Statistical Method
In descriptive analyzes, continuous variables are presented as
mean±standard deviation or median (25th-75th percentile) and categorical
variables as a percentage(%). The compliance of the data to normal
distribution was evaluated using the Shapiro-Wilk test. If the data has
a normal distribution, a t-test was used to compare two groups; under
non-parametric conditions, the Mann-Whitney U test was used. Comparison
of continuous variables between three and more categories was used the
one-way ANOVA or the non-parametric equivalent of the Kruskal-Wallis
test. The power of the correlation between two continuous variables was
assessed with the Spearman correlation analysis. Accordingly, the
correlation coefficient(r) values <0.2 show very weak or no
correlation, values from 0.2-0.4 show weak correlation, from 0.4-0.6
show moderate correlation, 0.6-0.8 show a high correlation, and
values>0.8 are interpreted as very high correlation.
Interobserver agreement was evaluated by using kappa coefficients(κ),
were computed and assessed as follows: 0.01–0.20, slight agreement;
0.21–0.40, fair agreement; 0.41–0.60, moderate agreement; 0.61–0.80,
substantial agreement; and 0.81–0.99, almost perfect agreement. To
evaluate the success of the obtained variables, to diagnose prostate
cancer and to determine cut-off points, ROC analysis was used with the
area under the curve(AUC) used to calculate sensitivity, specificity,
positive predictive value(PPV), and negative predictive value(NPV). SPSS
22.0 and MEDCALC programs were used for statistical analyses.
p<0.05 was accepted as statistically significant.