ArticleGenetic epidemiology2011
A risk prediction algorithm based on family history and common genetic variants: application to prostate cancer with potential clinical impact.
Article in Genetic epidemiology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 2 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
50 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Germline mutations in prostate cancer: a systematic review of the evidence for personalized medicine.Prostate cancer and prostatic diseases · 2023Pooled it
- Multigene panels in prostate cancer risk assessment: a systematic review.Genetics in medicine : official journal of the American College of Medical Genetics · 2016Pooled it
- CanRisk-Prostate: A Comprehensive, Externally Validated Risk Model for the Prediction of Future Prostate Cancer.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2023Article
- Bayesian linear mixed model with multiple random effects for family-based genetic studies.Frontiers in genetics · 2023Article
- Prediction of future risk of any and higher-grade prostate cancer based on the PLCO and SELECT trials.BMC urology · 2022Article
- Genetic predisposition to prostate cancer: an update.Familial cancer · 2022Review
- Novel strategy for disease risk prediction incorporating predicted gene expression and DNA methylation data: a multi-phased study of prostate cancer.Cancer communications (London, England) · 2021Article
- Review
- Single nucleotide polymorphisms (SNPs) in prostate cancer: its implications in diagnostics and therapeutics.American journal of translational research · 2021Review
- Hereditary Predisposition to Prostate Cancer: From Genetics to Clinical Implications.International journal of molecular sciences · 2020Review
- Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.American journal of human genetics · 2019Article
- Post-GWAS in prostate cancer: from genetic association to biological contribution.Nature reviews. Cancer · 2019Review
- Prostate Cancer Germline Variations and Implications for Screening and Treatment.Cold Spring Harbor perspectives in medicine · 2018Review
- A Review of Prostate Cancer Genome-Wide Association Studies (GWAS).Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2018Review
- Predicting the risk for colorectal cancer with personal characteristics and fecal immunochemical test.Medicine · 2018Observational
- Men with a susceptibility to prostate cancer and the role of genetic based screening.Translational andrology and urology · 2018Review
- Article
- Improving Disease Prediction by Incorporating Family Disease History in Risk Prediction Models with Large-Scale Genetic Data.Genetics · 2017Article
- Prediction of Breast and Prostate Cancer Risks in Male BRCA1 and BRCA2 Mutation Carriers Using Polygenic Risk Scores.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2017Article
- Using information of relatives in genomic prediction to apply effective stratified medicine.Scientific reports · 2017Article
Corrections and comments
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Authors and funding
24 authors.
Funding
Abstract
Genome wide association studies have identified several single nucleotide polymorphisms (SNPs) that are independently associated with small increments in risk of prostate cancer, opening up the possibility for using such variants in risk prediction. Using segregation analysis of population-based samples of 4,390 families of prostate cancer patients from the UK and Australia, and assuming all familial aggregation has genetic causes, we previously found that the best model for the genetic susceptibility to prostate cancer was a mixed model of inheritance that included both a recessive major gene component and a polygenic component (P) that represents the effect of a large number of genetic variants each of small effect, where . Based on published studies of 26 SNPs that are currently known to be associated with prostate cancer, we have extended our model to incorporate these SNPs by decomposing the polygenic component into two parts: a polygenic component due to the known susceptibility SNPs, , and the residual polygenic component due to the postulated but as yet unknown genetic variants, . The resulting algorithm can be used for predicting the probability of developing prostate cancer in the future based on both SNP profiles and explicit family history information. This approach can be applied to other diseases for which population-based family data and established risk variants exist.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.