S. Miccoli

Development of a risk score based on clinical–pathological features to predict the presence of germline BRCA1/2 pathogenic variants in ovarian cancer patients

Identification of germline BRCA1/2 pathogenic variants is crucial for tailoring ovarian cancer treatment and prevention. The purpose of the study was to develop a model to predict BRCA1/2 status in ovarian cancer patients. The association between clinical-pathological features and BRCA1/2 status was analysed in a series of 1009 ovarian cancer patients, using Fisher's exact test. Logistic regression models and a decision tree classification algorithm were used to develop a risk score. Compared with noncarriers, BRCA1/2 carriers (n = 216; 21.4%) presented more frequently with serous histotype non-low-grade (92.3% versus 71.6%, P < 0.001), family history of ovarian cancer (31.6% versus 5.7%, P < 0.001), family history of breast cancer (53.7% versus 31.6%, P < 0.001), previous breast cancer (20.9% versus 8.5%, P < 0.001), advanced stage (78.8% versus 69.5%, P = 0.019) and younger age (56.9 years versus 60.8 years, P < 0.001). Multivariable logistic regression on 648 patients with complete data confirmed histotype, family history of breast/ovarian cancer, previous breast cancer and age as independently and significantly associated with BRCA1/2 status. After refining the categorization of variables according to decision tree classification algorithm results, odds ratios derived from multivariable logistic regression were used to assign weights from 1 to 3 to each feature (non-low-grade serous histotype = 3, low-grade serous/high-grade endometrioid histotype/family history of ovarian cancer = 2, age at diagnosis <50 years/family and personal history of breast cancer = 1) and to develop a score ranging from 0 to 10, associated with increasing risk of BRCA1/2 variants (from 0.6% for score 0 to 88% for score ≥7). The area under the curve of the score was 0.78 (95% confidence interval 0.74-0.82) and the optimal cut-off was ≥4 points with a sensitivity of 81% and a specificity of 62.3%. The proposed risk score may improve assessment and counselling of ovarian cancer patients.