Spss statistics 23.0 package

Patients were grouped according to the localization of their primary tumor and type/site of bone metastases. The Kolmogorov-Smirnov test was used to decipher the normality of data distribution. Categorical and ordinal parameters consisting of basic patient information, primary tumor localization and bone‐specific metastatic pattern were statistically analyzed by χ2 test or Fisher’s exact test. Risk assumptions were presented as odds ratio (OR) and respective 95% confidence intervals (CI). Kaplan–Meier plots were used to estimate survival curves and the log-rank test was applied to compare discrepancies between the groups. Median follow-up time was estimated using the reverse-censored Kaplan-Meier method with the R package prodlim. The independent prognostic value of the clinicopathological variables was examined with a multivariate Cox proportional hazard regression model. p values are always presented as two-sided and were considered statistically significant when below 0.05. Metric data is always shown as median or mean and corresponding range or, in case of OS, as median and corresponding 95% CI. All statistical analyses were performed using R version 3.6.3 (R Foundation for Statistical Computing, Vienna, Austria) and SPSS Statistics 23.0 package (SPSS Inc., Chicago, IL, United States).

Categorical data was compared by performing Fishers’ exact or chi-square tests. Statistical differences between two groups were tested by Mann-Whitney U test. The significance of potential correlations of continuous parameters was investigated by using Pearson correlation. Overall survival (OS) was defined as time between initial MPM diagnosis and date of death or last follow-up. OS was estimated by the Kaplan-Meier method and a log rank test was used to calculate survival differences between two groups. A multivariate cox regression model was used to calculate hazard ratios and 95% confidence intervals for factors independently influencing OS. To investigate the accuracy of C4d as a predictor for survival and to distinguish between MPM and non-malignant pleural disease, Receiver Operating Characteristics (ROC) curve analysis was used. For each cut-off point, the Youden’s Index was calculated (sensitivity + specificity). All results were considered statistically significant when p < 0.05 two-sided. Analyses were performed using the SPSS Statistics 23.0 package (SPSS Inc., Chicago, IL, USA) and GraphPad Prism 5.0.