AUTHOR=Liu Long , Wang Qi , Zhao Xiaohong , Huang Yuxi , Feng Yuyi , Zhang Yu , Fang Zheping , Li Shaowei 

TITLE=Establishment and validation of nomogram model for the diagnosis of AFP-negative hepatocellular carcinoma

JOURNAL=Frontiers in Oncology

VOLUME=Volume 13 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2023.1131892

DOI=10.3389/fonc.2023.1131892

ISSN=2234-943X

ABSTRACT=As one of the most common malignant tumors in clinical practice, hepatocellular carcinoma (HCC) is a major threat to human health, where alpha-fetoprotein (AFP) is widely used for early screen-ing and diagnoses. However, the level of AFP would not elevate in about 30-40% of HCC patients, which is clinically referred to as AFP-negative HCC (AFP-NHCC), with small tumors at an early stage and atypical imaging features, making it difficult to distinguish benign from malignant by imaging alone. A total of 798 patients were enrolled in the study and were randomized 2:1 to the training and validation groups. An unordered multicategorical logistic regression analyses showed that the age, TBIL, ALT, ALB, PT, GGT and GPR help identify non-hepatic disease, hepa-titis, cirrhosis, and hepatocellular carcinoma. A multivariate logistic regression analyses showed that the gender, age, TBIL, GAR, and GPR were independent predictors for the diagnosis of AFP-NHCC. And an efficient and reliable nomogram model (AUC=0.837) was constructed based on independent predictors, which could be used as a marker for the diagnosis of AFP-NHCC, providing an objective basis for the early diagnosis and individualized treatment of hepatocel-lular carcinoma patients.