2.9 Statistical analysis
Categorical variables are reported as counts and percentages and
continuous variables as mean ±SD, or medians and interquartile ranges
(IQRs). Differences between percentages were assessed by chi-square or
Fisher exact tests. Student unpaired t -tests and analysis of
variance were used for normally distributed continuous variables.
Appropriate nonparametric tests (Mann-Whitney, Kruskal-Wallis and
Spearman rank correlation tests) were used for all other variables.
Data were analyzed for the assessment of treatment effect on biomarkers
performing a repeated measures MANOVA with one between subject factor
(treatment group) and one within-subject factor (time at two or three
levels). As covariates, we considered the possible random differences in
age and comorbidities between the groups.
After dividing the population into groups, the cumulative incidence was
estimated using a Kaplan–Meier product–limit estimator. Survival
curves were formally compared using the log-rank test. Cox proportional
hazards analysis was used to calculate the adjusted relative hazards of
outcome events by each clinical variable.
For multivariate models, model selection was performed using forward
stepwise regression on the basis of the Akaike information criterion.
Only p values <0.05 were considered statistically significant.
All tests were 2-tailed, and analyses were performed using computer
software packages (R version 2.15.2, R Development Core Team, Wien,
Austria).