The Clinical Study Of Solitary Pulmonary Nodule Diagnosis By Combining Of CT And Tumor Markers

Background: Lung cancer is one of the most common malignant tumors,and remains most lethal cancer.Because the majority of lung cancer patients are advanced,the prognosis is extremely poor.Based on relevant data,5-year survival rate of stage IA lung cancer patients can reach 95%,while 19% in stage IIIA.Therefore,the importance of early diagnosis of lung cancer is obviously clear.With the application of low-dose spiral computed tomography(LDCT)in the physical examination,numerous pulmonary nodules are found.Lacking effective diagnostic tools,the current diagnosis of benign and malignant pulmonary nodules is difficult.In our study,CT features and tumor markers of solitary pulmonary nodules(SPN)were used to probe whether the combination of them could enhance the sensitivity and specificity of SPN diagnosis and provide references for clinical works.Methods: The patients are divided into group A and group B.Group A(88 cases of pathologically confirmed SPNs,from March,2015 to June,2016)were used to validate the sensitivity and specificity of mathematical model established by department of Thoracic Surgery,Peking University People’s Hospital.(1)Probability of malignant = ex/(1+ex),(2)x=-4.496 +(0.07×age)+(0.676×diameter)+(0.736×spiculation)+(1.267×family history of cancer)-(1.615×calcification)–(1.408×caler border);e is the base of natural logarithms,while x is the regression coefficient in the logistic regression.In group B(94 cases of pathologically confirmed SPNs,from June,2016 to January,2018),the sensitivity and specificity are used to evaluate the predicting ability of mathematical model,the levels of tumor markers(CEA,NSE,CYFRA 21-1,SCC)and combination of mathematical model and tumor markers.Results: The consistency of SPN predicting mathematical model was good,which was verified by the 88 cases of group A.Among group B,72(76.6%)SPNs were malignant,and 22(23.4%)SPNs were benign.Using mathematical model,the sensitivity was 94.44%,the specificity was 77.27%,the positive predictive value was 94.44%,the negative predictive value was 77.27%,and AUC was 0.881±0.051(P<0.001).Using tumor markers,the sensitivity was 45.83%,the specificity was 63.64%,the positive predictive value was 80.49%,the negative predictive value was 26.42%,and AUC was 0.547±0.070(P=0.503).Combining mathematical model and tumor markers,the sensitivity was 95.83%,the specificity was 68.18%,the positive predictive value was 92.00%,the negative predictive value was 78.95%,and AUC was 0.813±0.062(P<0.001).Conclusion: 1.Mathematical model has good clinical value for differential diagnosis of benign and malignant SPN.2.Tumor markers have no obvious predictive value for benign and malignant SPN.3.CT combined with tumor markers can ensure the sensitivity of SPN benign and malignant predictions,but the specificity reduces.