Establishment and validation of nomogram model for the diagnosis of AFP-negative hepatocellular carcinoma - Liu, Long; Wang, Qi; Zhao, Xiaohong; Huang, Yuxi; Feng, Yuyi; Zhang, Yu; Fang, Zheping; Li, Shaowei (Frontiers in Oncology, 2023)
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.