| 王晓亮,毛琼儿,王东海.桥本氏甲状腺炎合并分化型甲状腺癌的风险预测模型建立[J].肿瘤学杂志,2019,25(6):519-523. |
| 桥本氏甲状腺炎合并分化型甲状腺癌的风险预测模型建立 |
| Risk Prediction Model of Hashimoto′s Thyroiditis Complicated with Differentiated Thyroid Cancer |
| 投稿时间：2018-12-05 |
| DOI：10.11735/j.issn.1671-170X.2019.06.B006 |
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| 中文关键词: 桥本氏甲状腺炎 甲状腺肿瘤 甲状腺自身抗体 Logistic模型 ROC曲线 |
| 英文关键词:Hashimoto’s thyroiditis thyroid carcinoma thyroid autoantibody Logistic models ROC curve |
| 基金项目:宁波市奉化区科技社会发展项目（201508804） |
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| 中文摘要: |
| 摘 要：［目的］ 研究桥本氏甲状腺炎（HT）合并分化型甲状腺癌(DTC)的危险因素，预测桥本氏甲状腺炎合并分化型甲状腺癌的风险。［方法］ 100例HT合并DTC患者为病例组，另选取115例HT合并良性结节患者为对照组，采用Logistic回归分析，建立预测桥本甲状腺炎合并分化型甲状腺癌模型。［结果］ 通过多因素Logistic回归分析，甲状腺结节A/T≥1、微钙化、低回声结节是HT合并分化型甲状腺癌的独立危险因素，TGAb是保护因素。A/T≥1者患甲状腺癌的风险是A/T<1者的13.348倍，微钙化者患癌的风险是无钙化者的9.923倍，低回声结节者患癌的风险是混合性回声结节者3.782倍，TGAb每升高1单位，患癌风险下降0.2%。［结论］ 可通过甲状腺结节的A/T值、结节回声、钙化情况、TGAb预测HT合并DTC的风险，使用Logistic回归模型能够对桥本甲状腺炎合并分化型甲状腺癌做出较准确的判断。 |
| 英文摘要: |
| Abstract：［Objective］To establish a risk prediction model for complicating differentiated thyroid cancer (DTC) in Hashimoto’s thyroiditis (HT). ［Methods］ One hundred HT patients with complicating DTC were selected as the case group，and 115 HT patients with complicating benign nodules as the control group. Logistic regression analysis was used to establish a model for predicting HT complicated with DTC. ［Results］ Multivariate Logistic regression analysis showed that A/T≥1，microcalcification and hypoechoic nodules were independent risk factors for complicating DTC in HT patients. The risk of A/T≥1 was 13.348 times higher than that of AT<1，the risk of microcalcification was 9.923 times higher than that of non-calcified nodules，and the risk of hypoechoic nodules was 9.923 times higher than that of non-calc，the risk was 3.782 times higher than that of mixed echo nodules；and TGAb was a protective factor，the risk of cancer decreased by 0.2% for every 1 unit increase of TGAb. ［Conclusion］ The risk of Hashimoto’s thyroiditis complicated with differentiated thyroid cancer can be predicted by A/T value，nodular echo，calcification and TGAb of thyroid nodules. |
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