Breast cancer risk prediction using a clinical risk model and polygenic risk score.
Breast cancer risk prediction using a clinical risk model and polygenic risk score.
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DOI：
10.1007/s10549-016-3953-2
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发表时间：
2016-10
影响因子：
3.8
通讯作者：
Ziv, Elad
中科院分区：
文献类型：
--
作者：
Shieh, Yiwey;Hu, Donglei;Ma, Lin;Huntsman, Scott;Gard, Charlotte C.;Leung, Jessica W. T.;Tice, Jeffrey A.;Vachon, Celine M.;Cummings, Steven R.;Kerlikowske, Karla;Ziv, Elad
乳腺癌风险评估可以为筛查和预防模式的使用提供信息。我们研究了乳腺癌监测联盟（BCSC）风险模型结合多基因风险评分（PRS）的性能，该评分由全基因组关联研究中鉴定的83个单核苷酸多态性组成。我们在一个筛选队列中对486例病例和495例匹配对照进行了巢式病例对照研究。使用贝叶斯方法计算PRS。使用条件Logistic回归检验了PRS和BCSC模型中变量对乳腺癌风险的贡献。使用受试者工作特征曲线下面积（AUROC）比较模型的判别准确性。PRS四分位数的增加与乳腺癌风险呈正相关，最高与最低四分位数乳腺癌的OR为2.54（95%CI 1.69-3.82）。在多变量模型中，PRS、家族史和乳腺密度仍然是强危险因素。PRS的AUROC为0.60（95% CI 0.57-0.64），亚洲特定PRS的AUROC为0.64（95% CI 0.53-0.74）。包括BCSC风险因素和PRS的组合模型比BCSC模型具有更好的区分度（AUROC 0.65 vs 0.62，p = 0.01）。BCSC-PRS模型将18%的病例归类为高风险（5年风险≥ 3%），而BCSC模型则为7%。减贫战略改进了对BCSC风险模式的区分，并将更多病例归类为高风险。值得进一步考虑减贫战略在筛查和预防战略决策中的作用。
Breast cancer risk assessment can inform the use of screening and prevention modalities. We investigated the performance of the Breast Cancer Surveillance Consortium (BCSC) risk model in combination with a polygenic risk score (PRS) comprised of 83 single nucleotide polymorphisms identified from genome wide association studies. We conducted a nested case-control study of 486 cases and 495 matched controls within a screening cohort. The PRS was calculated using a Bayesian approach. The contributions of the PRS and variables in the BCSC model to breast cancer risk were tested using conditional logistic regression. Discriminatory accuracy of the models was compared using the area under the receiver operating characteristic curve (AUROC). Increasing quartiles of the PRS were positively associated with breast cancer risk, with OR 2.54 (95% CI 1.69-3.82) for breast cancer in the highest versus lowest quartile. In a multivariable model, the PRS, family history, and breast density remained strong risk factors. The AUROC of the PRS was 0.60 (95% CI 0.57-0.64), and an Asian-specific PRS had AUROC 0.64 (95% CI 0.53-0.74). A combined model including the BCSC risk factors and PRS had better discrimination than the BCSC model (AUROC 0.65 versus 0.62, p = 0.01). The BCSC-PRS model classified 18% of cases as high-risk (5-year risk ≥ 3%), compared with 7% using the BCSC model. The PRS improved discrimination of the BCSC risk model and classified more cases as high-risk. Further consideration of the PRS's role in decision-making around screening and prevention strategies is merited.
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DOI：
10.1093/jnci/djq388
发表时间：
2010-11-03
期刊：
Journal of the National Cancer Institute
影响因子：
--
作者：
Mealiffe ME;Stokowski RP;Rhees BK;Prentice RL;Pettinger M;Hinds DA
通讯作者：
Hinds DA
影响因子：
14.9
作者：
Flicek P;Amode MR;Barrell D;Beal K;Billis K;Brent S;Carvalho-Silva D;Clapham P;Coates G;Fitzgerald S;Gil L;Girón CG;Gordon L;Hourlier T;Hunt S;Johnson N;Juettemann T;Kähäri AK;Keenan S;Kulesha E;Martin FJ;Maurel T;McLaren WM;Murphy DN;Nag R;Overduin B;Pignatelli M;Pritchard B;Pritchard E;Riat HS;Ruffier M;Sheppard D;Taylor K;Thormann A;Trevanion SJ;Vullo A;Wilder SP;Wilson M;Zadissa A;Aken BL;Birney E;Cunningham F;Harrow J;Herrero J;Hubbard TJ;Kinsella R;Muffato M;Parker A;Spudich G;Yates A;Zerbino DR;Searle SM
通讯作者：
Searle SM
东亚人的全基因组关联研究确定了乳腺癌的新易感位点
影响因子：
4.5
作者：
