The Risk Factors And The Establishment Of Predictive Models For Recurrent Laryngeal Nerve Lymph Node Metastasis In Patients With Thoracic Esophageal Squamous Cell Carcinoma

Objective:Analyzing the characteristics and regularity of recurrent laryngeal nerve(RLN)lymph node metastasis(LNM)in patients with thoracic esophageal squamous cell carcinoma(ESCC),and screening the risk factors of RLN LNM.Then constructing a nomogram risk prediction model according to independent risk factors.And the predictive value of the model is evaluated by the way of internal verification.At last,the prediction model can help medical staff effectively identify high-risk patients with RLN LNM in the process of clinical treatment and act as a basis for individualized treatment of patients.Method:99 patients with thoracic ESCC surgery are chose who met the exclusion and inclusion criteria,and all of them underwent thoracic surgery in the second Hospital of Jinlin University from July 2018 to October 2022.86 patients of them are selected to establish mathematical prediction models and 13 patients are selected to verify the accuracy of mathematical model’s predictive ability.Univariate analysis is used to analyze the patients in the modeling group,and then screening out the possible risk factors of RLN LNM.For these statistically significant factors in the results,they are analyzed by using binary logistic regression analysis to screen out the independent risk factors of RLN LNM.Based on this,using the Rstudio software to construct the nomogram prediction model of RLN LNM in ESCC patients.After that the internal verification of the model is carried out by the patient data of the verifiable group.And the receiver working characteristic curve(ROC)is drawn to evaluate the prediction effect of the model.Result:1.In this study,the proportion of RLN LNM is 26.74%in the thoracic ESCC patients.The results of univariate analysis shows that there are statistically significant differences between the RLN LNM group and the no RLN LNM group in five factors:the degree of tumor differentiation(P=0.019,χ~2=7.898),the location of tumor(P=0.004,χ~2=11.227),depth of tumor invasion(P=0.002,χ~2=14.811),whether tumor invaded nerves(P=0.001,χ~2=6.970),and carina lymph node metastasis(P=0.000,χ~2=23.254).2.The results of multivariate analysis shows that the independent risk factors for RLN LNM in patients with thoracic ESCC are as follows:the location of tumor(P=0.009<0.05,OR=5.132,95%CI 1.507～17.473),the degree of tumor differentiation(P=0.016<0.05,OR=4.349,95%CI 1.311～14.432),the depth of tumor invasion(P=0.036<0.05,OR=3.587,95%CI 1.085～11.863)and subcarinal lymph node metastasis(P=0.045<0.05,OR=5.469,95%CI 1.039～28.797);The area under the ROC curve of each independent risk factor was 0.682,0.723,0.727 and 0.756,respectively.3.The nomogram prediction model of RLN LNM in patients with thoracic ESCC is constructed according to four independent risk factors of the location of tumor,the degree of tumor differentiation,the depth of tumor invasion and subcarinal lymph node metastasis.And the nomogram prediction model is internally verified by using Bootstrap method.The verification results shows that the prediction calibration curve is roughly located between the standard curve and the acceptable line.The result of Hosmer-Lemeshow goodness-of-fit test shows P>0.05and the area under the ROC curve is 0.889.All of these statistics indicate that the model’s predictive ability of RLN LNM in thoracic ESCC is better than individual independent risk factors,and the calibration and discrimination degree are more accurate.Conclusions:1.In this study,the probability of RLN LNM in patients with thoracic ESCC is26.74%.2.The results of univariate analysis shows that gender,age,smoking history,drinking history,tumor family history,abnormal preoperative tumor markers,tumor maximum diameter,vascular cancer thrombus,periesophageal lymph node metastasis,lymph node metastasis in other sites,and the short diameter size of recurrent laryngeal nerve lymph nodes has no significant correlation with RLN LNM.3.The results of binary logistic regression analysis shows that the location of tumor,the degree of tumor differentiation,the depth of tumor invasion,and subcarinal lymph node metastasis are independent risk factors which can affect RLN LNM.(P<0.05)4.The prediction model of this nomogram has good accuracy and discrimination in predicting RLN LNM in ESCC patients,and the prediction ability is better than that of various independent risk factors.The prediction model can provide certain guiding value for predicting RLN LNM in ESCC patients.