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صفحه اصلی
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اولین کنگره بین المللی رویکردهای نوین سبک زندگی، پیشگیری و درمان سرطان
Application of Censored Quantile Regression to Investigation of prognostic factors of survival in breast cancer: A multi-center study
نویسندگان :
Akram Yazdani (دانشگاه علوم پزشکی کاشان)
کلمات کلیدی :
breast cancer،frailty model،quantile regression،survival time
چکیده :
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. 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. Age at diagnosis (years), tumor size (cm), Involvement of lymph nodes, tumor grade, type of surgery, auxiliary treatment with chemotherapy, radiotherapy, recurrence, and metastasis were the prognostic factors considered in this study. 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 10th and 50th 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 10th and 50th percentiles of survival time were 20.67 and 69.73 months, respectively (all P-value<0.05). An increase in the number of involved lymph nodes decreased the quantiles of survival time. The frailty variance was significant, which confirmed that, there was significant variability between the centers. Conclusions: This study confirmed the usefulness of a censored quantile regression model for cluster data in studying the impact of prognostic factors on survival.
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