Please use this identifier to cite or link to this item:
Title: Risk Model for Prostate Cancer Using Environmental and Genetic Factors in the Spanish Multi-Case-Control (MCC) Study.
Authors: Gómez-Acebo, Inés
Dierssen-Sotos, Trinidad
Fernandez-Navarro, Pablo
Palazuelos, Camilo
Moreno, Víctor
Aragonés, Nuria
Castaño-Vinyals, Gemma
Jiménez-Monleón, Jose J
Ruiz-Cerdá, Jose Luis
Pérez-Gómez, Beatriz
Ruiz-Dominguez, José Manuel
Molero, Jessica Alonso
Pollán, Marina
Kogevinas, Manolis
Llorca, Javier
metadata.dc.subject.mesh: Adult
Aged, 80 and over
Environmental Exposure
Genetic Predisposition to Disease
Middle Aged
Models, Statistical
Polymorphism, Single Nucleotide
Prostatic Neoplasms
ROC Curve
Risk Factors
Young Adult
Issue Date: 21-Aug-2017
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.
metadata.dc.identifier.doi: 10.1038/s41598-017-09386-9
Appears in Collections:Producción 2020

Files in This Item:
File SizeFormat 
PMC5566549.pdf1,43 MBAdobe PDFView/Open

This item is protected by original copyright

This item is licensed under a Creative Commons License Creative Commons