HBX Multi-Mutations Combined With Traditional Screening Indicators to Establish a Nomogram Contributes to Precisely...

Hepatocellular carcinoma (HCC) is one of the most prevalent malignant tumors, often diagnosed at an advanced stage with limited treatment options and a poor prognosis. The present study aimed to identify the risk factors (RFs) for HCC and develop a nomogram incorporating dominant HBX mutations to predict the risk of HCC occurrence in high-risk (HR) populations.

We collected early HCC screening and monitoring factors from cohorts of HCC patients and HR populations, including gender, age, AFP, ALT, as well as hepatitis B virus (HBV) infection and mutation indicators such as hepatitis B surface antigen (HBsAg), HBV DNA replication level, HBV genotype, and high-frequency mutations in HBX. Independent predictive factors for HCC onset were determined through both univariate and multivariate logistic regression analyses. Two nomograms with and without HBX mutation data were established to predict the risk of HCC incidence in HR populations, and their performance was evaluated using calibration curves, receiver operating characteristic (ROC) curves, as well as decision curve analysis (DCA).

A total of 312 participants were included. Independent RFs for HCC onset were identified as A1762T+G1764A multi-mutations, T1753C/G/A+A1762T+G1764A multi-mutations, and ALT > 40 U/L. The area under the curve (AUC) of the diagnostic nomogram with HBX mutation data was 0.835 in the training set and 0.869 in the testing set for the nomogram. Besides, the AUC of the diagnostic nomogram without HBX mutation data in the training set was 0.798 and 0.818 in the testing set. The calibration curve together with DCA indicated that the nomogram containing HBX mutation data had better predictive performance.

The established nomograms predicted the risk of HCC occurrence in HR populations with good accuracy, providing a valuable reference for precise stratification of HR populations and HCC screening.