Predicting the Survival Time for Bladder Cancer Using an Additive Hazards Model in Microarray Data.
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 information 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 integration of counting and absolute deviation and elastic net were utilized for simultaneous variable selection and estimation 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 outperform 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.


CONCLUSIONS
The elastic net had higher capability than the other methods for the prediction of survival time in patients with bladder cancer in the presence of competing risks base on additive hazards model.
Dept. of Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
Leili
L
Tapak
Research Center for Health Sciences and Dept. of Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
Hossein
H
Mahjub
Dept. of Statistics, Faculty of Science, Bu-Ali Sina University, Hamadan, Iran.
Majid
M
Sadeghifar
Research Center for Molecular Medicine, Dept. of Molecular Medicine and Genetics, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran.
Massoud
M
Saidijam
Modeling of Noncommunicable Diseases Research Center, Dept. of Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
Jalal
J
Poorolajal
Additive hazards model; Bladder cancer; Microarray data; Survival analysis; Variable selection