10.3760/cma.j.issn.1000−4955.2007.03.035. [11] 中华人民共和国国家卫生和计划生育委员会. WS/T 107.1－2016 尿中碘的测定 第1部分: 砷铈催化分光光度法 ［S］. 北京: 中国标准出版社, 2016.National Health and Family Planning Commission, PRC. WS/T 107.1－2016 Determination of iodine in urine－Part 1: As3+-Ce4+catalytic spectrophotometry［S］. Beijing: Standards Press of China, 2016. [12] 中华人民共和国国家卫生和计划生育委员会. WS/T 572－2017 血清中碘的测定 砷铈催化分光光度法［S］. 北京: 中国标准出版社, 2017.National Health and Family Planning Commission, PRC. WS/T 572－2017 Determination of iodine in serum - As3+［S］. Beijing: Standards Press of China, 2017. [13] Kwak JY, Han KH, Yoon JH, et al. Thyroid imaging reporting and data system for US features of nodules: a step in establishing better stratification of cancer risk[J]. Radiology, 2011, 260(3): 892–899. DOI: 10.1148/radiol.11110206. [14] Pemayun TGD. Current diagnosis and management of thyroid nodules[J]. Acta Med Indones, 2016, 48(3): 247–257. [15] 高勇. 甲状腺结节良恶性的多因素分析预测[J]. 数理医药学杂志,2017,30(4):501–503. DOI:10.3969/j.issn.1004−4337.2017.04.012.Gao Y. Multivariate analysis and prediction of benign and malignant thyroid nodules[J]. J Math Med, 2017, 30(4): 501–503. DOI: 10.3969/j.issn.1004−4337.2017.04.012. [16] 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. DOI: 10.1089/thy.2015.0020. [17] 邱华, 马步云, 赵萌. 甲状腺良恶性结节超声鉴别诊断的影响因素探讨[J]. 西部医学,2016,28(4):545–547,551. DOI:10.3969/j.issn.1672−3511.2016.04.026.Qiu H, Ma BY, Zhao M. Influential factor analysis of benign and malignant thyroid nodules with ultrasound identification[J]. Med J West China, 2016, 28(4): 545–547,551. DOI: 10.3969/j.issn.1672−3511.2016.04.026. [18] 张靖. 甲状腺癌临床新特点及评估甲状腺结节良恶性模型的建立［D］. 济南: 山东大学, 2020.Zhang J. Changes in clinical features of thyroid cancer and a quantitative method for predicting malignancy in thyroid nodules［D］. Ji′nan: Shandong University, 2020. [19] 郇琴. 6304例甲状腺结节患者流行病学特点及恶性结节危险因素分析［D］. 济南: 山东大学, 2014.Huan Q. Epidemiological characteristics of thyroid nodules and risk factors of malignant nodules: a retrospective study from 6304 surgical cases［D］. Ji′nan: Shandong University, 2014. [20] 邹冰, 王新, 孙丽, 等. 健康体检人群甲状腺结节患病率及其与代谢性疾病的关系研究[J]. 中国全科医学,2020,23(19):2423–2428. DOI:10.12114/j.issn.1007−9572.2020.00.089.Zou B, Wang X, Sun L, et al. Prevalence of thyroid nodules in health checkups and its relationship with metabolic diseases[J]. Chin Gen Pract, 2020, 23(19): 2423–2428. DOI: 10.12114/j.issn.1007−9572.2020.00.089. [21] 杜丹, 李阳桦, 陈艳伟, 等. 甲状腺结节危险因素的Meta分析[J]. 职业与健康,2016,32(8):1034–1037. DOI: 10.13329/j.cnki.zyyjk.2016.0286.Du D, Li YH, Chen YW, et al. Meta-analysis on risk factors of thyroid nodules[J]. Occup Health, 2016, 32(8): 1034–1037. DOI: 10.13329/j.cnki.zyyjk.2016.0286. [22] 罗景梅, 冯家钢, 詹东, 等. 甲状腺结节患者临床特征研究[J]. 