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基于高频超声图像特征的列线图模型预测甲状腺乳头状癌颈部淋巴结转移的临床价值 被引量:5

Clinical value of Nomogram model based on high frequency ultrasound features in predicting cervical lymph node metastasis of papillary thyroid carcinoma
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摘要 目的 基于高频超声图像特征构建列线图模型,探讨其预测甲状腺乳头状癌(PTC)患者发生颈部淋巴结转移(CLNM)的临床价值。方法 选取我院初次行甲状腺手术治疗及颈部淋巴结清扫术的PTC患者532例(638个结节),按7∶3比例随机分为训练集和验证集,其中训练集372例(446个结节),根据术后病理结果分为发生CLNM患者130例(CLNM组,166个结节)和未发生CLNM患者242例(非CLNM组,280个结节);验证集160例(192个结节),其中CLNM组58例(70个结节),非CLNM组102例(122个结节)。比较训练集两组患者性别、年龄,以及结节最大径、内部回声、微钙化、多发灶、后方回声衰减、内部成分、纵横比、结节边缘、被膜侵犯、彩色血流信号。选取训练集中CLNM组与非CLNM组差异有统计学意义的指标进行Logistic回归分析,筛选预测PTC患者发生CLNM的独立影响因素。基于筛选出的独立影响因素构建列线图模型,并对模型进行评价。结果 训练集中,两组患者性别、年龄,以及结节最大径、多发灶、边缘、微钙化、纵横比、被膜侵犯方面比较差异均有统计学意义(均P<0.05)。Logistic回归分析显示,结节边缘不规则、纵横比>1、微钙化、最大径>10 mm、多发灶、被膜侵犯均是PTC患者发生CLNM的独立影响因素(OR=2.598、4.926、5.307、5.850、10.293、15.226,均P<0.05)。列线图模型在训练集和验证集的ROC曲线下面积分别为0.875(95%可信区间:0.755~0.893)、0.855(95%可信区间:0.761~0.886);且列线图模型校准度良好,其预测CLNM风险概率与实际恶性风险无明显偏离;决策曲线显示,风险阈值概率在1%~90%时,有较高的净获益值,提示该模型临床实用性较好。结论 基于高频超声图像特征的列线图模型在预测PTC患者发生CLNM方面有较高的诊断效能,且区分度和校准度均较好。 Objective To explore the clinical value of Nomogram model based on high frequency ultrasound features in predicting cervical lymph node metastasis(CLNM)of papillary thyroid carcinoma(PTC).Methods A total of 532 PTC patients(638 nodules)who underwent primary thyroid surgery and cervical lymph node dissection in our hospital were randomly divided into training set and verification set according to the proportion of 7∶3.The training set included 372 patients(446 nodules)who were divided into 130 patients with CLNM(CLNM group,166 nodules)and 242 patients without CLNM(non-CLNM group,280nodules)according to the postoperative pathological results.The verification set included 160 patients(190 nodules)who were divided into 58 cases(70 nodules)of CLNM group and 102 cases(122 nodules)of non-CLNM group.The sex,age,maximum diameter of nodules,internal echo,microcalcification,multiple tumor,posterior echo attenuation,internal composition,aspect ratio,nodule edge,capsular invasion and color blood flow signal were compared between the two groups of the training set.The indexes with statistically significant difference between CLNM group and non-CLNM group in training set were selected for Logistic regression analysis to screen out the independent influencing factors of CLNM in PTC patients.The Nomogram model was constructed based on the screened independent predictors,and the model was evaluated.Results There were significant differences in sex,age,maximum diameter of nodules,multiple tumor,nodule edge,microcalcification,aspect ratio and capsule invasion between the two groups in training set(all P1,microcalcification,maximum diameter of nodules>10 mm,multiple tumor and capsule invasion were independent risk factors for CLNM in patients with PTC(OR=2.598,4.926,5.307,5.850,10.293,15.226,all P<0.05).The area under the ROC curve of the training set and the verification set of the Nomogram model were 0.875(95%CI:0.755~0.893)and 0.855(95%CI:0.761~0.886),respectively.The calibration of the Nomogram model was good,there was no significant deviation between the predicted CLNM risk probability and the actual malignant risk.The decision curve showed that when the threshold probability was 1%~90%,there was a higher net gain value and a higher clinical practicability of the model.Conclusion The Nomogram model based on high frequency ultrasound features has high diagnostic efficiency in predicting CLNM in PTC patients,and has good discrimination and calibration.
作者 谢卫珍 尹化如 XIE Weizhen;YIN Huaru(Department of Ultrasound,the Affiliated BenQ Hospital of Nanjing Medical University,Nanjing 210019,China)
出处 《临床超声医学杂志》 CSCD 2022年第11期859-863,共5页 Journal of Clinical Ultrasound in Medicine
关键词 超声检查 甲状腺乳头状癌 颈部淋巴结转移 被膜侵犯 列线图模型 Ultrasonography Papillary thyroid carcinoma Cervical lymph node metastasis Capsular invasion Nomogram model
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