Spss statistic 24

Data were organized and analyzed using Microsoft Excel and the statistical program IBM SPSS statistic 24 (IBM, Armonk, Nueva York, USA). Data were expressed as the mean ± SEM and represented the contribution percentage of the food groups to the total content of the polyphenols in the diet.
Differences between the three age groups at baseline were tested by Analysis of Variance (ANOVA) and post hoc analysis, with the Fisher’s least significant difference (LSD) test for multiple comparisons. Linear regression analysis was used to assess the relationship between 8-isoprostane concentrations, Gallic Acid Equivalents (GAE) in urine, and total polyphenol intake. Significance was defined as a value of p < 0.05.
Finally, in order to study the relationships between the different variables that were measured, and to reduce their number to a few factors that help us to interpret their similarities, a Factorial Analysis (FA) was applied. The method used to extract the factors was the Principal Component Analysis. The rotation method applied was the Varimax rotation. For this statistical analysis, the Stat Graphics Centurion XVI software (Stat Point Technologies, Inc., Dallas, TX, USA, 2013) was used.

Analysis of variance (ANOVA) and post-hoc test (Duncan’s multiple range) with a significance level of p < 0.05 were performed using the statistical software package IBM SPSS Statistic 24 (IBM Corp., Armonk, NY, USA) and linear relationships between variables were calculated with Sigma Plot 12.5 (Systat software Inc., San Jose, CA, USA).

Statistical analysis was performed using the computer software “Statistical Package for the Social Sciences” (IBM SPSS Statistic 24.0 Inc., Chicago, IL, USA). In this study p-values of less than 0.05 were considered statistically significant.
The TC database was divided due to the focality into two groups. Group 1, which contained the unifocal BC patients and group 2, consisting of the multifocal and/or multicentric BC patients. Differences between EP3 receptor positive and negative patients—always relating to the focality—influencing the prognosis were tested for significance. Kaplan–Meier Curve analysis was performed for each group to estimate the disease-free and overall survival in EP3 positive and negative patients. By applying the chi-square of the log rank test the significance was determined. As the device for statistical analysis, boxplots and Kruskal–Wallis tests were used. In order to evaluate whether EP3 expression is an independent prognostic factor, multivariate analyses via COX-regression were conducted. For multivariate analysis we included the following factors: tumor size, lymph node status, metastasis, grading, patient age, EP3, VDR, ER, and PR expression.