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滤泡性甲状腺癌术前预测模型的建立与验证。

Development and validation of a preoperative prediction model for follicular thyroid carcinoma.

机构信息

Department of Thyroid Surgery, First Affiliated Hospital of Harbin Medical University, Harbin, China.

出版信息

Clin Endocrinol (Oxf). 2019 Aug;91(2):348-355. doi: 10.1111/cen.14002. Epub 2019 May 9.

Abstract

OBJECTIVE

The low pre- and intraoperative diagnostic rates in follicular thyroid carcinoma (FTC) often lead to inadequate surgical resection and necessitate further completion surgery. Therefore, the preoperative prediction of FTC in thyroid nodules is essential. DESIGN AND PATIENT: Patients were categorized into two data sets: the modelling data set, which included 3649 patients admitted to our centre between January 2014 and December 2016, and the validation data set, which included 1253 patients admitted between January and December 2017. Patient data from the FTC and non-FTC groups were initially included in a modelling data set to establish a preoperative prediction model. This model was subsequently employed in a validation data set for external validation of the predictive value. The positivity rate for FTC predicted by the model was compared with that of the intraoperative frozen sections.

RESULTS

The preoperative serum thyroglobulin level, nodule diameter, calcification status, solidity and blood supply were selected as predictors for the model. The regression equation was as follows: Y = 0.010 × (thyroglobulin level) + 0.556 × (nodule diameter) + 0.675 × (calcification status) + 2.355 × (nodule component) + 1.072*(blood flow) - 9.787. The model positively predicted FTC at values of Y ≥ -4.11. The accuracy, sensitivity, specificity, positive likelihood ratio and negative likelihood ratio of the prediction model were 89.2%, 90.2%, 87.7%, 39.2 and 0.11, respectively. External validation of the model demonstrated acceptable results. The positive prediction rate of the model was 90.7% (78/86), which was significantly higher than that of the intraoperative frozen sections (10.5% [9/86]; P < 0.0001).

CONCLUSIONS

We successfully established and validated a simple and reliable preoperative prediction model for FTC using the preoperative thyroglobulin level and ultrasonographic features of the thyroid nodules. This model may improve the preoperative evaluation of FTC in clinical settings and facilitate the development of a reasonable surgical programme for FTC.

摘要

目的

滤泡状甲状腺癌(FTC)的术前和术中诊断率较低,往往导致手术切除不充分,需要进一步完成手术。因此,术前预测甲状腺结节中的 FTC 是至关重要的。

设计和患者

患者被分为两个数据集:建模数据集,其中包括 2014 年 1 月至 2016 年 12 月期间在我院就诊的 3649 例患者;验证数据集,其中包括 2017 年 1 月至 12 月期间就诊的 1253 例患者。FTC 和非-FTC 组的患者数据最初被纳入建模数据集,以建立术前预测模型。该模型随后被应用于验证数据集中,以验证预测值的外部有效性。该模型预测的 FTC 阳性率与术中冰冻切片的阳性率进行了比较。

结果

术前血清甲状腺球蛋白水平、结节直径、钙化状态、实性和血流供应被选为模型的预测因素。回归方程如下:Y=0.010×(甲状腺球蛋白水平)+0.556×(结节直径)+0.675×(钙化状态)+2.355×(结节成分)+1.072×(血流)-9.787。模型在 Y≥-4.11 时对 FTC 呈阳性预测。预测模型的准确性、敏感性、特异性、阳性似然比和阴性似然比分别为 89.2%、90.2%、87.7%、39.2%和 0.11。模型的外部验证结果可接受。模型的阳性预测率为 90.7%(78/86),明显高于术中冰冻切片的阳性预测率(10.5%[9/86];P<0.0001)。

结论

我们成功地建立并验证了一种使用术前甲状腺球蛋白水平和甲状腺结节超声特征的简单、可靠的 FTC 术前预测模型。该模型可提高临床中 FTC 的术前评估水平,并有助于制定合理的 FTC 手术方案。

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