Statistical analysis
death
REGRESSION
Based on the results obtained from the ITACa study, we assumed a prevalence of the haplotype to be validated (homozygosity in Patient characteristics were summarized using the median and range for the contin-uous variables and frequencies and percentages for the categorical variables. PFS was de-fined as the time between the date of diagnosis and that of progression or death; OS was defined as the time between the date of diagnosis and death; ORR was defined as the per-centage of patients achieving a complete (CR) or partial response (PR).The Kaplan–Meier method was used to estimate the time-to-event curves and the log-rank test was applied for their comparison. HRs for each polymorphism and haplo-types and relative 95% CI were calculated using the Cox proportional hazards model. The association between polymorphisms or haplotypes and ORR was analyzed by a logistic regression model and the effect of polymorphisms on ORR was estimated by odds ratio (OR) and 95% CI.Multivariate analyses were performed after univariate analyses revealed a significant effect of the polymorphism/haplotype. Models were adjusted for chemotherapy regimen (FOLFOX/CAPOX vs FOLFIRI/CAPIRI vs other), gender, age, All 