Development and validation of polygenic risk scores for prediction of breast cancer and breast cancer subtypes in Chinese women

Table 1 Characteristic of the participants in the Sichuan Breast Cancer Case-Control Study

Characteristics	Control (N = 374)	Case (N = 427)	P-value^*
Continuous variables (median, IQR)
Age (years)	48.00 (42.00–53.00)	50.00 (44.00–57.00)	0.01
BMI (kg/m²)	23.37 (21.46–25.10)	22.94 (21.23–25.24)	0.18
Age at menarche (years)	14.00 (13.00–15.00)	14.00 (13.00–15.00)	0.29
Number of live births (N)	1.00 (1.00–1.00)	1.00 (1.00–2.00)	< 0.001
Gail-2 model 5-year risk (%)	0.54 (0.42–0.67)	0.54 (0.46–0.67)	0.07
PRS_RLR	0.44 (0.05–0.84)	0.62 (0.23–1.05)	< 0.001
PRS_LRR	0.02 (−0.18–0.23)	0.14 (− 0.06–0.32)	< 0.001
PRS_ANN	− 0.17 (− 0.33–0.09)	0.01 (− 0.24–0.13)	< 0.001
Categorical variables (N, %)
Menopausal status			0.33
Premenopausal	223 (59.63%)	239 (55.97%)
Postmenopausal	151 (40.37%)	188 (44.03%)
Family history of breast cancer			0.83
Yes	7 (1.87%)	10 (2.34%)
No	367 (98.13%)	417 (97.66%)

^*P-value from Mann-Whitney U test (continuous variables) or chi-square test (categorical variables)
BMI body mass index, IQR interquartile range, PRS polygenic risk score, RLR repeated logistic regression, LRR logistic ridge regression, ANN Artificial Neural Network

ISSN: 1471-2407