A multi-state model incorporating cardiovascular risk factors and breast cancer characteristics outperformed traditional models for predicting 5-year cardiovascular death, achieving an AUC of 0.85.
Cohort (n=20,462)
Does a multi-state model incorporating breast cancer characteristics and cardiovascular risk factors improve prediction of cardiovascular and cancer mortality in women with loco-regional breast cancer compared to traditional cardiovascular risk models?
A novel multi-state model incorporating both breast cancer characteristics and cardiovascular risk factors outperforms traditional cardiovascular risk models in predicting cardiovascular mortality in women with loco-regional breast cancer.
Effect estimate: AUC 0.85 (95% CI 0.83-0.86)
BACKGROUND: Many women with breast cancer also have a high likelihood of cardiovascular mortality, and while there are several cardiovascular risk prediction models, none have been validated in a cohort of breast cancer patients. We first compared the performance of commonly-used cardiovascular models, and then derived a new model where breast cancer and cardiovascular mortality were modeled simultaneously, to account for the competing risk endpoints and commonality of risk factors between the two events. METHODS: We included 20,462 women diagnosed with stage I-III breast cancer between 2000 and 2010 in Kaiser Permanente Northern California (KPNC) with follow-up through April 30, 2015, and examined the performance of the Framingham, CORE and SCOREOP cardiovascular risk models by area under the receiver operating characteristic curve (AUC), and observed-to -expected (O/E) ratio. We developed a multi-state model based on cause-specific hazards (CSH) to jointly model the causes of mortality. RESULTS: The extended models including breast cancer characteristics (grade, tumor size, nodal involvement) with CVD risk factors had better discrimination at 5-years with AUCs of 0.85 (95% CI 0.83, 0.86) for cardiovascular death and 0.80 (95% CI 0.78, 0.87) for breast cancer death compared with the existing cardiovascular models evaluated at 5 years AUCs ranging 0.71-0.78. Five-year calibration for breast and cardiovascular mortality from our multi-state model was also excellent (O/E = 1.01, 95% CI 0.91-1.11). CONCLUSION: A model incorporating cardiovascular risk factors, breast cancer characteristics, and competing events, outperformed traditional models of cardiovascular disease by simultaneously estimating cancer and cardiovascular mortality risks.
Leoce et al. (Mon,) conducted a cohort in Stage I-III breast cancer (n=20,462). Multi-state risk prediction model vs. Traditional cardiovascular risk models was evaluated on Discrimination (AUC) for 5-year cardiovascular death (AUC 0.85, 95% CI 0.83-0.86). A multi-state model incorporating cardiovascular risk factors and breast cancer characteristics outperformed traditional models for predicting 5-year cardiovascular death, achieving an AUC of 0.85.
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