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Issue in Statistical Strategy In Case-Control StudyTo the Editor:We read with great interest the article by Aleksandrova and colleagues in HEPATOLOGY, 1 which gave us a new view of biomarkers of inflammation and hyperinsulinemia as predictors for hepatocellular carcinoma (HCC) among the general population. Indeed, inflammation biomarkers presented promising predictive capability in malignant disease, according to mounting evidence including our studies. 2 However, the population epidemic characteristics were not parallel among the groups. This study utilized risk-set sampling to identify the control group with paired factors including matched sex, age, date of blood collection, fasting status, time of the day at blood collection, menopausal status, and exogenous hormone use at blood donation. However, chronic hepatitis B virus (HBV) infection and chronic hepatitis C virus (HCV) infection were included as matching characteristics. It is widely accepted that chronic HBV or HCV infection is a major causes of HCC. 3 Thus, it might be more appropriate to include HBV and HCV infection in paired parameters. As a result, patients in the HCC group and the control group presented different status of HBV/HCV infection, which might lead to the different incidence rates of HCC among the population. The authors used a multivariable study to exclude the influence of the epidemic bias on their targets and reached acceptable results. However, the unparalleled patient characteristics might limit the practical value of this study.In summary, as suggested by Aleksandrova and colleagues, 1 higher circulating concentrations of interleukin-6, C-reactive protein, C-peptide, non-high-molecular weight adiponectin, and glutamate dehydrogenase were potentially associated with higher risk of HCC. Further study is needed to identify their value in practical usage.