Analysis of Risk Factors and Risk Prediction for Cervical Lymph Node Metastasis in Thyroid Papillary Carcinoma.

IF 2.5 4区医学 Q3 ONCOLOGY Cancer Management and Research Pub Date : 2024-11-11 eCollection Date: 2024-01-01 DOI:10.2147/CMAR.S485708

Dandan Tian, Xiaoqin Li, Zhongzhi Jia

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Abstract

Background: To analyze the risk factors of cervical lymph node metastasis (LNM) of thyroid papillary carcinoma (PTC) and construct the prediction model.

Methods: Clinical data of 1105 patients with pathologically confirmed PTC in our hospital from February 2019 to May 2024 were retrospectively analyzed, and randomly divided into a training set and validation set according to the proportion of 7:3. With cervical central LNM (CLNM) and lateral LNM (LLNM) as outcome variables respectively, ultrasound characteristics were analyzed and C-TIRADS scores were performed Combined with the general situation of the patient, preoperative serum thyroglobulin (Tg) level, BRAFV600E (hereinafter referred to as BRAF) gene mutation and other characteristics of the patient, analysis was conducted to determine the independent risk factors for cervical CLNM and LLNM of PTC, and establish Nomogram prediction models. The test data set is used to validate the model. The area under the ROC curve (AUC) and the decision curve analysis (DCA) were used to evaluate the prediction efficiency of the model.

Results: The analysis shows that male, age < 55 years old, tumor diameter ≥ 1 cm, capsular invasion, positive serum thyroglobulin (Tg), BRAF gene mutation type and C-TIRADS score are independent risk factors for cervical CLNM in PTC (P < 0.05). Tumor diameter ≥ 1 cm, capsular invasion, tumor located at the upper pole and presence of CLNM are independent risk factors for LLNM in PTC. Based on the above risk factors, Nomogram prediction models for CLNM and LLNM are constructed respectively. The AUC of the CLNM prediction model is 91.5%. LLNM model is 96.1%.

Conclusion: Ultrasound indicators, C-TIRADS score combined with BRAF gene status, Tg and clinical indicators of patients have important value in predicting cervical CLNM and LLNM in PTC. The Nomogram prediction models constructed based on the above indicators can effectively predict the risk of LNM in PTC.

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甲状腺乳头状癌颈淋巴结转移的风险因素分析与风险预测

背景：分析甲状腺乳头状癌（PTC）颈淋巴结转移（LNM）的风险因素并构建预测模型：分析甲状腺乳头状癌（PTC）颈淋巴结转移（LNM）的危险因素并构建预测模型：回顾性分析我院2019年2月至2024年5月经病理确诊的1105例PTC患者的临床资料，按照7:3的比例随机分为训练集和验证集。分别以宫颈中央LNM（CLNM）和侧方LNM（LLNM）为结局变量，分析超声特征，进行C-TIRADS评分结合患者一般情况、术前血清甲状腺球蛋白（Tg）水平、BRAFV600E（以下简称BRAF）基因突变等特征，分析确定PTC宫颈CLNM和LLNM的独立危险因素，建立Nomogram预测模型。测试数据集用于验证模型。采用 ROC 曲线下面积（AUC）和决策曲线分析（DCA）评估模型的预测效率：分析表明，男性、年龄小于55岁、肿瘤直径≥1厘米、囊腔浸润、血清甲状腺球蛋白（Tg）阳性、BRAF基因突变类型和C-TIRADS评分是PTC宫颈CLNM的独立危险因素（P＜0.05）。肿瘤直径≥1厘米、囊腔浸润、肿瘤位于上极和存在CLNM是PTC中LLNM的独立危险因素。根据上述风险因素，分别构建了 CLNM 和 LLNM 的 Nomogram 预测模型。CLNM预测模型的AUC为91.5%。LLNM模型的AUC为96.1%：超声指标、C-TIRADS评分结合患者的BRAF基因状态、Tg和临床指标对预测PTC宫颈CLNM和LLNM有重要价值。基于上述指标构建的Nomogram预测模型可有效预测PTC发生LNM的风险。

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来源期刊

Cancer Management and Research Medicine-Oncology

CiteScore

7.40

自引率

0.00%

发文量

448

审稿时长

16 weeks

期刊介绍： Cancer Management and Research is an international, peer reviewed, open access journal focusing on cancer research and the optimal use of preventative and integrated treatment interventions to achieve improved outcomes, enhanced survival, and quality of life for cancer patients. Specific topics covered in the journal include: ◦Epidemiology, detection and screening ◦Cellular research and biomarkers ◦Identification of biotargets and agents with novel mechanisms of action ◦Optimal clinical use of existing anticancer agents, including combination therapies ◦Radiation and surgery ◦Palliative care ◦Patient adherence, quality of life, satisfaction The journal welcomes submitted papers covering original research, basic science, clinical & epidemiological studies, reviews & evaluations, guidelines, expert opinion and commentary, and case series that shed novel insights on a disease or disease subtype.