Using Logistic Regression Analysis Model To Evaluate The Ultrasound Characteristics Of The Benign And Malignant Thyroid Nodules

Purpose: Sonographic features, patient’s gender and age as the independent variablesto indentify the benign and malignant of thyroid nodule, establish a logistic regressionmodel, a benign thyroid nodule. Compare the values of sonographic characteristics, thepatient’s gender, age and other factors in the differential diagnosis of benign and malignantthyroid nodulesthe.Materials and methods: A retrospective analysis of two hundred and eighty six casesof thyroid nodules confirmed by pathology after operation excision,one hundred and eightythree nodules were benign as control group, one hundred and three nodules were malignantas case group. A retrospective collection of two groups of patients with age, the sexualdistinction and the ultrasonographic features of thyroid nodules, including nodule number,diameter, shape, boundary, internal echo level, edge feature, anteroposterior and transversediameter ratio, rear echo attenuation, halo, calcification and the blood flow. In addition,multiple logistic regression analysis with a forward stepwise method for selection ofsignificant variables was performed to determine independent ultrasound predictors formalignancy from the ultrasound characteristics that showed statistical significance(P<0.05). At last Logistic regression model was set up.Results: The t test was used to evaluate the age of patient between the benign andmalignant nodules, the χ2test was used to evaluate the other parameters of two groups. Nosignificant difference between the two groups in the number of nodules (P=0.718), theother parameters of two groups were significant differences between theparameters(P<0.05). According to the output result of SPSS19.0, there were fiveindependent variable selected on the final step of Logistic regression analysis: calcification of nodules,the blood flow, age, capsular invasion,the echo level. There were the five of themore valuable parameter:spiculated margin (OR=20.830,r=2.970), calcification(OR=14.540, r=1.796), age (OR=16.359,r=-0.074), capsular invasion (OR=6.890, r=1.351), marked hypoechogenicity(OR=9.747,r=2.553). The model was: logit(P)=0.719+2.970edge(2)+1.796calcification(3)-0.074age+1.351capsularinvasion(1)+2.553theecho level(4). The likelihood ratio test was used to evaluate the fitting situation of thewhole model.It was statistically significant (χ2=170.571,P=0.000), the modle was used topredict the two hundred and eighty six thyroid nodules. The modle could distinguish thetwo kinds of nodules. When the regression value P was more than0.5, the prediction wasmalignant nodules. When the regression value P was less the or equal to0.5, the predictionwas benign nodules. The correct rate of prediction was85.3%.Conclusion:①Thyroid nodules which were single or multiple can be helpless todifferential diagnosis of benign and malignant.②Five of fifteen independent variableswere selected by Logistic regression analysis: the age of patients, calcification, edgefeatures, capsular invasion, the echo level.③The age of patients was negatively correlatedwith malignant, the smaller the age, the more possibility of malignant thyroid nodules were.④Spiculated margin, microcalcification, capsular invasion and marked hypoechogenicityare positively correlated with malignant thyroid nodules, this four ultrasonic characteristicsmore appeared, the more possibility of malignant thyroid nodules were.⑤According theimportance of the model, arranged from high to low is: spiculated margin＞age＞microcalcification＞marked hypoechogenicity＞capsular invasion.⑥The binary Logisticregression model with the sonographic characteristics and the patients age can be helpful todifferentiation of benign and malignant thyroid nodules.