Natalia Teixeira1, Simone Maistro2, Maria Del Pilar Estevez Diz3, Marian J Mourits4, Jan C Oosterwijk5, Maria Aparecida Koike Folgueira2, Geertruida H de Bock6. 1. 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. Electronic address: n.teixeira@umcg.nl. 2. Center of Translational Oncology Investigation (CTO), Instituto do Câncer do Estado de São Paulo, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil. 3. Department of Clinical Oncology, Instituto do Câncer do Estado de São Paulo, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil. 4. Department of Gynecologic Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. 5. Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. 6. Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Abstract
OBJECTIVES: 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). STUDY DESIGN: 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. MAIN OUTCOME MEASURES: 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. RESULTS: 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. CONCLUSION: 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.
OBJECTIVES: 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). STUDY DESIGN: 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. MAIN OUTCOME MEASURES: 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. RESULTS: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. CONCLUSION: 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.
Keywords:
AUC; BRCA1 gene; BRCA2 gene; Genetic testing; Hereditary breast and ovarian cancer syndrome; OC; Risk assessment; area under the receiver operating characteristic curves; ovarian cancer
Authors: Marcelo Cristiano de Azevedo Ramos; Maria Aparecida Azevedo Koike Folgueira; Simone Maistro; Alessandro Gonçalves Campolina; Patricia Coelho de Soárez; Geertruida Hendrika de Bock; Hillegonda Maria Dutilh Novaes; Maria Del Pilar Estevez Diz Journal: Rev Saude Publica Date: 2018-11-29 Impact factor: 2.106