术前良恶性甲状腺结节鉴别诊断评分系统的建立及验证

The derivation and validation of a prediction rule for differential diagnosis of thyroid nodules

目的建立术前良恶性甲状腺结节鉴别诊断评分系统，并评价其临床价值。方法以1997年6月—2012年7月在上海长征医院行甲状腺结节手术患者为研究对象，通过查阅病历获取其临床信息。随机抽取2／3研究对象作为建模人群，其余作为验证人群。采用多元logistic回归分析方法建立恶性结节术前诊断预测模型。根据模型中各变量的B值赋予分值，建立良恶性结节鉴别诊断评分系统。通过预测一致性、良恶性区分能力和诊断准确度评价评分系统的临床价值。结果共纳入13980例患者（建模人群9195例，验证人群4785例）。评分系统由性别、发热、颈部疼痛、颈部包块、心悸盗汗、结节数量、结节位置、回声性质、结节边界、颈部淋巴结、结节最大径、促甲状腺素（TSH）、游离T，（FT，）、甲状腺过氧化物酶抗体（TPOAb）、甲状腺球蛋白抗体（TgAb）、甲状腺球蛋白（Tg）、降钙素、癌胚抗原（CEA）组成，其预测的一致性好（P=0．437），良恶性区分能力强（受试者工作特征曲线下面积为0．928），诊断准确度高（以63．5分作为诊断界值，其敏感度、特异度、准确率、阳性预测值、阴性预测值、阳性似然比、阴性似然比分别为89．3％、81．5％、83．2％、56．8％、96．6％、4．83和0．13）。评分系统在验证人群中的鉴别诊断效能与建模人群中的结果相似。结论所建立的术前良恶性甲状腺结节鉴别诊断评分系统具有良好的诊断效能，可以在术前较为准确地预测甲状腺结节的良恶性质。

Objective To set up a prediction rule for the pro-operative differential diagnosis of thyroid nodules and evaluate its clinical value. Methods All patients of thyroid nodules underwent thyroid operations in Changzheng hospital from June, 1997 to July, 2012 were included in this study. They were randomly divided into the derivation cohort （2/3） and the validation cohort （1/3）. A prediction rule was developed based on the logistic regression model and the scoring system was established in accordance with assigning of the value of each variable 13 in the model. The prediction consistency, discriminatory power and diagnostic accuracy were conducted to evaluate the clinical value of the scoring system. Results A total of 13 980 patients were enrolled in the study with 9195 in the derivation cohort and 4785 in the validation cohort. The prediction rule consisted of 18 variables, which were gender, clinical manifestations including fever, neck sore, neck mass, palpitation and sweating, serum level of thyroid stimulating hormone （TSH） , free triiodothyronine （ FT3 ） , thyroid peroxidase antibody （ TPOAb ） , thyroglobulin antibody （ TgAb ） , thyroglobulin（Tg）, calcitonin and carcinoembryonic antigen （CEA）, uhrasonography features including nodules number, location, size, boundaries and ethological patterns and the presence and patterns of lymph nodes. The model showed good calibration consistency （ P = 0. 437 ） and discrimination power （ area under the receiver operating characteristic curve was 0. 928 ） in the derivation cohort. The sensitivity, specificity,accuracy, positive predictive value, negative predictive value, positive likelihood ratio and negative likelihood ratio of the model were 89. 3%, 81.5%, 83.2%, 56. 8%, 96. 6%, 4. 83 and 0.13, respectively. Conclusion The prediction rule and its scoring system established in the study are efficacious for the calibration and discrimination of thyroid nodules in Chinese population, which could be a useful tool for the pro-operative risk stratification.