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Background: For cancer patients, comorbidities affect the risk, progression, and process of treatment. They negatively affect prognoses by increasing mortality. It is therefore necessary to predict prognoses accurately for cancer survivors by measuring comorbidities and their severity.Methods: In this study, the frequency of comorbidities was analyzed on the basis of the Charlson comorbidity index (CCI) in breast cancer patients drawn from the National Health Insurance Service-National Sample Cohort data. This study examined the relative effects of certain factors (age, diagnosis period, and CCI) between deaths and cancer survivors with logistic regression analysis. We applied Cox's proportional hazard regression analysis to predict the risk of mortality according to CCI as a survival predictor of breast cancer patients using three models with correction for age, including the body mass index (BMI), smoking status, alcohol intake, and childbirth history.Results: The frequency analysis based on CCI found that the most frequent type of condition was pulmonary disease (2,262; 21.5%), followed by peptic ulcer (2,019; 19.2%), and metastatic cancer (1,821; 17.3%). The older one gets, the greater one’s risk of mortality with more severe comorbidities. Age and BMI led to greater risk of mortality, with correction for the variables (age, BMI, smoking status, alcohol intake and childbirth history) that could cause confounding.Conclusions: Severity of comorbidities significantly increased the risk of mortality for breast cancer patients. In particular, those cancer survivors who are aged ≥60 years, who have high BMI, and who once smoked need to get continuous care due to poor prognoses.

Factors of Specific Comorbidities Severity on the Risk of Mortality among Breast Cancer Survivors