Spss statistics for windows version 19

For statistical analysis, “IBM SPSS statistics for Windows Version 19.0” (Armonk, NY, IBM Corp.) computer package program used. Continuous variables are expressed as mean±standard deviation, categorical data as frequency, and percentage (n%). Whether continuous variables are normally distributed was tested using the Kolmogorov–Smirnov test. In comparison of binary groups, independent sample t-test was used for normally distributed variables and Mann–Whitney U test was used for variables that did not present normal distribution. Pearson correlation tests were used for parametric variables to determine the linear relationship between the variables. Whether various variables are independent risk factors affecting the height of NLR and PLR that were investigated using the logistic regression model. In multivariate analyzes, the independent effects of possible risk factors on predicting survival were analyzed by backward selection method using Cox regression analysis. Values for possible risk factors were determined using the Receiver Operating Characteristic to perform survival analysis. The effect of the levels of risk factors on survival was investigated with Log Rank (Mantel-Cox) test. Survival rates were calculated using the Kaplan–Meier method. Statistical significance limit was accepted as p<0.05.

All independent continuous variables are expressed as median with range and all independent categorical variables and outcome variables are expressed in frequencies and percentages. The association between the independent continuous variables and the outcome variables (neurological outcome and mortality) were assessed using the Mann–Whitney
Utest. The association between the independent categorical variables and the outcome variables were assessed using the chi-square test or Fisher's exact test. All statistical analyses were carried out at a 5% level of significance. The data were analyzed using the SPSS software version 19.0 (IBM Corp. Released 2010. IBM SPSS Statistics for Windows, Version 19.0. Armonk, NY: IBM Corp).

Continuous data are reported as mean ± standard deviation (range) and were compared using Wilcoxon-Mann-Whitney test. Differences between the two groups for continuous variables were analyzed with Wilcoxon-Mann-Whitney test, while differences in dummy variables were analyzed with Fisher exact test. Statistical significance was set at p<0.05. Statistical analyses were performed using IBMSPSS Statistics for Windows, Version 19.0 (IBM Corp., Armonk, NY, USA).

MZmine 2.0 and SIMCA (version 14.1; Umetrics, Malmö, Sweden) were used for peak detection and establishing the principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS‐DA) model.22, 23 Preliminary selection of differential metabolites was accomplished using the corresponding variable importance (VIP) value, coefficient plot and s‐plot. IBM SPSS Statistics for Windows, version 19.0 (IBM Corp., Armonk, NY, USA) was used for data analysis. Two‐tailed Wilcoxon rank‐sum tests were used to compare metabolite expression levels for 2‐sample tests: NC vs LC, LC vs MT. Steel‐Dwass tests were used for multiple comparisons between all groups: NC vs LC vs MT. Two‐tailed t test was used to compare pairwise differences in expression in cells, and ANOVA was used for comparisons involving multiple cells. The threshold for significance was P < .05 for all tests. Association between metabolite expression level and cell invasiveness was assessed by Pearson correlation coefficients. Hierarchical clustering was carried out on the log transformed normalized data using the MeV software package (version 4.9.0).