• Statistical analysis

    Differences were assessed with t tests (for continuous variables) or chi-square tests (for cate-goric variables). An a level of 0.05 was used for determining statistical significance. When differences between groups reached statistical significance, the magnitude of the effects was determined by Cohen’s d, a commonly used measure for effect size26. A value of ± 0.5 was considered the medium effect size. Multiple linear regression was used to determine associations between measures of quality of life, cognitive function, treatment modalities, and demographic characteristics. Backward linear regression modeling was applied using a p value < 0.04 for entry and a p > 0.05 for removal of the selected variables.

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