Cargando…

Risk Model for Prostate Cancer Using Environmental and Genetic Factors in the Spanish Multi-Case-Control (MCC) Study

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 hea...

Descripción completa

Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5566549/
https://www.ncbi.nlm.nih.gov/pubmed/28827750
http://dx.doi.org/10.1038/s41598-017-09386-9
_version_ 1783258568877670400
author 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
author_facet 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
author_sort Gómez-Acebo, Inés
collection PubMed
description 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.
format Online
Article
Text
id pubmed-5566549
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-55665492017-08-23 Risk Model for Prostate Cancer Using Environmental and Genetic Factors in the Spanish Multi-Case-Control (MCC) Study 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 Sci Rep Article 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. Nature Publishing Group UK 2017-08-21 /pmc/articles/PMC5566549/ /pubmed/28827750 http://dx.doi.org/10.1038/s41598-017-09386-9 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
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
Risk Model for Prostate Cancer Using Environmental and Genetic Factors in the Spanish Multi-Case-Control (MCC) Study
title Risk Model for Prostate Cancer Using Environmental and Genetic Factors in the Spanish Multi-Case-Control (MCC) Study
title_full Risk Model for Prostate Cancer Using Environmental and Genetic Factors in the Spanish Multi-Case-Control (MCC) Study
title_fullStr Risk Model for Prostate Cancer Using Environmental and Genetic Factors in the Spanish Multi-Case-Control (MCC) Study
title_full_unstemmed Risk Model for Prostate Cancer Using Environmental and Genetic Factors in the Spanish Multi-Case-Control (MCC) Study
title_short Risk Model for Prostate Cancer Using Environmental and Genetic Factors in the Spanish Multi-Case-Control (MCC) Study
title_sort risk model for prostate cancer using environmental and genetic factors in the spanish multi-case-control (mcc) study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5566549/
https://www.ncbi.nlm.nih.gov/pubmed/28827750
http://dx.doi.org/10.1038/s41598-017-09386-9
work_keys_str_mv AT gomezaceboines riskmodelforprostatecancerusingenvironmentalandgeneticfactorsinthespanishmulticasecontrolmccstudy
AT dierssensotostrinidad riskmodelforprostatecancerusingenvironmentalandgeneticfactorsinthespanishmulticasecontrolmccstudy
AT fernandeznavarropablo riskmodelforprostatecancerusingenvironmentalandgeneticfactorsinthespanishmulticasecontrolmccstudy
AT palazueloscamilo riskmodelforprostatecancerusingenvironmentalandgeneticfactorsinthespanishmulticasecontrolmccstudy
AT morenovictor riskmodelforprostatecancerusingenvironmentalandgeneticfactorsinthespanishmulticasecontrolmccstudy
AT aragonesnuria riskmodelforprostatecancerusingenvironmentalandgeneticfactorsinthespanishmulticasecontrolmccstudy
AT castanovinyalsgemma riskmodelforprostatecancerusingenvironmentalandgeneticfactorsinthespanishmulticasecontrolmccstudy
AT jimenezmonleonjosej riskmodelforprostatecancerusingenvironmentalandgeneticfactorsinthespanishmulticasecontrolmccstudy
AT ruizcerdajoseluis riskmodelforprostatecancerusingenvironmentalandgeneticfactorsinthespanishmulticasecontrolmccstudy
AT perezgomezbeatriz riskmodelforprostatecancerusingenvironmentalandgeneticfactorsinthespanishmulticasecontrolmccstudy
AT ruizdominguezjosemanuel riskmodelforprostatecancerusingenvironmentalandgeneticfactorsinthespanishmulticasecontrolmccstudy
AT molerojessicaalonso riskmodelforprostatecancerusingenvironmentalandgeneticfactorsinthespanishmulticasecontrolmccstudy
AT pollanmarina riskmodelforprostatecancerusingenvironmentalandgeneticfactorsinthespanishmulticasecontrolmccstudy
AT kogevinasmanolis riskmodelforprostatecancerusingenvironmentalandgeneticfactorsinthespanishmulticasecontrolmccstudy
AT llorcajavier riskmodelforprostatecancerusingenvironmentalandgeneticfactorsinthespanishmulticasecontrolmccstudy