Common genetic and clinical risk factors: association with fatal prostate cancer in the Cohort of Swedish Men.
Common genetic and clinical risk factors: association with fatal prostate cancer in the Cohort of Swedish Men.
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常见的遗传和临床风险因素：与瑞典男性队列中致命性前列腺癌的相关性。
DOI：
10.1038/s41391-021-00341-4
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发表时间：
2021-09
影响因子：
4.8
通讯作者：
PRACTICAL Consortium
中科院分区：
文献类型：
--
作者：
Huynh-Le MP;Karunamuni R;Fan CC;Thompson WK;Muir K;Lophatananon A;Tye K;Wolk A;Håkansson N;Mills IG;Andreassen OA;Dale AM;Seibert TM;PRACTICAL Consortium
临床变量年龄、家族史、遗传学用于前列腺癌风险分层。最近，多基因危险评分（PHS 46，PHS 166）被证实与前列腺癌诊断时的年龄相关。虽然多基因评分与所有前列腺癌相关（不特异于致命性癌症），但PHS 46也与前列腺癌死亡时的年龄相关。我们评估了将PHS加入临床变量是否改善了与前列腺癌死亡的相关性。基因型/表型数据来自瑞典男性嵌套病例对照队列（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）通过单变量考克斯比例风险模型与前列腺癌死亡年龄的相关性进行了检验。多变量考克斯模型与/无PHS进行了比较，对数似然检验。末次随访/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。在单变量分析中，PHS 46（HR 3.41 [95%CI 2.78-4.17]）、家族史（HR 1.72 [1.46-2.03]）、饮酒（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，PHS 46（HR 2.45 [1.99-2.97]）、家族史（HR 1.73 [1.48-2.03]）、饮酒（HR 1.45 [1.19-1.76]）、糖尿病（HR 0.62 [0.42-0.90]）均与致死性疾病相关。包括PHS 46或PHS 166改善了致死性前列腺癌的多变量模型（p<10−15）。在一个包含常见危险因素（包括家族史）的多变量模型中，PHS与致命性前列腺癌的相关性最强。将PHS加入临床变量可能会改善前列腺癌风险分层策略。
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. 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. 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). 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.
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影响因子：
4.8
作者：
Karunamuni RA;Huynh-Le MP;Fan CC;Thompson W;Eeles RA;Kote-Jarai Z;Muir K;Lophatananon A;UKGPCS collaborators;Schleutker J;Pashayan N;Batra J;APCB BioResource (Australian Prostate Cancer BioResource);Grönberg H;Walsh EI;Turner EL;Lane A;Martin RM;Neal DE;Donovan JL;Hamdy FC;Nordestgaard BG;Tangen CM;MacInnis RJ;Wolk A;Albanes D;Haiman CA;Travis RC;Stanford JL;Mucci LA;West CML;Nielsen SF;Kibel AS;Wiklund F;Cussenot O;Berndt SI;Koutros S;Sørensen KD;Cybulski C;Grindedal EM;Park JY;Ingles SA;Maier C;Hamilton RJ;Rosenstein BS;Vega A;IMPACT Study Steering Committee and Collaborators;Kogevinas M;Penney KL;Teixeira MR;Brenner H;John EM;Kaneva R;Logothetis CJ;Neuhausen SL;Razack A;Newcomb LF;Canary PASS Investigators;Gamulin M;Usmani N;Claessens F;Gago-Dominguez M;Townsend PA;Roobol MJ;Zheng W;Profile Study Steering Committee;Mills IG;Andreassen OA;Dale AM;Seibert TM;PRACTICAL Consortium
通讯作者：
PRACTICAL Consortium
DOI：
10.1038/s41431-020-0664-2
发表时间：
2020-10
期刊：
European journal of human genetics : EJHG
影响因子：
--
作者：
Karunamuni RA;Huynh-Le MP;Fan CC;Eeles RA;Easton DF;Kote-Jarai Z;Amin Al Olama A;Benlloch Garcia S;Muir K;Gronberg H;Wiklund F;Aly M;Schleutker J;Sipeky C;Tammela TLJ;Nordestgaard BG;Key TJ;Travis RC;Neal DE;Donovan JL;Hamdy FC;Pharoah P;Pashayan N;Khaw KT;Thibodeau SN;McDonnell SK;Schaid DJ;Maier C;Vogel W;Luedeke M;Herkommer K;Kibel AS;Cybulski C;Wokolorczyk D;Kluzniak W;Cannon-Albright L;Brenner H;Schöttker B;Holleczek B;Park JY;Sellers TA;Lin HY;Slavov C;Kaneva R;Mitev V;Batra J;Clements JA;Spurdle A;Australian Prostate Cancer BioResource (APCB);Teixeira MR;Paulo P;Maia S;Pandha H;Michael A;Mills IG;Andreassen OA;Dale AM;Seibert TM;PRACTICAL Consortium
通讯作者：
PRACTICAL Consortium
影响因子：
50.5
作者：
Discacciati, A.;Orsini, N.;Wolk, A.
通讯作者：
Wolk, A.
影响因子：
2.8
作者：
Albright, Frederick;Stephenson, Robert A.;Agarwal, Neeraj;Teerlink, Craig C.;Lowrance, William T.;Farnham, James M.;Albright, Lisa A. Cannon
通讯作者：
Albright, Lisa A. Cannon
影响因子：
254.7
作者：
Parkin, DM;Bray, F;Pisani, P
通讯作者：
Pisani, P