中国全科医学,2018,21(36):4445–4452,4458. DOI:10.12114/j.issn.1007−9572.2018.00.109.Luo JM, Feng JG, Zhan D, et al. Study on clinical characteristics of thyroid nodules[J]. Chin Gen Pract, 2018, 21(36): 4445–4452,4458. DOI: 10.12114/j.issn.1007−9572.2018.00.109. [23] 孙荣欣, 郑召辉, 张强, 等. 人群体质量指数与甲状腺结节患病率及其恶性风险分层的相关性[J]. 川北医学院学报,2021,36(1):72–75. DOI:10.3969/j.issn.1005−3697.2021.01.017.Sun RX, Zheng ZH, Zhang Q, et al. Correlation between the body mass index with thyroid nodule prevalence and risk stratification[J]. J North Sichuan Med Coll, 2021, 36(1): 72–75. DOI: 10.3969/j.issn.1005−3697.2021.01.017. [24] Rezzonico J, Rezzonico M, Pusiol E, et al. Introducing the thyroid gland as another victim of the insulin resistance syndrome[J]. Thyroid, 2008, 18(4): 461–464. DOI: 10.1089/thy.2007.0223. [25] Xu WM, Chen ZX, Li N, et al. Relationship of anthropometric measurements to thyroid nodules in a Chinese population[J]. BMJ Open, 2015, 5(12): e008452. DOI: 10.1136/bmjopen−2015−008452. [26] Bétry C, Challan-Belval MA, Bernard A, et al. Increased TSH in obesity: evidence for a BMI-independent association with leptin[J]. Diabetes Metab, 2015, 41(3): 248–251. DOI: 10.1016/j.diabet.2014.11.009. [27] 高芳凤, 郑伍桂, 车春, 等. 健康体检人群甲状腺结节相关因素研究[J]. 华南预防医学,2019,45(6):536–539. DOI: 10.12183/j.scjpm.2019.0537.Gao FF, Zheng WG, Che C, et al. Related factors of thyroid nodules in healthy physical examination people[J]. South China J Prev Med, 2019, 45(6): 536–539. DOI: 10.12183/j.scjpm.2019.0537. [28] 吴少彬, 彭林平, 苗思慧, 等. 惠州地区居民碘营养状况调查及甲状腺结节的危险因素分析[J]. 实用预防医学,2018,25(7):814–817. DOI:10.3969/j.issn.1006−3110.2018.07.013.Wu SB, Peng LP, Miao SH, et al. Status of iodine nutrition and risk factors of thyroid nodules among residents in Huizhou region[J]. Pract Prev Med, 2018, 25(7): 814–817. DOI: 10.3969/j.issn.1006−3110.2018.07.013. [29] 李彦娟, 王磊, 王钰, 等. 甲状腺结节发病率调查及影响因素分析[J]. 中国综合临床,2020,36(5):455–459. DOI:10.3760/cma.j.cn121361−20191221−00090.Li YJ, Wang L, Wang Y, et al. Analysis of incidence rate and influencing factors of thyroid nodules[J]. Clin Med China, 2020, 36(5): 455–459. DOI: 10.3760/cma.j.cn121361−20191221−00090. [30] Lall R, Campbell MJ, Walters SJ, et al. A review of ordinal regression models applied on health-related quality of life assessments[J]. Stat Methods Med Res, 2002, 11(1): 49–67. DOI: 10.1191/0962280202sm271ra. [31] 唐俐玲, 翟晓红, 王萍, 等. 偏比例优势模型在有序分类资料中的应用[J]. 山西医科大学学报,2010,41(8):685–687. DOI:10.3969/J.ISSN.1007−6611.2010.08.006.Tang LL, Zhai XH, Wang P, et al. The application of partial proportional odds model in the ordinal data[J]. J Shanxi Med Univ, 2010, 41(8): 685–687. DOI: 10.3969/J.ISSN.1007−6611.2010.08.006. -
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