Statistical analysis
In our study, 22.0 version (IBM, Armonk, NY, USA) of the SPSS (Statistical Package for the Social Sciences) program was used for statistical analysis of data. Descriptive statistics, discrete​ ​and continuous numerical variables were expressed as mean, ± standard deviation or median (minimum-maximum). Categorical variables were expressed as number of cases (%). Cross table statistics were used to compare categorical variables (Chi-Square, Fisher’ exact test). Normally distributed parametric data were compared with Student’s t-test and non-parametric data that did not meet normal distribution were compared with Mann Whitney U and Kruskal Wallis tests. Correlation analysis was performed by Pearson or Spearman method according to normality distribution. ​Kaplan-Meier and log-rank methods were used for survival analysis. Multivariate analysis was performed by using logistic regression. Sensitivity and specificity calculation were performed by Receiver operating characteristic (ROC) analysis. p<0.05 value was considered statistically significant.