Mahshid Ghoncheh - Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Jalal poorolajal - Department of Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran
Gohar mohammadi - Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Introduction: Several approaches have been suggested for incorporating risk factors to predict the future risk of breast cancer. The BOADICEA and IBIS are among these approaches. We compared the performance of these models in discriminate between cases and controls in the Iranian women. Methods: This case-control study was conducted in Tehran in 2015. We enrolled 1633 women aged 24 to 75 years, including 506 cases of breast cancer, 916 population-based controls, and 211 clinic-based controls. The risk of breast cancer predicted by the IBIS and BOADICEA models and the logistic regression model calculated and compared. For model discrimination, we computed the area under the Receiver Operating Characteristic (ROC).Results: The risk of breast cancer predicted by IBIS model was higher than BOADICEA model, but lower than logistic model. The area under the ROC plots indicated that the logistic regression model showed better discrimination between cases and controls (71.53%) compared to IBIS model (49.36%) and BOADICEA model (35.84%).Based on the Pierson correlation coefficient, the correlation between IBIS and BOADICEA models was much stronger than the correlation between IBIS and logistic models (0.3884 and 0.1639, respectively). Conclusion: The IBIS model discriminated cases and controls better than BOADICEA model in the Iranian women. However, the discrimination of the logistic regression model was better than the two models

Breast Neoplasms; Risk Assessment; Case-Control Studies