Lung Cancer Risk Prediction Using Common SNPs Located in GWAS-Identified Susceptibility Regions.

ABSTRACT:

Introduction

Genome-wide association studies (GWAS) have consistently identified specific lung cancer susceptibility regions. We evaluated the lung cancer-predictive performance of single-nucleotide polymorphisms (SNPs) in these regions.

Methods

Lung cancer cases (N = 778) and controls (N = 1166) were genotyped for 77 SNPs located in GWAS-identified lung cancer susceptibility regions. Variable selection and model development used stepwise logistic regression and decision-tree analyses. In a subset nested in the Pittsburgh Lung Screening Study, change in area under the receiver operator characteristic curve and net reclassification improvement were used to compare predictions made by risk factor models with and without genetic variables.

Results

Variable selection and

SUBMITTER: Weissfeld JL 

PROVIDER: S-EPMC4636453 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature