title: High-dimensional additive hazards regression for oral squamous cell carcinoma using microarray data: a comparative study.
abstract: Microarray technology results in high-dimensional and low-sample size data sets. Therefore, fitting sparse models is substantial because only a small number of influential genes can reliably be identified. A number of variable selection approaches have been proposed for high-dimensional time-to-event data based on Cox proportional hazards where censoring is present. The present study applied three sparse variable selection techniques of Lasso, smoothly clipped absolute deviation and the smooth integration of counting, and absolute deviation for gene expression survival time data using the additive risk model which is adopted when the absolute effects of multiple predictors on the hazard function are of interest. The performances of used techniques were evaluated by time dependent ROC curve and bootstrap .632+ prediction error curves. The selected genes by all methods were highly significant (P < 0.001). The Lasso showed maximum median of area under ROC curve over time (0.95) and smoothly clipped absolute deviation showed the lowest prediction error (0.105). It was observed that the selected genes by all methods improved the prediction of purely clinical model indicating the valuable information containing in the microarray features. So it was concluded that used approaches can satisfactorily predict survival based on selected gene expression measurements.
authors: Department of Science, Hamadan University of Technology, Hamedan 65155, Iran.
authors: Omid
authors: O
authors: Hamidi
authors: Department of Biostatistics and Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan 6517838695, Iran.
authors: Lily
authors: L
authors: Tapak
authors: Department of Epidemiology & Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
authors: Aarefeh
authors: A
authors: Jafarzadeh Kohneloo
authors: Department of Statistics, Faculty of Science, Bu-Ali Sina University, Hamadan 6517838695, Iran.
authors: Majid
authors: M
authors: Sadeghifar
mesh_terms: D002294:Carcinoma, Squamous Cell / Q000235:genetics*; D052138:Genes, Neoplasm; D006801:Humans; D008954:Models, Biological; D009062:Mouth Neoplasms / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis; D016016:Proportional Hazards Models; D012372:ROC Curve; D016019:Survival Analysis