Genetic and clinical predictors for breast cancer risk assessment and stratification among chinese women

Journal of the National Cancer Institute

Volumn 102, Issue 13, 2010, Pages 972-981

  Zheng, Wei ^a   Wen, Wanqing ^a   Gao, Yu Tang ^b,c   Shyr, Yu ^b   Zheng, Ying ^d   Long, Jirong ^a   Li, Guoliang ^a   Li, Chun ^b   Gu, Kai ^d   Cai, Qiuyin ^a   Shu, Xiao Ou ^a   Lu, Wei ^d  

^a VANDERBILT UNIVERSITY MEDICAL CENTER   (United States)

^b VANDERBILT UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c SHANGHAI CANCER INSTITUTE   (China)

^d Shanghai Institute of Preventive Medicine   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; ARTICLE; BREAST CANCER; CANCER RISK; CHINESE; CONTROLLED STUDY; FAMILY HISTORY; FEMALE; GENETIC MARKER; GENETIC RISK; GENETIC VARIABILITY; GENOME ANALYSIS; HIGH RISK POPULATION; HUMAN; LIVE BIRTH; MAJOR CLINICAL STUDY; MENARCHE; POPULATION RESEARCH; PRIORITY JOURNAL; SCORING SYSTEM; SINGLE NUCLEOTIDE POLYMORPHISM; WAIST HIP RATIO; ASIAN; BREAST TUMOR; CASE CONTROL STUDY; CAUCASIAN; CHINA; GENETIC ASSOCIATION; GENETIC PREDISPOSITION; GENETICS; GENOTYPE; MIDDLE AGED; ONSET AGE; PREDICTION AND FORECASTING; RISK ASSESSMENT; RISK FACTOR; STATISTICAL MODEL; STATISTICS;

ADULT; AGE OF ONSET; ASIAN CONTINENTAL ANCESTRY GROUP; BREAST NEOPLASMS; CASE-CONTROL STUDIES; CHINA; EUROPEAN CONTINENTAL ANCESTRY GROUP; FEMALE; GENETIC PREDISPOSITION TO DISEASE; GENOME-WIDE ASSOCIATION STUDY; GENOTYPE; HUMANS; LIVE BIRTH; MENARCHE; MIDDLE AGED; MODELS, STATISTICAL; POLYMORPHISM, SINGLE NUCLEOTIDE; PREDICTIVE VALUE OF TESTS; RISK ASSESSMENT; RISK FACTORS; WAIST-HIP RATIO;

EID: 77954753875     PISSN: 00278874     EISSN: 14602105     Source Type: Journal    
DOI: 10.1093/jnci/djq170     Document Type: Article

References (39)

