Lihua Yu1, Xiaoli Liu1, Xinhui Wang1, Dongdong Zhou1, Huiwen Yan1, Yuqing Xie2, Qing Pu1, Ke Zhang3, Zhiyun Yang4. 1. Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, P.R. China. 2. Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, P.R. China; First Clinical Medical College, Beijing University of Chinese Medicine, Beijing 100029, P.R. China. 3. Department of Hepatobiliary Surgery, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, P.R. China. 4. Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, P.R. China. Electronic address: yangzhiyun2016@163.com.
Abstract
INTRODUCTION: Among all immune cells, natural killer (NK) cells play an important role as the first line of defense against tumor. The purpose of our study is to observe whether the NK cell counts can predict the overall survival of patients with hepatocellular carcinoma (HCC). METHODS: To develop a novel model, from January 2010 to June 2015, HCC patients enrolled in Beijing Ditan hospital were divided into training and validation cohort. Cox multiple regression analysis was used to analyze the independent risk factors for 1-year, 3-year and 5-year overall survival (OS) of patients with HCC, and the nomogram was used to establish the prediction model. In addition, the decision tree was established to verify the contribution of NK cell counts to the survival of patients with HCC. RESULTS: The model used in predicting overall survival of HCC included six variables (namely, NK cell counts, albumin (ALB) level, alpha-fetoprotein (AFP) level, portal vein tumor thrombus (PVTT), tumor number and treatment). The C-index of nomogram model in HCC patients predicting 1-year, 3-year and 5-year overall survival was 0.858, 0.788 and 0.782 respectively, which was higher than tumor-lymph node-metastasis (TNM) staging system, Okuda, model for end-stage liver disease (MELD), MELD-Na, the Chinese University Prognostic Index (CUPI) and Japan Integrated Staging (JIS) scores (p < 0.001). The decision tree showed the specific 5-year OS probability of HCC patients under different risk factors, and found that NK cell counts were the third in the column contribution. CONCLUSIONS: Our study emphasizes the utility of NK cell counts for exploring interactions between long-term survival of HCC patients and predictor variables.
INTRODUCTION: Among all immune cells, natural killer (NK) cells play an important role as the first line of defense against tumor. The purpose of our study is to observe whether the NK cell counts can predict the overall survival of patients with hepatocellular carcinoma (HCC). METHODS: To develop a novel model, from January 2010 to June 2015, HCC patients enrolled in Beijing Ditan hospital were divided into training and validation cohort. Cox multiple regression analysis was used to analyze the independent risk factors for 1-year, 3-year and 5-year overall survival (OS) of patients with HCC, and the nomogram was used to establish the prediction model. In addition, the decision tree was established to verify the contribution of NK cell counts to the survival of patients with HCC. RESULTS: The model used in predicting overall survival of HCC included six variables (namely, NK cell counts, albumin (ALB) level, alpha-fetoprotein (AFP) level, portal vein tumor thrombus (PVTT), tumor number and treatment). The C-index of nomogram model in HCC patients predicting 1-year, 3-year and 5-year overall survival was 0.858, 0.788 and 0.782 respectively, which was higher than tumor-lymph node-metastasis (TNM) staging system, Okuda, model for end-stage liver disease (MELD), MELD-Na, the Chinese University Prognostic Index (CUPI) and Japan Integrated Staging (JIS) scores (p < 0.001). The decision tree showed the specific 5-year OS probability of HCC patients under different risk factors, and found that NK cell counts were the third in the column contribution. CONCLUSIONS: Our study emphasizes the utility of NK cell counts for exploring interactions between long-term survival of HCC patients and predictor variables.