Fig. 7: Performance of the P4 model in predicting people at high risk of HCC in prospective validation cohort.

a Performance of the P4 score, serum biomarkers (AFP, PIVKA-II, AFP + PIVKA-II), and early diagnosis score models (ASAP and aMAP score model) for LC patients (n = 76) in prospective validation set to predict LC patients who developed to HCC at subsequent follow up. The upper panel illustrated ROC curves, and the lower panel showed the AUC, sensitivity, and specificity. b Differences of P4 scores between LC patients who developed HCC (n = 11) and LC patients who did not develop HCC (n = 65) in the validation cohort. Significance was determined by Wilcoxon test with Benjamini-Hochberg multiple test adjustment. Box plots indicate median (middle line), 25%, 75% percentile (box) and minimum and maximum (whiskers) as well as outliers (single points). c Confusion matrix showed P4 panel performance for predicting people at high risk of HCC in the validation cohort (n = 76). d The categorization of imaging results, P4 scores, serum biomarkers, ASAP model and aMAP score results of 11 LC patients in the validation cohort who developed HCC during follow-up was shown in each color-code plot. Blue indicated positive, gray indicated negative, while pink indicated no detection. e Time distribution of P4 panel predicted HCC occurrence earlier than imaging results. f The concordance comparison of P4 scores, serum biomarkers and risk scores compared with positive and negative of CT/MRI scan results during HCC occurrence. g The time-course demonstration of imaging results and quantified levels of P4 scores, serum biomarkers and risk scores during the clinical course of 11 patients who developed HCC. The corresponding cutoffs were indicated by dashed lines. Source data are provided as a Source Data file.