Teixeira Natalia, Maistro Simone, Del Pilar Estevez Diz Maria, Mourits Marian J, Oosterwijk Jan C, Folgueira Maria Aparecida Koike, de Bock Geertruida H
Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands; Center of Translational Oncology Investigation (CTO), Instituto do Câncer do Estado de São Paulo, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil.
Center of Translational Oncology Investigation (CTO), Instituto do Câncer do Estado de São Paulo, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil.
Maturitas. 2017 Nov;105:113-118. doi: 10.1016/j.maturitas.2017.06.002. Epub 2017 Jun 4.
To evaluate the accuracy of algorithms for predicting BRCA1/2 germ-line mutation carrier probability, and to identify factors that could improve their performance among Brazilian women with ovarian cancer (OC).
In this cross-sectional study, we enrolled patients (unselected for family history of cancer) undergoing treatment or follow-up for OC in a single centre in Brazil. Clinical and demographic data, including family history of cancer, were obtained. Blood samples were collected for genetic testing.
The entire coding sequence of BRCA1 and BRCA2 was evaluated for mutations. Mutation carrier probability was calculated using BOADICEA, BRCAPRO, Myriad and the Manchester score. Sensitivity, specificity, positive and negative predictive values, and area under the receiver operating characteristic curves (AUC) were calculated for each algorithm. Logistic regression was used to detect additional factors associated with BRCA1/2 status, and these were added to the algorithms before recalculating the AUCs.
BRCA1/2 mutations were identified in 19 of the 100 included patients. BOADICEA outperformed other algorithms (sensitivity, 73.7%; specificity, 87.7%; AUC, 0.87, with a threshold of a 10% risk of mutation). Later menarche was associated with the presence of a BRCA1/2 mutation. Although adding age at menarche resulted in a larger AUC for all models, this increase was significant only for the Myriad algorithm.
A BOADICEA risk evaluation of 10% or more most accurately predicted BRCA1/2 status, and the inclusion of age at menarche tended to improve the performance of all algorithms. Using these tools could reduce the number of tests, but at the expense of missing a significant proportion of mutation carriers.
评估预测BRCA1/2种系突变携带者概率的算法的准确性,并确定可改善巴西卵巢癌(OC)女性中这些算法性能的因素。
在这项横断面研究中,我们纳入了在巴西单一中心接受OC治疗或随访的患者(未根据癌症家族史进行筛选)。获取了包括癌症家族史在内的临床和人口统计学数据。采集血样进行基因检测。
评估BRCA1和BRCA2的整个编码序列是否存在突变。使用BOADICEA、BRCAPRO、Myriad和曼彻斯特评分计算突变携带者概率。计算每种算法的敏感性、特异性、阳性和阴性预测值以及受试者操作特征曲线下面积(AUC)。使用逻辑回归检测与BRCA1/2状态相关的其他因素,并在重新计算AUC之前将这些因素添加到算法中。
在100名纳入患者中,有19名被鉴定出存在BRCA1/2突变。BOADICEA的表现优于其他算法(敏感性为73.7%;特异性为87.7%;AUC为0.87,突变风险阈值为10%)。月经初潮较晚与BRCA1/2突变的存在相关。尽管将月经初潮年龄纳入所有模型后AUC更大,但这种增加仅在Myriad算法中具有统计学意义。
BOADICEA风险评估为10%或更高时最准确地预测了BRCA1/2状态,纳入月经初潮年龄倾向于改善所有算法的性能。使用这些工具可以减少检测次数,但代价是会遗漏相当一部分突变携带者。