Development and Validation of a Preoperative Prediction Model for Follicular Thyroid Carcinoma

QingAn Yu; KunPeng Liu; ChangMing Xie; DaKun Ma; YaoHua Wu; HongChi Jiang; WenJie Dai

Disclosures

Clin Endocrinol. 2019;91(2):348-355. 

In This Article

Abstract and Introduction

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.

Introduction

Thyroid nodules are a common clinical finding, with a prevalence rate of 4%–7% on palpation and 20%–67% on ultrasonography.[1,2] However, only <10% of thyroid nodules are malignant.[3,4] The most common thyroid malignancies are papillary thyroid carcinoma (PTC) and follicular thyroid carcinoma (FTC), both of which are derived from the follicular cells, and are collectively referred to as differentiated thyroid cancers. FTC and PTC are sensitive to radioactive iodine therapy.[5] FTC accounts for 5%–10% of all thyroid cancers;[6,7] in iodine-deficient areas, its prevalence is comparable to that of PTC.[8]

The diagnosis and treatment of FTC are difficult and controversial for various reasons. Firstly, the preoperative ultrasound classification and scoring systems are inadequate for the evaluation of FTC.[9,10] Secondly, the sensitivity of preoperative fine-needle aspiration cytology is not sufficient for diagnosing FTC;[11] also, the scope of intraoperative frozen sections is limited by the inability to differentiate FTC from follicular thyroid adenoma (FTA) and the follicular variant of PTC.[12] Finally, the extent of treatment and follow-up in FTC remains unclear. According to the American Thyroid Association guidelines, 2015, FTC may be classified into minimally invasive and widely invasive tumours based on the number of vascular and capsular invasion.[13] For minimally invasive FTC, hemithyroidectomy is adequate. However, total thyroidectomy and postoperative radioactive iodine therapy are required for widely invasive FTC. Owing to the low pre- and intraoperative diagnostic rates, surgical resection for FTC is often inadequate, necessitating further completion surgery. Therefore, the preoperative prediction of FTC in thyroid nodules is particularly important.

This study aimed to develop and validate a simple and reliable preoperative prediction model for FTC using the preoperative thyroglobulin level and ultrasonographic features of the thyroid nodules to facilitate improved preoperative evaluation of FTC.

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