The Prognostic Quality of Risk Prediction Models to Assess the Individual Breast Cancer Risk in Women: An Overview of Reviews

Table 3

Overview of the prognostic quality of the empirical and genetic models.

Risk prediction models and derived/modified versions	Number of validation studies	Discriminatory accuracy: AUC (reference), range^1
Empirical risk prediction models
Gail model/BRCAT	58	0.41 [29]–0.93 [30]
BCSC model	6	0.58 [31]–0.72 [32]
Rosner–Colditz model	9	0.57 [33]–0.68 [34]
Genetic risk prediction models
IBIS/Tyrer–Cuzick model	8	0.51 [35, 36]–0.76 [37]
BOADICEA	1 [38]	0.66 (without SNPs); 0.70 (SNP enhanced)
BRCAPRO™	1 [38]	0.65 (without SNPs); 0.69 (SNP enhanced)

AUC = area under the curve, BCSC = Breast Cancer Surveillance Consortium, BRCAT = Breast Cancer Risk Assessment Tool, CI = confidence interval, IBIS = International Breast Cancer Intervention Study, NR = not reported, SNPs = single-nucleotide polymorphisms. ¹Range involves AUC values for varying risk factors. The bold values present the AUC value ranges.