biostudies-literatureKarunamuni RACancer Research UKNIBIB NIH HHSMedical Research CouncilNational Institute for Health Research (NIHR)NCI NIH HHS532-541https://www.ebi.ac.uk/biostudies/studies/S-EPMC8157993biostudies-literatureUnknown24(2)<h4>Background</h4>Polygenic hazard scores (PHS) can identify individuals with increased risk of prostate cancer. We estimated the benefit of additional SNPs on performance of a previously validated PHS (PHS46).<h4>Materials and method</h4>180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the toProstate cancer and prostatic diseasesAdditional SNPs improve risk stratification of a polygenic hazard score for prostate cancer.PMC8157993NIHR2024111916915064NIHR201620G05009662443229019K08 EB02650329017UG1 CA189974MR/M012190/1U01 CA182883U10 CA037429Gamulin MBerndt SITeixeira MRRosenstein BSLophatananon AHuynh-Le MPGrindedal EMKoutros SUKGPCS collaboratorsNordestgaard BGAndreassen OAPashayan NLane ANeal DEWiklund FWolk AKote-Jarai ZMacInnis RJEeles RAIngles SAKarunamuni RATurner ELDonovan JLClaessens FZheng WRazack AStanford JLNielsen SFMucci LABrenner HNeuhausen SLAPCB BioResource (Australian Prostate Cancer BioResource)Martin RMRoobol MJTravis RCMills IGSeibert TMUsmani NCussenot OTangen CMKibel ASSorensen KDVega AFan CCPark JYNewcomb LFWest CMLProfile Study Steering CommitteeMuir KHaiman CAJohn EMWalsh EISchleutker JTownsend PALogothetis CJKogevinas MGago-Dominguez MGronberg HAlbanes DIMPACT Study Steering Committee and CollaboratorsBatra JMaier CDale AMHamilton RJPenney KLKaneva RCanary PASS InvestigatorsThompson WHamdy FCPRACTICAL ConsortiumCybulski CfalseAdditional SNPs improve risk stratification of a polygenic hazard score for prostate cancer.<h4>Background</h4>Polygenic hazard scores (PHS) can identify individuals with increased risk of prostate cancer. We estimated the benefit of additional SNPs on performance of a previously validated PHS (PHS46).<h4>Materials and method</h4>180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the to2021-01-01T00:00:00Z2021 Jun2026-05-09T04:14:57.06Z2025-04-05T00:23:41.734ZS-EPMC81579933342041610.1038/s41391-020-00311-2