2.3. Statistical Analysis

Categorical variables were analyzed by Pearson’s chi-square test or Fisher’s exact test. Continuous variables were analyzed with the Mann-Whitney test. Variables with a p value < 0.2 in comparison analysis between two antifungal treatment groups of fluconazole and echinocandins were included in a multiple logistic regression analysis to calculate a propensity score [11], which was used for propensity score matching to control for baseline variables. Covariates in calculating the propensity score included underlying comorbidities (cardiac disease, neurologic disease, malignancy, and renal disease), clinical conditions (mechanical ventilation, renal replacement therapy, and presence of septic shock), and source of candidemia due to central venous catheterization. Patients in the fluconazole treatment group were matched at a ratio of 1:1 with those in the echinocandin treatment group by individual propensity scores. In the matched cohort, the Kaplan–Meier survival analysis was performed to assess relationship between antifungal treatment groups and 60-day mortality. A multivariable logistic regression analysis using variables with a p value < 0.2 from comparison analysis and antifungal treatment was conducted to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for 60-day mortality. A p value < 0.05 was considered to be statistically significant. SPSS version 23.0 for Windows (SPSS Inc., Chicago, IL, USA) was employed for statistical analyses.