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.