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=3,279; 2,163 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 were 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. Impact: Adding PHS to clinical variables may improve prostate cancer risk stratification strategies.

中文翻译：

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常见的遗传和临床危险因素：与瑞典男性队列中的致命性前列腺癌相关

背景：临床变量-年龄，家族史，遗传学-用于前列腺癌风险分层。最近，在前列腺癌诊断中，多基因危险评分（PHS46，PHS166）被证实与年龄有关。虽然多基因评分与所有前列腺癌相关（并非致命癌症特异性），但PHS46仍与前列腺癌死亡时的年龄有关。我们评估了在临床变量中添加PHS是否能改善与前列腺癌死亡的关联。方法：基因型/表型数据来自瑞典男性的病例对照队列（n = 3,279； 2,163例前列腺癌，278例前列腺癌死亡）。PHS和临床变量（家族史，饮酒，吸烟，心脏病，高血压，糖尿病，体重指数）通过单变量Cox比例风险模型进行测试，以与前列腺癌死亡时的年龄相关联。将具有/不具有PHS的多变量Cox模型与对数似然测试进行比较。结果：最后一次随访/前列腺癌死亡的中位年龄分别为78.0（IQR：72.3-84.1）和81.4（75.4-86.3）岁。单变量分析显示，PHS46（HR 3.41 [95％CI 2.78-4.17]），家族史（HR 1.72 [1.46-2.03]），酒精（HR 1.74 [1.40-2.15]），糖尿病（HR 0.53 [0.37-0.75] ）均与前列腺癌死亡相关。在多变量分析中，均保留了PHS46（HR 2.45 [1.99-2.97]），家族史（HR 1.73 [1.48-2.03]），酒精（HR 1.45 [1.19-1.76]），糖尿病（HR 0.62 [0.42-0.90]）与致命疾病有关。包括PHS46或PHS166在内的改进的致命前列腺癌多变量模型（p <10-15）。结论：在具有常见风险因素（包括家族史）的多变量模型中，PHS与致命性前列腺癌的关联最密切。影响：在临床变量中添加PHS可能会改善前列腺癌的风险分层策略。