■近年来，甲状腺癌病例数量的增加不仅增加了医疗负担，而且增加了过度治疗的可能性。因此,治疗甲状腺结节时，术前区分甲状腺乳头状癌和甲状腺良性结节至关重要。
■患者分为两组：117名患者组成验证队列，414名患者组成主要队列。作为主要队列的结果，建立了术前预测模型，然后在验证队列中进行外部验证。术前促甲状腺激素（促甲状腺激素，TSH),全身免疫炎症指数（SII），淋巴细胞与单核细胞比率（LMR），并记录两组的超声特征。
■作为模型的预测因子，术前血液TSH水平，SII,LMR,回声,margin,钙化,composition,比宽高,和年龄选择。回归方程:Y=-0.070×(年龄)+1.511×(回声)+1.664×(边缘)+1.003×(钙化)+0.939×(成分)+2.964×(高比宽)+0.305×(TSH)+0.558×(SII)-1.271×(LMR)+0.327。甲状腺乳头状癌(PTC)呈阳性预测,Y值≥0.808。预测模型的准确性，灵敏度,特异性为88.2%，85.1%,94.9%,分别。受试者工作特征(ROC)曲线下面积为0.961。模型的外部验证产生了令人满意的结果，具有准确性，灵敏度,特异性为85.5%，90.9%,75.5%,分别。
■使用术前TSH，SII,LMR,和超声特征，已开发并验证了一种简单而准确的PTC术前预测模型.该方法增强了PTC在临床应用中的术前评估。
UNASSIGNED: The increase in the number of thyroid cancer cases in recent years has increased not only the medical burden but also the potential for overtreatment. Therefore, it is crucial to distinguish papillary thyroid cancer from benign thyroid nodules before surgery when treating thyroid nodules.
UNASSIGNED: The patients were divided into two groups: 117 patients made up the validation cohort and 414 patients made up the primary cohort. As a result of the primary cohort, a preoperative prediction model was developed, which was then validated externally in the validation cohort. Preoperative thyrotropin (thyroid stimulating hormone, TSH), systemic immune-inflammation index (SII), lymphocyte-to-monocyte ratio (LMR), and ultrasonographic features were recorded in both groups.
UNASSIGNED: As predictors for the model, the preoperative blood levels of TSH, SII, LMR, echogenicity, margin, calcification, composition, taller-than-wide, and age were chosen. This was the regression equation: Y = -0.070 × (age) + 1.511 × (echogenicity) + 1.664 × (margin) + 1.003 × (calcification) + 0.939 × (composition) + 2.964 × (tall than wide) + 0.305 × (TSH) + 0.558 × (SII) - 1.271 × (LMR) + 0.327. Papillary thyroid carcinoma (PTC) was predicted positively with values of Y ≥0.808. The prediction model\'s accuracy, sensitivity, and specificity were 88.2%, 85.1%, and 94.9%, respectively. The area under the receiver operating characteristic (ROC) curve was 0.961. The model\'s external validation produced satisfactory results with accuracy, sensitivity, and specificity of 85.5%, 90.9%, and 75.5%, respectively.
UNASSIGNED: Using the preoperative TSH, SII, LMR, and ultrasonographic characteristics, a straightforward and accurate preoperative prediction model for PTC has been developed and validated. The preoperative assessment of PTC in clinical application is enhanced by this approach.
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