Development And Validation Of A Nomogram Predictive Model For Central Lymph Node Metastasis Risk In The Papillary Thyroid Microcarcinoma

Objectives The purpose of this study was to analyze the clinical data of the patients and identify the influencing factors of central lymph node metastasis(CLNM)in clinical lymph node negative(c N0)papillary thyroid microcarcinoma(PTMC)patients by Logistic regression analysis.Based on influencing factors,we establish a new nomogram clinical predictive model to analyze the ability to predict the risk of CLNM in PTMC patients,so that clinicians can objectively and accurately evaluate the risk of CLNM in each patient,and guide clinical decision-making.Methods This study analyzed the typical preoperative ultrasonographic and clinicopathologic features of 546 PTMC patients who underwent surgery retrospectively from October 2014 to October 2020 in Hebei General Hospital,among which 382 patients were recruited in the training cohort and 164 patients in the independent validation cohort.Univariate and multivate logistic regression analysis was performed on the ultrasonographic and clinicopathologic features of PTMC to identify influencing factors related to CLNM,including age,sex,preoperative TSH level,and ultrasonographic features(tumor size,aspect ratio,relationship between nodule and membrane,calcification,single focus/multiple focus,combined with Hashimoto’s thyroiditis,combined with nodular goiter),and finally construct a nomogram.The area under the curve(AUC)of operating characteristics(ROC),Hosmer-Lemeshow test and calibration curves were used to evaluate the nomogram performance in predicting the risk of central lymph node metastasis.Results A total of 382 PTMC patients were included in the training cohort.Among them,114 patients developed CLNM.Totally,six independent predictors,including the age,tumor size,capsular invasion,multifocality,Hashimotos thyroiditis,were enrolled in the nomogram.Both the internal validation in the training cohort and the external validation in the validation cohort showed the nomogram had good discriminations,with AUC of 0.775(95%CI: 0.723-0.826)and 0.720(95%CI: 0.635-0.804),respectively.Hosmer-Lemeshow test results in the training cohort and the validation cohort were respectively P=0.752 and 0.734.Good agreement was observed using calibration curves in training and validation cohorts.Conclusions 1 Totally,six independent predictors,including the age,sex,tumor size,relationship between nodule and thyroid capsule,multifocality,Hashimotos thyroiditis were identified.2 This study obtained a quantitative,intuitive and concise evaluation method by establishing a nomogram clinical prediction model,when the patient’s score was greater than 239.05,prophylactic central lymph node dissection could be considered.3 By constructing nomogram clinical prediction model,this study provides a noninvasive way to judge the status of central lymph nodes in patients with papillary thyroid microcarcinoma.This prediction model has good differentiation,calibration and clinical application value,which enables clinicians to quickly,accurately and objectively evaluate the risk of central lymph node metastasis in each patient and thus guide clinical decisionmaking.Figure 7;Table 8;Reference 168...