TY  - JOUR
AU  - Karunamuni, Roshan A
AU  - Huynh-Le, Minh-Phuong
AU  - Fan, Chun C
AU  - Thompson, Wesley
AU  - Eeles, Rosalind A
AU  - Kote-Jarai, Zsofia
AU  - Muir, Kenneth
AU  - Lophatananon, Artitaya
AU  - Schleutker, Johanna
AU  - Pashayan, Nora
AU  - Batra, Jyotsna
AU  - Grönberg, Henrik
AU  - Walsh, Eleanor I
AU  - Turner, Emma L
AU  - Lane, Athene
AU  - Martin, Richard M
AU  - Neal, David E
AU  - Donovan, Jenny L
AU  - Hamdy, Freddie C
AU  - Nordestgaard, Børge G
AU  - Tangen, Catherine M
AU  - MacInnis, Robert J
AU  - Wolk, Alicja
AU  - Albanes, Demetrius
AU  - Haiman, Christopher A
AU  - Travis, Ruth C
AU  - Stanford, Janet L
AU  - Mucci, Lorelei A
AU  - West, Catharine M L
AU  - Nielsen, Sune F
AU  - Kibel, Adam S
AU  - Wiklund, Fredrik
AU  - Cussenot, Olivier
AU  - Berndt, Sonja I
AU  - Koutros, Stella
AU  - Sørensen, Karina Dalsgaard
AU  - Cybulski, Cezary
AU  - Grindedal, Eli Marie
AU  - Park, Jong Y
AU  - Ingles, Sue A
AU  - Maier, Christiane
AU  - Hamilton, Robert J
AU  - Rosenstein, Barry S
AU  - Vega, Ana
AU  - Committee, IMPACT Study Steering
AU  - Kogevinas, Manolis
AU  - Penney, Kathryn L
AU  - Teixeira, Manuel R
AU  - Brenner, Hermann
AU  - John, Esther M
AU  - Kaneva, Radka
AU  - Logothetis, Christopher J
AU  - Neuhausen, Susan L
AU  - Razack, Azad
AU  - Newcomb, Lisa F
AU  - Gamulin, Marija
AU  - Usmani, Nawaid
AU  - Claessens, Frank
AU  - Gago-Dominguez, Manuela
AU  - Townsend, Paul A
AU  - Roobol, Monique J
AU  - Zheng, Wei
AU  - Mills, Ian G
AU  - Andreassen, Ole A
AU  - Dale, Anders M
AU  - Seibert, Tyler M
TI  - Additional SNPs improve risk stratification of a polygenic hazard score for prostate cancer.
JO  - Prostate cancer and prostatic diseases
VL  - 24
IS  - 2
SN  - 1476-5608
CY  - Basingstoke
PB  - Stockton Press
M1  - DKFZ-2021-01162
SP  - 532 - 541
PY  - 2021
AB  - 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).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 top 5
LB  - PUB:(DE-HGF)16
C6  - pmid:33420416
DO  - DOI:10.1038/s41391-020-00311-2
UR  - https://inrepo02.dkfz.de/record/168960
ER  -