Research Paper Advance Articles

Development and validation of a nomogram for preoperative prediction of cervical lymph node involvement in thyroid microcarcinoma

Figure 1. Demographic and clinicopathological characteristics screening applying the LASSO logistic regression model. Final predictors include age, race, sex, extension, multifocality, tumor size. (A) Suitable parameter (λ) selection in the LASSO model used 5-fold cross-validation via minimum criteria [3840]. We plotted the partial likelihood deviance (binomial deviance) curve versus log (λ). 2 dotted vertical lines were drawn at the optimal values applying the minimum criteria and the 1 standard error of the minimum criteria (the 1-SE criteria). (B) LASSO coefficient profiles of the 6 variables. We produced a coefficient profile plot against the log (λ) sequence. A suitable λ was chosen when log (λ)= -5 and resulted in 6 variables with nonzero coefficients. LASSO=least absolute shrinkage and selection operator, SE=standard error.