Fasching Peter A, Bani Mayada R, Nestle-Krämling Carolin, Goecke Tim O, Niederacher Dieter, Beckmann Matthias W, Lux Michael P
Department of Gynecology and Obstetrics, Erlangen University Hospital, Erlangen, Germany.
Eur J Cancer Prev. 2007 Jun;16(3):216-24. doi: 10.1097/CEJ.0b013e32801023b3.
Chemoprevention, prophylactic surgery, and intensified screening can be offered to patients with an increased lifetime risk, p(life), for breast cancer. Estimation of p(life) includes BRCA analysis and risk estimation based on individual risk factors and family history. MENDEL and BRCAPRO are models that estimate the probability of BRCA1/2-mutations, p(mut), and p(life). In this study, the models are compared with Ford and Claus penetrance/frequency functions. The results were compared with the Tyrer-Cuzick model. Genetic analysis of 111 breast cancer-affected patients from 103 kindreds with a family history of breast and/or ovarian cancer (German Consortium for Hereditary Breast and Ovarian Cancer) was carried out by sequencing BRCA1 and BRCA2. p(life) and p(mut) were calculated with MENDEL, BRCAPRO(Claus), BRCAPRO(Ford), as well as the Tyrer-Cuzick model. The accuracy of p(mut) was analyzed by receiver operating characteristics, and p(life) of each model was compared. The strongest correlation of p(life) was shown by BRCAPRO(Ford)/MENDEL, at r=0.69; no correlation was shown by BRCAPRO(Claus)/MENDEL, at r=0.018. The Tyrer-Cuzick model had the strongest correlations with MENDEL and BRCAPRO(Ford). For MENDEL and BRCAPRO, low correlation or p(mut)-prediction was improved by excluding kindreds with ovarian cancer. p(mut) showed the best accuracy for BRCAPRO(Ford) and MENDEL. BRCAPRO and MENDEL are useful tools for calculating p(mut). They can provide support in decision-making for or against genetic analysis. Estimations of p(life) and p(mut) based on a mathematical model should use algorithms and penetrance/frequency data appropriate to the population counseled. Reproductive/hormonal data, should be incorporated as Tyrer-Cuzick does.
对于乳腺癌终生风险p（life）增加的患者，可以提供化学预防、预防性手术和强化筛查。p（life）的估计包括BRCA分析以及基于个体风险因素和家族史的风险估计。MENDEL和BRCAPRO是估计BRCA1/2突变概率p（mut）和p（life）的模型。在本研究中，将这些模型与Ford和Claus外显率/频率函数进行比较。将结果与Tyrer-Cuzick模型进行比较。对来自103个有乳腺癌和/或卵巢癌家族史的家系（德国遗传性乳腺癌和卵巢癌联盟）的111例乳腺癌患者进行了BRCA1和BRCA2测序的基因分析。用MENDEL、BRCAPRO（Claus）、BRCAPRO（Ford）以及Tyrer-Cuzick模型计算p（life）和p（mut）。通过受试者工作特征分析p（mut）的准确性，并比较每个模型的p（life）。BRCAPRO（Ford）/MENDEL显示p（life）的相关性最强，r = 0.69；BRCAPRO（Claus）/MENDEL显示无相关性，r = 0.018。Tyrer-Cuzick模型与MENDEL和BRCAPRO（Ford）的相关性最强。对于MENDEL和BRCAPRO，通过排除有卵巢癌的家系，低相关性或p（mut）预测得到改善。BRCAPRO（Ford）和MENDEL的p（mut）准确性最佳。BRCAPRO和MENDEL是计算p（mut）的有用工具。它们可为支持或反对基因分析的决策提供帮助。基于数学模型的p（life）和p（mut）估计应使用适合所咨询人群的算法和外显率/频率数据。应像Tyrer-Cuzick模型那样纳入生殖/激素数据。