1. Nathanson KL, Wooster R, Weber BL. Breast cancer genetics: what we know and what we need. Nat Med. 2001;7(5):552-556.
2. Balmain A, Gray J, Ponder B. The genetics and genomics of cancer. Nat Genet. 2003;33(suppl):238-244.
3. Walsh T, Casadei S, Coats KH, et al. Spectrum of mutations in BRCA1, BRCA2, CHEK2, and TP53 in families at high risk of breast cancer. JAMA. 2006;295(12):1379-1388.
4. Easton DF, Pooley KA, Dunning AM, et al. Genome-wide association study identifes novel breast cancer susceptibility loci. Nature. 2007; 447(7148):1087-1093.
5. Hunter DJ, Kraft P, Jacobs KB, et al. A genome-wide association study identifes alleles in FGFR2 associated with risk of sporadic postmeno-pausal breast cancer. Nat Genet. 2007;39(7):870-874.
6. Stacey SN, Manolescu A, Sulem P, et al. Common variants on chromosomes 2q35 and 16q12 confer susceptibility to estrogen receptor-positive breast cancer. Nat Genet. 2007;39(7):865-869.
7. Stacey SN, Manolescu A, Sulem P, et al. Common variants on chromosome 5p12 confer susceptibility to estrogen receptor-positive breast cancer. Nat Genet. 2008;40(6):703-706.
8. Gold B, Kirchhoff T, Stefanov S, et al. Genome-wide association study provides evidence for a breast cancer risk locus at 6q22.33. Proc Natl Acad Sci USA. 2008;105(11):4340-4345.
9. Zheng W, Long J, Gao YT, et al. Genome-wide association study iden-tifes a new breast cancer susceptibility locus at 6q25.1. Nat Genet. 2009;41(3):324-328.
10. Gail MH. Discriminatory accuracy from single-nucleotide polymorphisms in models to predict breast cancer risk. J Natl Cancer Inst. 2008;100(14): 1037-1041.
11. Pharoah PD, Antoniou AC, Easton DF, Ponder BA. Polygenes, risk prediction, and targeted prevention of breast cancer. N Engl J Med. 2008;358(26):2796-2803.
12. Gail MH, Brinton LA, Byar DP, et al. Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst. 1989;81(24):1879-1886.
13. Rosner B, Colditz GA. Nurses' health study: log-incidence mathematical model of breast cancer incidence. J Natl Cancer Inst. 1996;88(6):359-364.
14. Costantino JP, Gail MH, Pee D, et al. Validation studies for models projecting the risk of invasive and total breast cancer incidence. J Natl Cancer Inst. 1999;91(18):1541-1548.
15. Gail MH, Costantino JP, Pee D, et al. Projecting individualized absolute invasive breast cancer risk in African American women. J Natl Cancer Inst. 2007;99(23):1782-1792.
16. Chlebowski RT, Anderson GL, Lane DS, et al. Predicting risk of breast cancer in postmenopausal women by hormone receptor status. J Natl Cancer Inst. 2007;99(22):1695-1705.
17. Barlow WE, White E, Ballard-Barbash R, et al. Prospective breast cancer risk prediction model for women undergoing screening mammography. J Natl Cancer Inst. 2006;98(17):1204-1214.
18. Tice JA, Cummings SR, Smith-Bindman R, Ichikawa L, Barlow WE, Kerlikowske K. Using clinical factors and mammographic breast density to estimate breast cancer risk: development and validation of a new predictive model. Ann Intern Med. 2008;148(5):337-347.
19. Chen J, Pee D, Ayyagari R, et al. Projecting absolute invasive breast cancer risk in white women with a model that includes mammographic density. J Natl Cancer Inst. 2006;98(17):1215-1226.
20. Parkin DM, Whelan SL, Ferlay J, Storm H. Cancer Incidence in Five Continents. Vol.1-8. 7th ed. Lyon, France; 2005. IARC CancerBase No. 7.
21. Linos E, Spanos D, Rosner BA, et al. Effects of reproductive and demographic changes on breast cancer incidence in China: a modeling analysis. J Natl Cancer Inst. 2008;100(19):1352-1360.
22. Gao YT, Shu XO, Dai Q, et al. Association of menstrual and reproductive factors with breast cancer risk: results from the Shanghai Breast Cancer Study. Int J Cancer. 2000;87(2):295-300.
23. Harrell FE Jr. Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis. Springer. 2001.
24. Steyerberg EW, Harrell FE Jr, Borsboom GJ, Eijkemans MJ, Vergouwe Y, Habbema JD. Internal validation of predictive models: effciency of some procedures for logistic regression analysis. J Clin Epidemiol. 2001;54(8): 774-781.
25. Efron B, Tibshirani R. Improvements on cross-validation: The.632+ bootstrap method. J Amer Statist Assoc. 1997;92(438):548-560.
26. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44(3):837-845.
27. Pencina MJ, D'Agostino RB Sr, D'Agostino RB Jr, Vasan RS. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassifcation and beyond. Stat Med. 2008;27(2):157-172.
28. Benichou J, Gail MH. Methods of inference for estimates of absolute risk derived from population-based case-control studies. Biometrics. 1995;51(1): 182-194.
29. Cook NR, Ridker PM. Advances in measuring the effect of individual predictors of cardiovascular risk: the role of reclassifcation measures. Ann Intern Med. 2009;150(11):795-802.
30. Pharoah PD, Antoniou A, Bobrow M, Zimmern RL, Easton DF, Ponder BA. Polygenic susceptibility to breast cancer and implications for prevention. Nat Genet. 2002;31(1):33-36.
31. Pepe MS, Janes HE. Gauging the performance of SNPs, biomarkers, and clinical factors for predicting risk of breast cancer. J Natl Cancer Inst. 2008;100(14):978-979.
32. Gail MH. Value of adding single-nucleotide polymorphism genotypes to a breast cancer risk model. J Natl Cancer Inst. 2009;101(13):959-963.
33. Zheng W, Chow WH, Yang G, et al. The Shanghai Women's Health Study: rationale, study design, and baseline characteristics. Am J Epidemiol. 2005;162(11):1123-1131.
34. Minami Y, Tsubono Y, Nishino Y, Ohuchi N, Shibuya D, Hisamichi S. The increase of female breast cancer incidence in Japan: emergence of birth cohort effect. Int J Cancer. 2004;108(6):901-906.
35. Yoo KY, Kang D, Park SK, et al. Epidemiology of breast cancer in Korea: occurrence, high-risk groups, and prevention. J Korean Med Sci. 2002;17(1): 1-6.
36. Seow A, Duffy SW, McGee MA, Lee J, Lee HP. Breast cancer in Singapore: trends in incidence 1968-1992. Int J Epidemiol. 1996;25(1): 40-45.
37. Chia KS, Reilly M, Tan CS, et al. Profound changes in breast cancer incidence may refect changes into a Westernized lifestyle: a comparative population-based study in Singapore and Sweden. Int J Cancer. 2005; 113(2):302-306.
38. Tan SM, Evans AJ, Lam TP, Cheung KL. How relevant is breast cancer screening in the Asia/Pacifc region? Breast. 2007;16(2):113-119.
39. Okonkwo QL, Draisma G, der KA, Brown ML, de Koning HJ. Breast cancer screening policies in developing countries: a cost-effectiveness analysis for India. J Natl Cancer Inst. 2008;100(18):1290-1300.