Hailun Xie1,2,3, Guotian Ruan1,2,3, Lishuang Wei4, Heyang Zhang1,2,3, Yizhong Ge1,2,3, Qi Zhang1,2,3, Shiqi Lin1,2,3, Mengmeng Song1,2,3, Xi Zhang1,2,3, Xiaoyue Liu1,2,3, Ming Yang1,2,3, Meng Tang1,2,3, Chun-Hua Song5, Li Deng1,2,3, Hanping Shi6,7,8. 1. Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China. 2. Beijing International Science and Technology Cooperation Base for Cancer Metabolism and Nutrition, Beijing, 100038, China. 3. Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, 100038, China. 4. Department of Geriatric Respiratory Disease Ward, The First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, China. 5. Department of Epidemiology, College of Public Health, Zhengzhou University, Zhenzhou, 450000, China. 6. Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China. shihp@ccmu.edu.cn. 7. Beijing International Science and Technology Cooperation Base for Cancer Metabolism and Nutrition, Beijing, 100038, China. shihp@ccmu.edu.cn. 8. Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, 100038, China. shihp@ccmu.edu.cn.
Abstract
AIMS: Systemic inflammation plays an important role in cancer cachexia. However, among the systemic inflammatory biomarkers, it is unclear which has optimal prognostic value for cancer cachexia. METHODS: The Kaplan-Meier method was used and the log-rank analysis was performed to estimate survival differences between groups. Cox proportional hazard regression analyses were conducted to assess independent risk factors for all-cause mortality. RESULTS: The C-reactive protein-to-albumin ratio (CAR) was the optimal prognostic assessment tool for patients with cancer cachexia, with 1-, 3-, and 5-year predictive powers of 0.650, 0.658, and 0.605, respectively. Patients with a high CAR had significantly lower survival rates than those with a low CAR. Moreover, CAR can differentiate the prognoses of patients with the same pathological stage. Cox proportional risk regression analyses showed that a high CAR was an independent risk factor for cancer cachexia. For every standard deviation increase in CAR, the risk of poor prognosis for patients with cancer cachexia was increased by 20% (hazard ratio = 1.200, 95% confidence interval = 1.132-1.273, P < 0.001). CONCLUSIONS: CAR is an effective representative of systemic inflammation and a powerful factor for predicting the life function and clinical outcome of patients with cancer cachexia.
AIMS: Systemic inflammation plays an important role in cancer cachexia. However, among the systemic inflammatory biomarkers, it is unclear which has optimal prognostic value for cancer cachexia. METHODS: The Kaplan-Meier method was used and the log-rank analysis was performed to estimate survival differences between groups. Cox proportional hazard regression analyses were conducted to assess independent risk factors for all-cause mortality. RESULTS: The C-reactive protein-to-albumin ratio (CAR) was the optimal prognostic assessment tool for patients with cancer cachexia, with 1-, 3-, and 5-year predictive powers of 0.650, 0.658, and 0.605, respectively. Patients with a high CAR had significantly lower survival rates than those with a low CAR. Moreover, CAR can differentiate the prognoses of patients with the same pathological stage. Cox proportional risk regression analyses showed that a high CAR was an independent risk factor for cancer cachexia. For every standard deviation increase in CAR, the risk of poor prognosis for patients with cancer cachexia was increased by 20% (hazard ratio = 1.200, 95% confidence interval = 1.132-1.273, P < 0.001). CONCLUSIONS: CAR is an effective representative of systemic inflammation and a powerful factor for predicting the life function and clinical outcome of patients with cancer cachexia.