Abstract
Prostate cancer (PCa) is the second most common cancer among men worldwide. Its etiology remains largely unknown compared to other common cancers. We have developed a risk stratification model combining environmental factors with family history and genetic susceptibility. 818 PCa cases and 1,006 healthy controls were compared. Subjects were interviewed on major lifestyle factors and family history. Fifty-six PCa susceptibility SNPs were genotyped. Risk models based on logistic regression were developed to combine environmental factors, family history and a genetic risk score. In the whole model, compared with subjects with low risk (reference category, decile 1), those carrying an intermediate risk (decile 5) had a 265% increase in PCa risk (OR = 3.65, 95% CI 2.26 to 5.91). The genetic risk score had an area under the ROC curve (AUROC) of 0.66 (95% CI 0.63 to 0.68). When adding the environmental score and family history to the genetic risk score, the AUROC increased by 0.05, reaching 0.71 (95% CI 0.69 to 0.74). Genetic susceptibility has a stronger risk value of the prediction that modifiable risk factors. While the added value of each SNP is small, the combination of 56 SNPs adds to the predictive ability of the risk model.
Highlights
Hereditary component accounts for up to 42% of the Prostate cancer (PCa) risk, including individual and combined effects of rare highly penetrant genes, common weak penetrant genes, and genes that act in concert with others[14,15,16]
Diabetes behaved as a protective factor against prostate cancer in those who were either untreated (OR = 0.41, 95% confidence intervals (CI) = 0.22 to 0.77), or in those whose treatment was with oral antidiabetic agents (OR = 0.69, 95% CI = 0.52 to 0.92)
We have evaluated the potential usefulness of a model for predicting risk of PCa, which combines modifiable risk factors with family history of PCa and genetic risk score based on the susceptibility of 56 SNPs
Summary
Hereditary component accounts for up to 42% of the PCa risk, including individual and combined effects of rare highly penetrant genes, common weak penetrant genes, and genes that act in concert with others[14,15,16]. Studies of genome-wide association (GWAS) are being designed with increasing statistical power in order to identify genetic variants associated with complex human diseases[17]. Each separate allele confers a small individual risk (odds ratios [OR] between 1.06 to 1.79 per allele)[18,19,20]. The detection of these risk alleles in an individual, together with the value of prostate specific antigen (PSA), family history and environmental factors, could increase the specificity and sensitivity of PCa diagnostic tests. We have developed a risk stratification model that combines environmental factors with family history and genetic susceptibility. We evaluated the relative contribution of these factors and the utility of the model for risk stratification and public health intervention
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