Risk estimation for healthy women from breast cancer families: New insights and new strategies

被引：32

作者：

van Asperen, CJ

Jonker, MA

Jacobi, CE

van Diemen-Homan, JEM

Bakker, E

Breuning, MH

van Houwelingen, JC

de Bock, GH

机构：

[1] Leiden Univ, Ctr Med, Dept Clin Genet, Ctr Human & Clin Genet, NL-2300 RC Leiden, Netherlands

[2] Leiden Univ, Ctr Med, Dept Med Stat, NL-2300 RC Leiden, Netherlands

[3] Leiden Univ, Ctr Med, Dept Med Decis Making, NL-2300 RC Leiden, Netherlands

来源：

CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION | 2004年 / 13卷 / 01期

关键词：

D O I：

10.1158/1055-9965.EPI-03-0090

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

Risk estimation in breast cancer families is often estimated by use of the Claus tables. We analyzed the family histories of 196 counselees; compared the Claus tables with the Claus, the BRCA1/2, the BRCA1/2/ models; and performed linear regression analysis to extend the Claus tables with characteristics of hereditary breast cancer. Finally, we compared the Claus extended method with the Claus, the BRCA1/2, and the BRCAI/2/u models. We found 47% agreement for Claus table versus Claus model; 39% agreement for Claus table versus BRCA1/2 model; 48% agreement for Claus table versus BRCA1/2/u model; 37% agreement for Claus extended method versus Claus model; 44% agreement for Claus extended model versus BRCA1/2 model; and 66% agreement for Claus extended method versus BRCA1/2/u model. The regression formula (Claus extended method) for the lifetime risk for breast cancer was 0.08 + 0.40 * Claus Table + 0.07 * ovarian cancer + 0.08 * bilateral breast cancer + 0.07 * multiple cases. This new method for risk estimation, which is an extension of the Claus tables, incorporates information on the presence of ovarian cancer, bilateral breast cancer, and whether there are more than two affected relatives with breast cancer. This extension might offer a good alternative for breast cancer risk estimation in clinical practice.

引用

页码：87 / 93

页数：7

共 35 条

[31] BRCA 1 sequence analysis in women at high risk for susceptibility mutations - Risk factor analysis and implications for genetic testing [J].

ShattuckEidens, D ;

Oliphant, A ;

McClure, M ;

McBride, C ;

Gupte, J ;

Rubano, T ;

Pruss, D ;

Tavtigian, SV ;

Teng, DHF ;

Adey, N ;

Staebell, M ;

Gumpper, K ;

Lundstrom, R ;

Hulick, M ;

Kelly, M ;

Holmen, J ;

Lingenfelter, B ;

Manley, S ;

Fujimura, F ;

Luce, M ;

Ward, B ;

CannonAlbright, L ;

Steele, L ;

Offit, K ;

Gilewski, T ;

Norton, L ;

Brown, K ;

Schulz, C ;

Hampel, H ;

Schluger, A ;

Giulotto, E ;

Zoli, W ;

Ravaioli, A ;

Nevanlinna, H ;

Pyrhonen, S ;

Rowley, P ;

Loader, S ;

Osborne, MP ;

Daly, M ;

Tepler, I ;

Weinstein, PL ;

Scalia, JL ;

Michaelson, R ;

Scott, RJ ;

Radice, P ;

Pierotti, MA ;

Garber, JE ;

Isaacs, C ;

Peshkin, B ;

Lippman, ME .

JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 1997, 278 (15) :1242-1250

[32] A comparison of methods currently used in clinical practice to estimate familial breast cancer risks [J].

Tischkowitz, M ;

Wheeler, D ;

France, E ;

Chapman, C ;

Lucassen, A ;

Sampson, J ;

Harper, P ;

Krawczak, M ;

Gray, J .

ANNALS OF ONCOLOGY, 2000, 11 (04) :451-454

[33] What do women really want to know? Motives for attending familial breast cancer clinics [J].

van Asperen, CJ ;

van Dijk, S ;

Zoeteweij, MW ;

Timmermans, DRM ;

de Bock, GH ;

Meijers-Heijboer, EJ ;

Niermeijer, MF ;

Breuning, MH ;

Kievit, J ;

Otten, W .

JOURNAL OF MEDICAL GENETICS, 2002, 39 (06) :410-414

[34]

Weitzel JN, 1999, CANCER, V86, P2483, DOI 10.1002/(SICI)1097-0142(19991201)86:11+<2483::AID-CNCR5>3.0.CO

[35]

2-4

← 1 2 3 4 →