Risk prediction models for familial breast cancer.
Summary
This meta-analysis assessed the performance of breast cancer risk prediction models in women with a family history of the disease. The Gail (BCRAT) and BOADICEA models demonstrated good calibration, while Tyrer-Cuzick overpredicted and BRCAPRO underpredicted risk. Regarding discriminatory accuracy, no single model was clearly superior, with Tyrer-Cuzick version 8, BOADICEA, and BRCAPRO showing similar modest discrimination. The authors suggest that BOADICEA may be useful for patient management in familial breast cancer risk settings, despite limitations such as high risk of bias and study heterogeneity.
Analysis
This study is crucial for clinical practice as it compares the effectiveness of various breast cancer risk prediction tools in women with a high familial risk. It highlights the strengths and weaknesses of widely used models like Gail, Tyrer-Cuzick, BOADICEA, and BRCAPRO, enabling clinicians to select the most appropriate model for personalized screening and prevention strategies. The potential recommendation of BOADICEA, despite caveats, offers valuable guidance for risk assessment and clinical decision-making, while also emphasizing the need for improved discriminatory ability of existing models and better reporting in future studies.