Fig. 4

The nomogram was constructed by combining CEA (0 represents ≤ 5 ng/mL; 1 represents > 5 ng/mL), maximum diameter, spiculation (0 represented absence of the sign; 1 represented presence of the sign), vacuole sign (0 represented absence of the sign; 1 represented presence of the sign). Each variable was awarded a score on the point scale axis. The total score was obtained by adding each single score and by projecting the total score to the lower total point scale, the estimated probability of lymphovascular invasion in lung adenocarcinoma could be obtained, there was an example of the nomogram in clinical application (a). The ROC curves of the nomogram (b), including training set (AUC = 0.800) and test set (AUC = 0.790). The calibration curves for the nomogram. The x-axis represented the nomogram-predicted probability and the y-axis represented the actual probability of lymphovascular invasion. Perfect prediction performance would correspond to the 45° black solid line. The calibration curve showed a good calibration of the nomogram in the training and test sets (c, d). Decision curve analysis based on the multi-parameter model nomogram (e). The ordinate represented the net benefit rate, and the abscissa was the threshold probability. Red line represented the nomogram. Gray curve represented that all patients were LVI-positive. Black transverse lines represented all patients who were LVI-negative. Compared with all LVI-negative patients (black horizontal line) or all LVI-positive patients (grey curve), the nomogram offered the highest clinical net benefit within a threshold range of 0.20–0.85