A Logistic Regression Model for Noninvasive Prediction of AFP-Negative Hepatocellular Carcinoma

作者：Changliang Luo, Yuan Rong, Hao Chen, Wu-Wen Zhang, Long Wu, Wei Diao, Xiuqi Wei, Lie-Jun Mei, Fubing Wang · 发表于：Technology in Cancer Research & Treatment · 年份：2019 · DOI：10.1177/1533033819846632 · 被引用次数：28 · 研究领域：Hepatocellular Carcinoma Treatment and Prognosis、Liver Disease Diagnosis and Treatment、Inflammatory Biomarkers in Disease Prognosis

α-Fetoprotein is commonly used in the diagnosis of hepatocellular carcinoma. However, the diagnostic significance of α-fetoprotein has been questioned because a number of patients with hepatocellular carcinoma are α-fetoprotein negative. It is therefore necessary to develop novel noninvasive techniques for the early diagnosis of hepatocellular carcinoma, particularly when α-fetoprotein level is low or negative. The current study aimed to evaluate the diagnostic efficiency of hematological parameters to determine which can act as surrogate markers in α-fetoprotein-negative hepatocellular carcinoma. Therefore, a retrospective study was conducted on a training set recruited from Zhongnan Hospital of Wuhan University-including 171 α-fetoprotein-negative patients with hepatocellular carcinoma and 102 healthy individuals. The results show that mean values of mean platelet volume, red blood cell distribution width, mean platelet volume-PC ratio, neutrophils-lymphocytes ratio, and platelet count-lymphocytes ratio were significantly higher in patients with hepatocellular carcinoma in comparison to the healthy individuals. Most of these parameters showed moderate area under the curve in α-fetoprotein-negative patients with hepatocellular carcinoma, but their sensitivities or specificities were not satisfactory enough. So, we built a logistic regression model combining multiple hematological parameters. This model presented better diagnostic efficiency with area under the curve of 0.922...