Early detection of hepatocellular carcinoma co-occurring with hepatitis C virus infection: A mathematical model.
OBJECTIVE
To develop a mathematical model for the early detection of hepatocellular carcinoma (HCC) with a panel of serum proteins in combination with α-fetoprotein (AFP).


METHODS
Serum levels of interleukin (IL)-8, soluble intercellular adhesion molecule-1 (sICAM-1), soluble tumor necrosis factor receptor II (sTNF-RII), proteasome, and β-catenin were measured in 479 subjects categorized into four groups: (1) HCC concurrent with hepatitis C virus (HCV) infection (n = 192); (2) HCV related liver cirrhosis (LC) (n = 96); (3) Chronic hepatitis C (CHC) (n = 96); and (4) Healthy controls (n = 95). The R package and different modules for binary and multi-class classifiers based on generalized linear models were used to model the data. Predictive power was used to evaluate the performance of the model. Receiver operating characteristic curve analysis over pairs of groups was used to identify the best cutoffs differentiating the different groups.


RESULTS
We revealed mathematical models, based on a binary classifier, made up of a unique panel of serum proteins that improved the individual performance of AFP in discriminating HCC patients from patients with chronic liver disease either with or without cirrhosis. We discriminated the HCC group from the cirrhotic liver group using a mathematical model (-11.3 + 7.38 × Prot + 0.00108 × sICAM + 0.2574 × β-catenin + 0.01597 × AFP) with a cutoff of 0.6552, which achieved 98.8% specificity and 89.1% sensitivity. For the discrimination of the HCC group from the CHC group, we used a mathematical model [-10.40 + 1.416 × proteasome + 0.002024 × IL + 0.004096 × sICAM-1 + (4.251 × 10(-4)) × sTNF + 0.02567 × β-catenin + 0.02442 × AFP] with a cutoff 0.744 and achieved 96.8% specificity and 89.7% sensitivity. Additionally, we derived an algorithm, based on a binary classifier, for resolving the multi-class classification problem by using three successive mathematical model predictions of liver disease status.


