Figure 5.

Disease diagnosis and the presence of certain mutations predict clinical outcomes. (A) The graph depicts 95% confidence interval and Hodges-Lehmann median differences of odds ratios of different clinical parameters for indicated clinic outcomes. (B) The graph depict the Kaplan-Meier survival curve of patients with ≥4 mutations or patients with <4 mutations. Statistical significance of the Kaplan-Meier survival curve was analyzed by the log-rank test (C) Graphs depict the mean ± SEM of indicated clinic parameters in different disease subgroups. Statistical significance was assessed using 1-way ANOVA and Kruskal-Wallis tests. (D) Graphs depict the comparison of frequencies of indicated clinic outcomes in different disease groups. Statistical significance was analyzed using contingency table χ² tests. (E) The graph depicts 95% confidence interval and Hodges-Lehmann median differences for different clinical parameters in the presence or absence of mutations in a given gene. Statistical significance of continual variables was calculated using Mann-Whitney U tests, whereas for bilinear variables, significance was calculated by Fisher's exact test, and the log10-transformed odds ratios are shown. (F) Graphs depict Kaplan-Meier survival curves of patients in the presence or absence of given gene mutations. Statistical significance of the Kaplan-Meier survival curve was analyzed by the log-rank test. WT, wild-type.