LAUSR

In addition to impacting incidence, risk factors for breast cancer may also influence recurrence and survival from the disease. However, it is unclear how these factors affect combinatorial biomarkers for aiding treatment decision-making in breast cancer. Patients were 8179 women with histologically confirmed invasive breast cancer, diagnosed and treated in a large cancer hospital in Beijing, China. Individual clinicopathological (tumor size, grade, lymph nodes) and immunohistochemical (IHC: ER, PR, HER2, KI67) markers were used to define clinically relevant combinatorial prognostic biomarkers, including the Nottingham Prognostic Index (NPI: combining size, grade, nodes) and IHC4 score (combining ER, PR, HER2, KI67). Odds ratios (ORs) and 95% confidence intervals (CIs) for associations between breast cancer risk factors and quartiles (Q1–Q4) of NPI and IHC4 were assessed in multivariable polytomous logistic regression models. Overall, increasing parity (ORtrend(95% CI) = 1.20(1.05–1.37);Ptrend = 0.007), overweight (OR(95% CI)vs normal = 1.60(1.29–1.98)), and obesity (OR(95% CI) vs normal = 2.12(1.43–3.14)) were associated with higher likelihood of developing tumors with high (Q4) versus low (Q1) NPI score. Conversely, increasing age (ORtrend(95% CI) = 0.75(0.66–0.84);Ptrend < 0.001) and positive family history of breast cancer (FHBC) (OR(95% CI) = 0.66(0.45–0.95)) were inversely associated with NPI. Only body mass index (BMI) was associated with IHC4, with overweight (OR(95% CI) vs normal = 0.82(0.66–1.02)) and obese (OR(95% CI) vs normal = 0.52(0.36–0.76)) women less likely to develop high IHC4 tumors. Notably, elevated BMI was associated with higher NPI irrespective of hormone receptor-expression status. Our findings indicate that factors affecting breast cancer incidence, particularly age, parity, FHBC, and BMI, may impact clinically relevant prognostic biomarkers with implications for surveillance, prognostication, and counseling.