Prism 6 program for windows

Categorical data are expressed as numbers (%), and numerical data are expressed as the mean and standard deviation for normally distributed data. For non-normally distributed data, the data are expressed as medians with interquartile ranges. To analyze the differences in hsa_circ_0003570 expression between the tumor and adjacent nontumor tissues, a paired t-test was used. To compare the clinicopathological characteristics between the two groups according to the hsa_circ_0003570 expression, we used the chi-square or Fisher’s exact probability test. Using the Kaplan–Meier method and log-rank test, we analyzed patient survival and compared survival between the groups. To identify the predictors of survival, we performed a logistic regression based on the Cox proportional hazards model. The statistical significance was set at p < 0.05. We conducted all the analyses using R statistical software 3.6.3 (the R foundation for Statistical Computing, Vienna, Austria; available at http://www.r-project.org, accessed on 5 March 2020), and the GraphPad Prism 6 program for Windows (GraphPad Software, La Jolla, CA, USA) was used to generate figures.

For descriptive statistics, categorical data were expressed as number (%) and numerical data as the mean and standard deviation for normally distributed data and as the median with interquartile range for non-normally distributed data. A paired t-test was used to analyse differences in hsa_circ_0005986 expression between HCC and adjacent non-tumor tissue. We used the chi-square or Fisher’s exact probability test to compare clinicopathological characteristics between two groups with different hsa_circ_0005986 expressions. The Kaplan–Meier method was used to generate survival curves, and the log-rank test was conducted to compare survival curves between groups. The prognostic performances^{30 (link)} of hsa_circ_0005986 were expressed as specificity, sensitivity, and area under the receiver operating curve (AUC). To determine the predictors of survivals, univariate and multivariate analyses based on a Cox proportional hazards model were performed. p-values of < 0.05 were considered statistically significant. Values that were statistically significant in univariate analyses were included in multivariate analyses, with a p-value of < 0.1. We conducted all the analyses using SAS version 9.4 software (SAS Institute Inc., Cary, NC, USA), and GraphPad Prism 6 program for Windows (GraphPad Software, La Jolla, CA, USA) was used to generate figures.