Dataset Information

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

ABSTRACT: ?-Fetoprotein is commonly used in the diagnosis of hepatocellular carcinoma. However, the diagnostic significance of ?-fetoprotein has been questioned because a number of patients with hepatocellular carcinoma are ?-fetoprotein negative. It is therefore necessary to develop novel noninvasive techniques for the early diagnosis of hepatocellular carcinoma, particularly when ?-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 ?-fetoprotein-negative hepatocellular carcinoma. Therefore, a retrospective study was conducted on a training set recruited from Zhongnan Hospital of Wuhan University-including 171 ?-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 ?-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, sensitivity of 83.0%, and specificity of 93.1%. In addition, the 4 validation sets from different hospitals were used to validate the model. They all showed good area under the curve with satisfactory sensitivities or specificities. These data indicate that the logistic regression model combining multiple hematological parameters has better diagnostic efficiency, and they might be helpful for the early diagnosis for ?-fetoprotein-negative hepatocellular carcinoma.

SUBMITTER: Luo CL

PROVIDER: S-EPMC6535757 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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

Luo Chang-Liang CL Rong Yuan Y Chen Hao H Zhang Wu-Wen WW Wu Long L Wei Diao D Wei Xiu-Qi XQ Mei Lie-Jun LJ Wang Fu-Bing FB

Technology in cancer research & treatment 20190101

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 parame ...[more]

PMID: 31106685

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Project description:Hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) is prevalent worldwide. Despite its limitations, serum alpha-fetoprotein (AFP) remains the most widely-used biomarker for the diagnosis of HCC. This study aimed to assess whether measurement of peripheral plasma Dickkopf-1 (DKK1) and Tie2-expressing monocytes (TEMs) could overcome the limitations of AFP and improve the diagnostic accuracy of HCC.Plasma DKK1 level and the percentage of TEMs in peripheral CD14+CD16+ monocytes from HCC patients (n = 82), HBV-related liver cirrhosis (LC) patients (n = 29), chronic hepatitis B (CHB) infected patients (n = 28) and healthy volunteers (n = 31) were analyzed by ELISA and flow cytometry. Receiver operating characteristic (ROC) curves were used to analyze a single biomarker, or a combination of two or three biomarkers. Univariate and multivariate analyses were performed to assess the significance of each marker in prediction of HCC and AFP-negative HCC from LC patients.The percentage of TEMs in peripheral CD14+CD16+ monocytes and plasma level of DKK1 in HCC group were significantly higher than those in LC, CHB and healthy control groups (all P-values <0.05). The percentage of TEMs alone was also significantly higher in AFP-negative HCC group than that in LC, CHB and healthy control groups (all P-values <0.05). Plasma DKK1 level alone could not distinguish between AFP-negative HCC and LC patients. ROC curves showed that the optimal diagnostic cutoff value was 550.93 ng/L for DKK1 and 4.95% for TEMs. There was no significant difference in AUC of DKK1, TEMs and AFP in HCC diagnosis between the four groups (all P>0.05). A combination of DKK1, TEMs and AFP measurements increased the AUC for HCC diagnosis as compared with either marker alone (0.833; 95%CI 0.768-0.886). The AUC for TEMs was 0.692 (95% CI 0.564-0.819) in differentiating AFP-negative HCC from LC, with a sensitivity of 80.0% and a specificity of 65.52%. Only TEMs prevailed as a significant predictor for AFP-negative HCC differentiating from LC patients in univariate and multivariate analyses (P = 0.016, P = 0.023).TEMs and DKK1 may prove to be potential complementary biomarkers for AFP in the diagnosis of HCC. TEMs rather than DKK1 could serve as a complementary biomarker for AFP in the differential diagnosis of AFP-negative HCC versus LC patients.

Dataset Information

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

Publications

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

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