Key result
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.
Why the study?
Existing cardiovascular risk prediction models have not been validated in breast cancer patients, who often face high cardiovascular mortality and shared risk factors across competing causes of death.
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?
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.
Answers are grounded in this paper and cite their sources.
May aid CV risk stratification in breast cancer survivors; leaves open need for prospective validation before practice change.
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.
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Leoce et al. (2021) 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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