Modeling risks of cardiovascular and cancer mortality following a diagnosis of loco-regional breast cancer

Leoce, Nicole M.; Jin, Zhezhen; Kehm, Rebecca D.; Roh, Janise M.; Laurent, Cecile A.; Kushi, Lawrence H.; Terry, Mary B.

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.

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.

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).

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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Breast Cancer Research

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Published Here
December 20, 2022


Breast cancer, Cardiovascular disease, Cardiovascular mortality, Risk prediction models