Multivariate analysis in solitary cold thyroid nodules for the diagnosis of malignancy

A stepwise logistic regression (SLR) was performed on 162 patients with a solitary and cold thyroid nodule in order to discriminate between malignant and benign lesions. Sixteen variables were recorded for each patient. The predictions of the logistic regression model were compared to the histological diagnoses in order to evaluate the accuracy of the classification. The value of the logistic function (LF) was calculated for each patient. Using the ROC curve approach, an optimum threshold value (OTV) corresponding to a 100% sensitivity was defined. The classification obtained with the OTV was validated using a cross-validation procedure (CVP). The significant variables selected by the SLR are (from the most significant to the least significant): cytologic result, sex, irregular margin on the Tc scintigraphy and homogeneity on the ultrasound examination. The OTV corresponds to a specificity of 73% for a sensitivity of 100%. The specificity and the sensitivity obtained with the CVP are 73% and 96% respectively. In conclusion, the classification of the patients according to the value of the LF is a highly accurate diagnostic procedure.