CONCLUSIONS
Our proposed mathematical model may be a useful method for the early detection of different statuses of liver disease co-occurring with HCV infection.
Abdel-Rahman Nabawy Zekri, Amira Salah El-Din Youssef, Yasser Mabrouk Bakr, Reham Mohamed Gabr, Ola Sayed Ahmed, Mostafa Hamed Elberry, Ahmed Mahmoud Mayla, Molecular Virology and Immunology Unit, Cancer Biology Department, National Cancer Institute, Cairo University, Cairo 11976, Egypt.
Abdel-Rahman Nabawy
AR
Zekri
Abdel-Rahman Nabawy Zekri, Amira Salah El-Din Youssef, Yasser Mabrouk Bakr, Reham Mohamed Gabr, Ola Sayed Ahmed, Mostafa Hamed Elberry, Ahmed Mahmoud Mayla, Molecular Virology and Immunology Unit, Cancer Biology Department, National Cancer Institute, Cairo University, Cairo 11976, Egypt.
Amira Salah El-Din
AS
Youssef
Abdel-Rahman Nabawy Zekri, Amira Salah El-Din Youssef, Yasser Mabrouk Bakr, Reham Mohamed Gabr, Ola Sayed Ahmed, Mostafa Hamed Elberry, Ahmed Mahmoud Mayla, Molecular Virology and Immunology Unit, Cancer Biology Department, National Cancer Institute, Cairo University, Cairo 11976, Egypt.
Yasser Mabrouk
YM
Bakr
Abdel-Rahman Nabawy Zekri, Amira Salah El-Din Youssef, Yasser Mabrouk Bakr, Reham Mohamed Gabr, Ola Sayed Ahmed, Mostafa Hamed Elberry, Ahmed Mahmoud Mayla, Molecular Virology and Immunology Unit, Cancer Biology Department, National Cancer Institute, Cairo University, Cairo 11976, Egypt.
Reham Mohamed
RM
Gabr
Abdel-Rahman Nabawy Zekri, Amira Salah El-Din Youssef, Yasser Mabrouk Bakr, Reham Mohamed Gabr, Ola Sayed Ahmed, Mostafa Hamed Elberry, Ahmed Mahmoud Mayla, Molecular Virology and Immunology Unit, Cancer Biology Department, National Cancer Institute, Cairo University, Cairo 11976, Egypt.
Ola Sayed
OS
Ahmed
Abdel-Rahman Nabawy Zekri, Amira Salah El-Din Youssef, Yasser Mabrouk Bakr, Reham Mohamed Gabr, Ola Sayed Ahmed, Mostafa Hamed Elberry, Ahmed Mahmoud Mayla, Molecular Virology and Immunology Unit, Cancer Biology Department, National Cancer Institute, Cairo University, Cairo 11976, Egypt.
Mostafa Hamed
MH
Elberry
Abdel-Rahman Nabawy Zekri, Amira Salah El-Din Youssef, Yasser Mabrouk Bakr, Reham Mohamed Gabr, Ola Sayed Ahmed, Mostafa Hamed Elberry, Ahmed Mahmoud Mayla, Molecular Virology and Immunology Unit, Cancer Biology Department, National Cancer Institute, Cairo University, Cairo 11976, Egypt.
Ahmed Mahmoud
AM
Mayla
Abdel-Rahman Nabawy Zekri, Amira Salah El-Din Youssef, Yasser Mabrouk Bakr, Reham Mohamed Gabr, Ola Sayed Ahmed, Mostafa Hamed Elberry, Ahmed Mahmoud Mayla, Molecular Virology and Immunology Unit, Cancer Biology Department, National Cancer Institute, Cairo University, Cairo 11976, Egypt.
Mohamed
M
Abouelhoda
Abdel-Rahman Nabawy Zekri, Amira Salah El-Din Youssef, Yasser Mabrouk Bakr, Reham Mohamed Gabr, Ola Sayed Ahmed, Mostafa Hamed Elberry, Ahmed Mahmoud Mayla, Molecular Virology and Immunology Unit, Cancer Biology Department, National Cancer Institute, Cairo University, Cairo 11976, Egypt.
Abeer A
AA
Bahnassy
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D019540:Area Under Curve; D014408:Biomarkers, Tumor / Q000097:blood*; D006528:Carcinoma, Hepatocellular / Q000097:blood / Q000175:diagnosis* / Q000821:virology; D016009:Chi-Square Distribution; D003937:Diagnosis, Differential; D055088:Early Detection of Cancer; D004534:Egypt; D005260:Female; D006526:Hepatitis C / Q000097:blood / Q000150:complications / Q000175:diagnosis*; D006801:Humans; D018799:Intercellular Adhesion Molecule-1 / Q000097:blood; D016014:Linear Models; D008103:Liver Cirrhosis / Q000097:blood / Q000175:diagnosis / Q000821:virology; D008113:Liver Neoplasms / Q000097:blood / Q000175:diagnosis* / Q000821:virology; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011237:Predictive Value of Tests; D046988:Proteasome Endopeptidase Complex / Q000097:blood; D012372:ROC Curve; D015203:Reproducibility of Results; D012189:Retrospective Studies; D055815:Young Adult; D000509:alpha-Fetoproteins / Q000032:analysis; D051176:beta Catenin / Q000097:blood
C097353:AFP protein, human; D014408:Biomarkers, Tumor; C495270:CTNNB1 protein, human; C573420:ICAM1 protein, human; D000509:alpha-Fetoproteins; D051176:beta Catenin; D018799:Intercellular Adhesion Molecule-1; D046988:Proteasome Endopeptidase Complex
Hepatocellular carcinoma; Interleukin-8; Mathematical model; Proteasome; Soluble intercellular adhesion molecule-1; Soluble tumor necrosis factor receptor II; α-fetoprotein; β-catenin