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Epidemiol Health > Accepted Articles
Epidemiology and Health 2022;e2022075.
DOI: https://doi.org/10.4178/epih.e2022075    [Accepted] Published online Sep 13, 2022.
Prediction of cancer survivors’ mortality risk in Korea: a 25-year nationwide prospective cohort study
Yeun Soo Yang1,2  , Hee Jin Kimm2  , Keum Ji Jung2  , Seul Ji Moon2  , Sun Mi Lee3  , Sun Ha Jee2 
1Department of Public Health, Yonsei University Graduate School, Seoul, Korea, Seoul, Korea
2Department of Epidemiology and Health Promotion, Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul city, Korea
3Health Insurance Policy Research Institute, National Health Insurance Service, Wonju, Korea
Correspondence  Keum Ji Jung ,Email: KJJUNG@yuhs.ac
Received: May 9, 2022  Accepted after revision: Sep 13, 2022
Abstract
Objectives:
To investigate the factors affecting cancer survivors and develop a Korean mortality prediction model for cancer survivors. Our study identified lifestyle and mortality risk factors and attempted to determine if health-promoting lifestyles affect mortality.
Method:
Among the 1,637,287 participants, 200,834 cancer survivors who were alive after cancer diagnosis were analyzed in the Korean Cancer Prevention Study (KCPS) cohort. Discrimination and calibration for predicting the 10-year mortality risk were evaluated. The prediction model was derived using the Cox model coefficients, mean risk factor values, and mean mortality from the cancer survivors in KCPS cohort.
Results:
During the 21.6-year follow-up, the all-cause mortality rates of cancer survivors were 57.2% and 39.4% in men and women, respectively. Men, older age, current smoking, and history of diabetes were high-risk factors for mortality. In contrast, exercise habits and a family history of cancer showed a reduced risk. The prediction model discriminations in the validation dataset for both KCPS all-cause mortality (KAR) and KCPS cancer mortality (KCR) were C-statistics, 0.69 and 0.68, respectively. Based on the constructed prediction models, when we modified exercise status and smoking status, which are modifiable factors, the risk of mortality of cancer survivors decreased linearly (30% to 9%). Moreover, there was an equally linear reduction in the risk of cancer-related mortality, decreasing from 24% to 3%.
Conclusions:
A mortality prediction model for cancer survivors was developed and may be helpful in supporting a healthy life. Lifestyle modifications in cancer survivors may affect the risk of mortality in the future.
Keywords: cancer survivor; prediction; mortality risk factors; lifestyle modification; tobacco smoking


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