Background: Clinical variables-age, family history, genetics-are used for prostate cancer risk stratification. Recently, polygenic hazard scores (PHS46, PHS166) were validated as associated with age at prostate cancer diagnosis. While polygenic scores are associated with all prostate cancer (not specific for fatal cancers), PHS46 was also associated with age at prostate cancer death. We evaluated if adding PHS to clinical variables improves associations with prostate cancer death.
Methods: Genotype/phenotype data were obtained from a nested case-control Cohort of Swedish Men (n = 3279; 2163 with prostate cancer, 278 prostate cancer deaths). PHS and clinical variables (family history, alcohol intake, smoking, heart disease, hypertension, diabetes, body mass index) were tested via univariable Cox proportional hazards models for association with age at prostate cancer death. Multivariable Cox models with/without PHS were compared with log-likelihood tests.
Results: Median age at last follow-up/prostate cancer death was 78.0 (IQR: 72.3-84.1) and 81.4 (75.4-86.3) years, respectively. On univariable analysis, PHS46 (HR 3.41 [95% CI 2.78-4.17]), family history (HR 1.72 [1.46-2.03]), alcohol (HR 1.74 [1.40-2.15]), diabetes (HR 0.53 [0.37-0.75]) were each associated with prostate cancer death. On multivariable analysis, PHS46 (HR 2.45 [1.99-2.97]), family history (HR 1.73 [1.48-2.03]), alcohol (HR 1.45 [1.19-1.76]), diabetes (HR 0.62 [0.42-0.90]) all remained associated with fatal disease. Including PHS46 or PHS166 improved multivariable models for fatal prostate cancer (p < 10-15).
Conclusions: PHS had the most robust association with fatal prostate cancer in a multivariable model with common risk factors, including family history. Adding PHS to clinical variables may improve prostate cancer risk stratification strategies.
© 2021. The Author(s), under exclusive licence to Springer Nature Limited.