Abstract

The majority of newly diagnosed breast cancers in the US are in women aged older than 65 years who can have additional comorbidities. Balancing the risks and benefits of treatment should take into account these competing risks of death. The Surveillance, Epidemiology, and End Results Program-Medicare database was used to identify women with stage I breast cancer undergoing operations from 2004-2012. Using neural network analysis, comorbidities associated with mortality were grouped into clinically relevant categories. Cumulative incidence graphs and Fine and Gray competing risk regression analyses were used to study the association of age, race, comorbidity groupings, and tumor variables with 3 competing mortality outcomes: dead of disease (DOD), dead of other cancers (DOC), and non-cancer death (NCD). The overall cumulative incidence of mortality was 4.9% for DOD, 3.7% for DOC, and 21.3% for NCD for the 47,220 patients studied. For all patients, the 5- and 8-year probability of DOD was 3% and 4.7%, for DOC 1.9% and 3.5%, and for NCD 9.8% and 18.9%, respectively. The presence of any major comorbidity (eg cardiovascular or neurologic disorders) significantly increased the probability of NCD, and estrogen receptor status was the strongest predictor of DOD. Given patient age, comorbidity, and estrogen receptor status, an estimate of competing risks of death from DOD, DOC, and NCD can be calculated. To aid clinical decision making, we quantify competing risks of death in patients with stage I breast cancer by taking into account patient age, comorbidity, and estrogen receptor status.

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