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基于血清代谢标志物的甲状腺癌患者淋巴结转移风险的预测模型
作者:李洪跃  徐先发  杨晓琦  唐玲  薄少军  郭雨田 
单位:北京大学民航临床医学院 民航总医院 耳鼻喉头颈外科, 北京 100123
关键词:血清代谢标志物 甲状腺癌 淋巴结转移 列线图 
分类号:R736.1
出版年·卷·期(页码):2022·50·第五期(581-588)
摘要:

目的:探讨基于血清代谢标志物建立的预测模型对甲状腺癌(TC)患者淋巴结转移风险的预测价值。方法:选择2020年1月至2021年1月于我院确诊TC并行手术治疗的患者207例,通过随机数字表法选择20%作为验证集,剩余80%作为训练集进行比较并建立预测模型。根据影像学资料及术中标本病理检查结果按是否发生淋巴结转移将所有患者分为转移组及未转移组。收集所有患者临床、实验室检查及影像学检查资料,并于术前抽取患者外周静脉血检测3-羟基丁酸(BHB)、二十二碳六烯酸(DHA)及孕二醇-3-葡糖醛酸(PdG)含量。通过Logistic模型分析上述资料中与淋巴结转移相关的因素,并通过列线图建立预测模型并验证预测效果。结果:转移组患者年龄大于未转移组,桥本甲状腺炎病史占比高于未转移组,差异具有统计学意义(P<0.05)。转移组患者促甲状腺释放激素(TSH)、甲状腺球蛋白抗体(TGAb)、BHB、DHA高于未转移组,而PdG则低于未转移组,差异具有统计学意义(P<0.05)。转移组患者肿瘤最大直径大于未转移组,两组患者肿瘤数目、形态、与被膜关系、血流情况比较,差异具有统计学意义(P<0.05)。结果显示年龄、BHB、DHA、PdG、肿瘤最大直径、与被膜关系是影响TC淋巴结转移的相关因素(P<0.05)。列线图模型预测发生TC淋巴结转移的C-index为0.924(95%CI 0.901~0.974),校正曲线显示列线图模型预测可能性绝对误差为0.025,一致性良好。结论:基于血清代谢学指标建立的模型对于TC淋巴结转移的预测具有一定价值,可对临床确诊及手术方式的选择提供参考。

Objective:To explore the predictive value of a model based on serum metabolic markers in predicting the risk of lymph node metastasis in patients with thyroid cancer(TC). Methods:A total of 207 patients who were diagnosed with TC in our hospital from January 2020 to January 2021 were selected for surgical treatment, then 20% of the patients were selected as the validation set by random number table method, and the remaining 80% were used as the training set for comparison to establish a prediction model. According to imaging data and intraoperative pathological examination results of specimens, all patients were divided into metastatic group and non-metastatic group. All of the patients' clinical data, laboratory examination and imaging examination results were collected. Peripheral venous blood was drawn from patients before the operation to detect the levels of 3-hydroxybutyric acid(BHB), docosahexaenoic acid(DHA) and pregnadiol-3-glucuronic acid(PdG). The logistic model was used to analyze the factors related to lymph node metastasis, then the prediction model was established through the nomogram and the prediction effectiveness was verified. Results:The patients in the metastatic group were older than those in the non-metastatic group, and the proportion of Hashimoto's thyroiditis history was higher than that in the non-metastatic group. The difference was statistically significant(P<0.05). The levels of TSH, TGAb, BHB and DHA of the metastatic group were higher than those of the non-metastatic group, while PdG was lower than that of the non-metastatic group, the difference being statistically significant(P<0.05). The maximum diameter of the tumor in the metastatic group was larger than that in the non-metastatic group. There were differences in the number of tumors, morphology, association with enveloping membrane, and blood flow between the two groups, and the difference was statistically significant(P<0.05). The results showed that age, BHB, DHA, PdG, the maximum diameter of tumor, and the relationship with the enveloping membrane were the related factors that affect TC lymph node metastasis(P<0.05). The C-index of the nomogram model in predicting the occurrence of TC lymph node metastasis was 0.924(95% CI 0.901-0.974), and the calibration curve showed that the absolute error of the nomogram model prediction probability was 0.025, which showed a good consistency. Conclusion:The model established based on serum metabolic indicators has a certain value in the prediction of TC lymph node metastasis, and can provide reference for clinical diagnosis and surgical options.

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