Dingan Luo1, Haoran Li1, Heng Yu2, Mao Zhang1, Jianchong Hu1, Cheng Jin2, Meisze Chua3, Bing Han1. 1. Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hospital of Qingdao University, Qingdao, China. 2. Department of Radiation Oncology, Stanford Medical School, Stanford University, Stanford, California. 3. Department of Surgery, Asian Liver Center, Stanford University School of Medicine, Stanford, California.
Abstract
BACKGROUND: Inflammation plays an important role in the progression and prognosis of hepatocellular carcinoma (HCC). Our aim is to explore the prognostic value of preoperative and postoperative peripheral lymphocyte differences and to develop a dynamic prognosis nomogram in hepatitis B virus-related HCC patients. METHODS: Important indicators related to overall survival (OS) are screened out by Cox proportional hazard models. The receiver operating characteristic curves, decision curve analysis curves, net reclassification improvement, and integrated discrimination improvement were used to evaluate the performance of the model. RESULTS: Lymphocyte (L) difference was an independent risk factor. It was further verified that the performance of the nomogram was significantly improved after the L difference was incorporated into the nomogram. The nomogram generated had the area under curves of 0.779, 0.775, and 0.793 at 3, 5, and 7 years after surgery, respectively. Our nomogram models showed significantly better performance in predicting the HCC prognosis compared to other models. And online webserver and scoring system table was built based on the proposed nomogram for convenient clinical use. CONCLUSIONS: It is newly found that L difference is an effective predictor of OS, and the nomogram based on this indicator can accurately predict the prognosis of HCC patients.
BACKGROUND:Inflammation plays an important role in the progression and prognosis of hepatocellular carcinoma (HCC). Our aim is to explore the prognostic value of preoperative and postoperative peripheral lymphocyte differences and to develop a dynamic prognosis nomogram in hepatitis B virus-related HCC patients. METHODS: Important indicators related to overall survival (OS) are screened out by Cox proportional hazard models. The receiver operating characteristic curves, decision curve analysis curves, net reclassification improvement, and integrated discrimination improvement were used to evaluate the performance of the model. RESULTS: Lymphocyte (L) difference was an independent risk factor. It was further verified that the performance of the nomogram was significantly improved after the L difference was incorporated into the nomogram. The nomogram generated had the area under curves of 0.779, 0.775, and 0.793 at 3, 5, and 7 years after surgery, respectively. Our nomogram models showed significantly better performance in predicting the HCC prognosis compared to other models. And online webserver and scoring system table was built based on the proposed nomogram for convenient clinical use. CONCLUSIONS: It is newly found that L difference is an effective predictor of OS, and the nomogram based on this indicator can accurately predict the prognosis of HCC patients.