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基于超声、促甲状腺激素和炎症标志物的甲状腺乳头状癌列线图的开发与验证:一项病例对照研究

Development and validation of the nomogram based on ultrasound, thyroid stimulating hormone, and inflammatory marker in papillary thyroid carcinoma: a case-control study.

作者信息

Tang Zhong-Wei, Li Xin-Xi, Luo Jun

机构信息

Department of Vascular Thyroid Surgery, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.

出版信息

Transl Cancer Res. 2023 Mar 31;12(3):490-501. doi: 10.21037/tcr-22-2478. Epub 2023 Mar 17.

Abstract

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

摘要

背景

近年来甲状腺癌病例数量的增加不仅加重了医疗负担,还增加了过度治疗的可能性。因此,在治疗甲状腺结节时,术前区分甲状腺乳头状癌和良性甲状腺结节至关重要。

方法

将患者分为两组:验证队列有117例患者,初级队列有414例患者。基于初级队列的结果,开发了一个术前预测模型,然后在验证队列中进行外部验证。两组均记录术前促甲状腺激素(甲状腺刺激激素,TSH)、全身免疫炎症指数(SII)、淋巴细胞与单核细胞比值(LMR)以及超声特征。

结果

作为该模型的预测指标,选择了术前血液中的TSH、SII、LMR、回声性、边界、钙化、成分、纵横比以及年龄。回归方程为:Y = -0.070×(年龄) + 1.511×(回声性) + 1.664×(边界) + 1.003×(钙化) + 0.939×(成分) + 2.964×(纵横比) + 0.305×(TSH) + 0.558×(SII) - 1.271×(LMR) + 0.327。当Y≥0.808时,预测为甲状腺乳头状癌(PTC)阳性。该预测模型的准确性、敏感性和特异性分别为88.2%、85.1%和94.9%。受试者操作特征(ROC)曲线下面积为0.961。该模型的外部验证产生了令人满意的结果,准确性、敏感性和特异性分别为85.5%、90.9%和75.5%。

结论

利用术前TSH、SII、LMR和超声特征,开发并验证了一种简单准确的PTC术前预测模型。这种方法增强了PTC在临床应用中的术前评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92ca/10080328/af12346e7678/tcr-12-03-490-f1.jpg

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