مشخصات پژوهش

صفحه نخست /Predicting the Survival Time ...
عنوان
Predicting the Survival Time for Bladder Cancer Using an Addi-tive Hazards Model in Microarray Data
نوع پژوهش مقاله چاپ شده
کلیدواژه‌ها
Survival analysis, Microarray data, Additive hazards model, Variable selection, Bladder cancer
چکیده
Background: One substantial part of microarray studies is to predict patients’ survival based on their gene expression profile. Variable selection techniques are powerful tools to handle high dimensionality in analysis of microarray data. However, these techniques have not been investigated in competing risks setting. This study aimed to investigate the performance of four sparse variable selection methods in estimating the survival time. Methods: The data included 1381 gene expression measurements and clinical infor mation from 301 patients with bladder cancer operated in the years 1987 to 2000 in hospitals in Denmark, Sweden, Spain, France, and England. Four methods of the least absolute shrinkage and selection operator, smoothly clipped absolute deviation, the smooth inte-gration of counting and absolute deviation and elastic net were utilized for simultaneous variable selection and estim a-tion under an additive hazards model. The criteria of area under ROC curve, Brier score and c -index were used to compare the methods. Results: The median follow-up time for all patients was 47 months. The elastic net approach was indicated to outper-form other methods. The elastic net had the lowest integrated Brier score (0.137±0.07) and the greatest median of the over-time AUC and C-index (0.803±0.06 and 0.779±0.13, respectively). Five out of 19 selected genes by the elastic net were significant (P<0.05) under an additive hazards model. It was indicated that the expression of RTN4, SON, IGF1R and CDC20 decrease the survival time, while the expression of SMARCAD1 increase it. Conclusion: The elastic net had higher capability than the other methods fo r the prediction of survival time in pa-tients with bladder cancer in the presence of competing risks base on additive hazards model.
پژوهشگران لیلی تاپاک (نفر اول)، حسین محجوب (نفر دوم)، مسعود سعیدی جم (نفر چهارم)، جلال پورالعجل (نفر پنجم)