IGES 2025: Causality, diversity, and innovation
Read about the 2025 International Genetic Epidemiology Society conference and learn why genomics research is entering a new era.
STATGEN 2024 talk
BRCAPRO+BCRAT: extending a Mendelian breast cancer risk prediction model to include non-genetic risk factors
Zoe Guan
BRCAPRO: Mendelian model, genes
BCRAT: 1st family hx, hormonal risk factors, hx of benign disease
Combine these complementary models.
https://www.mdpi.com/2072-6694/15/4/1090
#STATGEN2024 #Genetics #BreastCancer #RiskPrediction #StatisticalGenetics
Combining Breast Cancer Risk Prediction Models
Accurate risk stratification is key to reducing cancer morbidity through targeted screening and preventative interventions. Multiple breast cancer risk prediction models are used in clinical practice, and often provide a range of different predictions for the same patient. Integrating information from different models may improve the accuracy of predictions, which would be valuable for both clinicians and patients. BRCAPRO is a widely used model that predicts breast cancer risk based on detailed family history information. A major limitation of this model is that it does not consider non-genetic risk factors. To address this limitation, we expand BRCAPRO by combining it with another popular existing model, BCRAT (i.e., Gail), which uses a largely complementary set of risk factors, most of them non-genetic. We consider two approaches for combining BRCAPRO and BCRAT: (1) modifying the penetrance (age-specific probability of developing cancer given genotype) functions in BRCAPRO using relative hazard estimates from BCRAT, and (2) training an ensemble model that takes BRCAPRO and BCRAT predictions as input. Using both simulated data and data from Newton-Wellesley Hospital and the Cancer Genetics Network, we show that the combination models are able to achieve performance gains over both BRCAPRO and BCRAT. In the Cancer Genetics Network cohort, we show that the proposed BRCAPRO + BCRAT penetrance modification model performs comparably to IBIS, an existing model that combines detailed family history with non-genetic risk factors.
Heart disease: CT scans may be best for predicting risk during middle age
A new study suggests that CT scans used in conjunction with traditional risk markers can help doctors assess individual coronary heart disease risk more accurately than genetic testing in middle aged and older adults.
Lars Juhl Jensen
Daniel E. Weeks
Poetry News