Application of Frailty Quantile Regression Model to Investigate of Factors Survival Time in Breast Cancer: A Multi-Center Study

Background The prognostic factors of survival can be accurately identified using data from different health centers, but the structure of multi-center data is heterogeneous due to the treatment of patients in different centers or similar reasons. In survival analysis, the shared frailty model is a common way to analyze multi-center data that assumes all covariates have homogenous effects. We used a censored quantile regression model for clustered survival data to study the impact of prognostic factors on survival time. Methods This multi-center historical cohort study included 1785 participants with breast cancer from four different medical centers. A censored quantile regression model with a gamma distribution for the frailty term was used, and p -value less than 0.05 considered significant. Results The 10 th and 50 th percentiles (95% confidence interval) of survival time were 26.22 (23–28.77) and 235.07 (130–236.55) months, respectively. The effect of metastasis on the 10 th and 50 th percentiles of survival time was 20.67 and 69.73 months, respectively (all p -value