Dawei Zhu1, Ruoxi Ding1, Yong Ma2, Zhishui Chen3, Xuefeng Shi4, Ping He5. 1. China Center for Health Development Studies, Peking University, Beijing, 100191, China. 2. China Health Insurance Research Association, Beijing, 100013, China. 3. Department of Medical Insurance, Peking University Cancer Hospital and Institute, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Beijing, 100142, China. 4. School of Management, Beijing University of Chinese Medicine, Beijing, 100029, China. shixuefeng981206@163.com. 5. China Center for Health Development Studies, Peking University, Beijing, 100191, China. phe@pku.edu.cn.
Abstract
BACKGROUND: Comorbidity has been established as one of the important predictors of poor prognosis in lung cancer. In this study, we analyzed the prevalence of main comorbidities and its association with hospital readmission and fatality for lung cancer patients in China. METHODS: The analyses are based on China Urban Employees' Basic Medical insurance (UEBMI) and Urban Residents' Basic Medical Insurance (URBMI) claims database and Hospital Information System (HIS) Database in the Beijing University Cancer Hospital in 2013-2016. We use Elixhauser Comorbidity Index to identify main types of comorbidities. RESULTS: Among 10,175 lung cancer patients, 32.2% had at least one comorbid condition, and the proportion of patients with one, two, and three or more comorbidities was 21.7, 8.3 and 2.2%, respectively. The most prevalent comorbidities identified were other malignancy (7.5%), hypertension (5.4%), pulmonary disease (3.7%), diabetes mellitus (2.5%), cardiovascular disease (2.4%) and liver disease (2.3%). The predicted probability of having comorbidity and the predicted number of comorbidities was higher for middle elderly age groups, and then decreased among patients older than 85 years. Comorbidity was positively associated with increased risk of 31-days readmission and in-hospital death. CONCLUSION: Our study is the first to provide an overview of comorbidity among lung cancer patients in China, underlines the necessity of incorporating comorbidity in the design of screening, treatment and management of lung cancer patients in China.
BACKGROUND: Comorbidity has been established as one of the important predictors of poor prognosis in lung cancer. In this study, we analyzed the prevalence of main comorbidities and its association with hospital readmission and fatality for lung cancerpatients in China. METHODS: The analyses are based on China Urban Employees' Basic Medical insurance (UEBMI) and Urban Residents' Basic Medical Insurance (URBMI) claims database and Hospital Information System (HIS) Database in the Beijing University Cancer Hospital in 2013-2016. We use Elixhauser Comorbidity Index to identify main types of comorbidities. RESULTS: Among 10,175 lung cancerpatients, 32.2% had at least one comorbid condition, and the proportion of patients with one, two, and three or more comorbidities was 21.7, 8.3 and 2.2%, respectively. The most prevalent comorbidities identified were other malignancy (7.5%), hypertension (5.4%), pulmonary disease (3.7%), diabetes mellitus (2.5%), cardiovascular disease (2.4%) and liver disease (2.3%). The predicted probability of having comorbidity and the predicted number of comorbidities was higher for middle elderly age groups, and then decreased among patients older than 85 years. Comorbidity was positively associated with increased risk of 31-days readmission and in-hospital death. CONCLUSION: Our study is the first to provide an overview of comorbidity among lung cancerpatients in China, underlines the necessity of incorporating comorbidity in the design of screening, treatment and management of lung cancerpatients in China.
Authors: Jacques Ferlay; Hai-Rim Shin; Freddie Bray; David Forman; Colin Mathers; Donald Maxwell Parkin Journal: Int J Cancer Date: 2010-12-15 Impact factor: 7.396
Authors: Zhengwei Huang; Stephen Nicholas; Yong Yang; Xiaoping Chen; Elizabeth Maitland; Yong Ma; Xuefeng Shi Journal: BMC Health Serv Res Date: 2022-02-19 Impact factor: 2.655