Propensity score matching (PSM) was applied to reduce selection bias between the study groups. Age, sex, diabetes mellitus, hepatitis B, hepatitis C, liver cirrhosis, Child-Pugh grade, tumor size, tumor number and microvascular invasion were selected as independent variables. The greedy method of NCSS 10 Statistical Software (LLC, Kaysville, UT, USA) was used for matching the study groups in a 1:4 ratio; the caliper width was 0.2 of the standard deviation of the propensity score between study groups. The standardized mean difference (SMD) was used to evaluate covariate balance after PSM.

Demographic data were compared between groups using Fisher’s exact test or the chi-square test, as appropriate. Continuous variables are expressed as the median ± interquartile range (IQR). The Kaplan-Meier method was used to plot the RFS and OS curves stratified by chemopreventive agent use and the curves were compared using the log-rank test. Factors that were significant in the univariate analysis (p < 0.05) were included in multivariate analyses of OS and RFS using a Cox forward stepwise variable selection process. Hazard ratios (HR) and 95% confidence intervals (CI) were also calculated for each factor. Statistical analyses were performed using SPSS 22.0 software (SPSS Inc., Chicago, IL, USA). All statistical tests were two-sided; p-values < 0.05 were considered significant.

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