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A novel score based on a combination of cytokeratins and routine laboratory tests provided a more accurate diagnosis of HCC versus serum α-fetoprotein alone.
A new model based on cytokeratin 18 (CK18), cytokeratin 19 (CK19), albumin, platelet count, and α-fetoprotein (AFP) may offer a refined approach for detecting hepatocellular carcinoma (HCC) in patients with hepatitis C virus (HCV).1
The model, coined the CK-HCC score, outperformed AFP alone for discriminating patients with HCC from those with liver cirrhosis by incorporating additional routine laboratory tests, offering a potential noninvasive alternative to liver biopsy in this high-risk patient population.1
“There was an urgent need to identify more accurate and sensitive biomarkers for early detection of HCC patients,” Mahdi Al Haddad, of the department of chemistry at Helwan University in Egypt, and colleagues wrote.1
The most common type of primary liver cancer, HCC occurs most often in people with chronic liver diseases, such as cirrhosis caused by viral hepatitis. People with long-term liver diseases and scarring on the liver are at an increased risk of HCC. Early detection is essential for ensuring prompt treatment and improving outcomes, underscoring the need for reliable biomarkers to detect HCC in its early stages.2
To develop a novel score for accurately detecting HCC, investigators recruited patients with liver cirrhosis who developed HCC (n = 75) from the Damietta Cancer Institute from October 2017 - December 2018. In addition to the group of patients with HCC, investigators included a second group of patients with HCV with liver cirrhosis but no evidence of malignancy (n = 50) as well as a control group of healthy individuals with no evidence of any hepatitis markers (n = 20).1
Prior to applying any therapy protocol, 10 milliliters of blood was collected from each patient to assess laboratory values and assay serum CK18, CK19, AFP, albumin, and platelet count. Investigators then assessed their diagnostic accuracy for discriminating HCC from liver cirrhosis by plotting receiver operating characteristic (ROC) curves and selecting the best collection parameters based on their diagnostic utility.1
In order to enhance the diagnostic performance of AFP alone, investigators combined AFP (Area under curve [AUC], 0.692) with other biomarkers of high AUC, including CK19 (0.864), albumin (0.811), CK18 (0.795), and platelet count (0.783). The proposed model, CK-HCC, is as follows:
Investigators pointed out the score had a wide range from -0.68 to 4.2 and it showed notable significance for differentiating patients with HCC from those with cirrhosis (P <.001). Compared to AFP, CK-HCC produced a greater AUC for distinguishing HCC from cirrhosis (0.919 vs 0.692). The greatest sensitivity (94%) and specificity (91%) were taken at a cut-off of 1.3, where above 1.3, the patient is considered to have HCC, and below 1.3, the patient is considered to have cirrhosis.1
Additionally, investigators noted CK-HCC was superior to AFP for differentiating patients with low TNM stage, complete capsulation, low grade, small tumor size, absence of vascular invasion, and single focal lesions. Specifically, AFP alone had a weak diagnostic power for differentiating patients with HCC with small tumor size from those with cirrhosis (AUC, 0.512) versus the CH-HCC score, which produced an AUC of 0.756. Additionally, AFP was unable to discriminate patients with a low tumor grade from those with cirrhosis (AUC, 0.501) compared with the AUC of 0.815 produced by the CK-HCC score.1
“For the first time, we report the clinical validation of four biomarkers (CK19, CK18, albumin, and platelets count) in combination with AFP to improve the accuracy for diagnosis of HCC among hepatitis C high-risk patients,” investigators concluded.1
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