Long J;Cai Q;Sung H;Shi J;Zhang B;Choi JY;Wen W;Delahanty RJ;Lu W;Gao YT;Shen H;Park SK;Chen K;Shen CY;Ren Z;Haiman CA;Matsuo K;Kim MK;Khoo US;Iwasaki M;Zheng Y;Xiang YB;Gu K;Rothman N;Wang W;Hu Z;Liu Y;Yoo KY;Noh DY;Han BG;Lee MH;Zheng H;Zhang L;Wu PE;Shieh YL;Chan SY;Wang S;Xie X;Kim SW;Henderson BE;Le Marchand L;Ito H;Kasuga Y;Ahn SH;Kang HS;Chan KY;Iwata H;Tsugane S;Li C;Shu XO;Kang DH;Zheng W
通讯作者：
Zheng W
影响因子：
30.8
作者：
Michailidou K;Beesley J;Lindstrom S;Canisius S;Dennis J;Lush MJ;Maranian MJ;Bolla MK;Wang Q;Shah M;Perkins BJ;Czene K;Eriksson M;Darabi H;Brand JS;Bojesen SE;Nordestgaard BG;Flyger H;Nielsen SF;Rahman N;Turnbull C;BOCS;Fletcher O;Peto J;Gibson L;dos-Santos-Silva I;Chang-Claude J;Flesch-Janys D;Rudolph A;Eilber U;Behrens S;Nevanlinna H;Muranen TA;Aittomäki K;Blomqvist C;Khan S;Aaltonen K;Ahsan H;Kibriya MG;Whittemore AS;John EM;Malone KE;Gammon MD;Santella RM;Ursin G;Makalic E;Schmidt DF;Casey G;Hunter DJ;Gapstur SM;Gaudet MM;Diver WR;Haiman CA;Schumacher F;Henderson BE;Le Marchand L;Berg CD;Chanock SJ;Figueroa J;Hoover RN;Lambrechts D;Neven P;Wildiers H;van Limbergen E;Schmidt MK;Broeks A;Verhoef S;Cornelissen S;Couch FJ;Olson JE;Hallberg E;Vachon C;Waisfisz Q;Meijers-Heijboer H;Adank MA;van der Luijt RB;Li J;Liu J;Humphreys K;Kang D;Choi JY;Park SK;Yoo KY;Matsuo K;Ito H;Iwata H;Tajima K;Guénel P;Truong T;Mulot C;Sanchez M;Burwinkel B;Marme F;Surowy H;Sohn C;Wu AH;Tseng CC;Van Den Berg D;Stram DO;González-Neira A;Benitez J;Zamora MP;Perez JI;Shu XO;Lu W;Gao YT;Cai H;Cox A;Cross SS;Reed MW;Andrulis IL;Knight JA;Glendon G;Mulligan AM;Sawyer EJ;Tomlinson I;Kerin MJ;Miller N;kConFab Investigators;AOCS Group;Lindblom A;Margolin S;Teo SH;Yip CH;Taib NA;Tan GH;Hooning MJ;Hollestelle A;Martens JW;Collée JM;Blot W;Signorello LB;Cai Q;Hopper JL;Southey MC;Tsimiklis H;Apicella C;Shen CY;Hsiung CN;Wu PE;Hou MF;Kristensen VN;Nord S;Alnaes GI;NBCS;Giles GG;Milne RL;McLean C;Canzian F;Trichopoulos D;Peeters P;Lund E;Sund M;Khaw KT;Gunter MJ;Palli D;Mortensen LM;Dossus L;Huerta JM;Meindl A;Schmutzler RK;Sutter C;Yang R;Muir K;Lophatananon A;Stewart-Brown S;Siriwanarangsan P;Hartman M;Miao H;Chia KS;Chan CW;Fasching PA;Hein A;Beckmann MW;Haeberle L;Brenner H;Dieffenbach AK;Arndt V;Stegmaier C;Ashworth A;Orr N;Schoemaker MJ;Swerdlow AJ;Brinton L;Garcia-Closas M;Zheng W;Halverson SL;Shrubsole M;Long J;Goldberg MS;Labrèche F;Dumont M;Winqvist R;Pylkäs K;Jukkola-Vuorinen A;Grip M;Brauch H;Hamann U;Brüning T;GENICA Network;Radice P;Peterlongo P;Manoukian S;Bernard L;Bogdanova NV;Dörk T;Mannermaa A;Kataja V;Kosma VM;Hartikainen JM;Devilee P;Tollenaar RA;Seynaeve C;Van Asperen CJ;Jakubowska A;Lubinski J;Jaworska K;Huzarski T;Sangrajrang S;Gaborieau V;Brennan P;McKay J;Slager S;Toland AE;Ambrosone CB;Yannoukakos D;Kabisch M;Torres D;Neuhausen SL;Anton-Culver H;Luccarini C;Baynes C;Ahmed S;Healey CS;Tessier DC;Vincent D;Bacot F;Pita G;Alonso MR;Álvarez N;Herrero D;Simard J;Pharoah PP;Kraft P;Dunning AM;Chenevix-Trench G;Hall P;Easton DF
通讯作者：
Easton DF
影响因子：
16.6
作者：
Fejerman, Laura;Ahmadiyeh, Nasim;Hu, Donglei;Huntsman, Scott;Beckman, Kenneth B.;Caswell, Jennifer L.;Tsung, Karen;John, Esther M.;Torres-Mejia, Gabriela;Carvajal-Carmona, Luis;Echeverry, Maria Magdalena;Tuazon, Anna Marie D.;Ramirez, Carolina;Gignoux, Christopher R.;Eng, Celeste;Gonzalez-Burchard, Esteban;Henderson, Brian;Le Marchand, Loic;Kooperberg, Charles;Hou, Lifang;Agalliu, Ilir;Kraft, Peter;Lindstroem, Sara;Perez-Stable, Eliseo J.;Haiman, Christopher A.;Ziv, Elad
通讯作者：
Ziv, Elad