Jiarui Yang1, Shuguang Zhu2, Juanjuan Yong3, Long Xia2, Xiangjun Qian1, Jiawei Yang1, Xueqiao Hu1, Yuxuan Li1, Chusi Wang1,4, Wenguang Peng1, Lei Zhang1, Meihai Deng4, Weidong Pan1. 1. Department of Biliary-Pancreatic Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China. 2. Department of Hepatic Surgery and Liver Transplantation Center, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China. 3. Department of Pathology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China. 4. Department of Hepatobiliary Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Abstract
BACKGROUND: Microvascular invasion (MVI) is highly associated with poor prognosis in patients with liver cancer. Predicting MVI before surgery is helpful for surgeons to better make surgical plan. In this study, we aim at establishing a nomogram to preoperatively predict the occurrence of microvascular invasion in liver cancer. METHOD: A total of 405 patients with postoperative pathological reports who underwent curative hepatocellular carcinoma resection in the Third Affiliated Hospital of Sun Yat-sen University from 2013 to 2015 were collected in this study. Among these patients, 290 were randomly assigned to the development group while others were assigned to the validation group. The MVI predictive factors were selected by Lasso regression analysis. Nomogram was established to preoperatively predict the MVI risk in HCC based on these predictive factors. The discrimination, calibration, and effectiveness of nomogram were evaluated by internal validation. RESULTS: Lasso regression analysis revealed that discomfort of right upper abdomen, vascular invasion, lymph node metastases, unclear tumor boundary, tumor necrosis, tumor size, higher alkaline phosphatase were predictive MVI factors in HCC. The nomogram was established with the value of AUROC 0.757 (0.716-0.809) and 0.768 (0.703-0.814) in the development and the validation groups. Well-fitted calibration was in both development and validation groups. Decision curve analysis confirmed that the predictive model provided more benefit than treat all or none patients. The predictive model demonstrated sensitivity of 58.7%, specificity of 80.7% at the cut-off value of 0.312. CONCLUSION: Nomogram was established for predicting preoperative risk of MVI in HCC. Better treatment plans can be formulated according to the predicted results.
BACKGROUND: Microvascular invasion (MVI) is highly associated with poor prognosis in patients with liver cancer. Predicting MVI before surgery is helpful for surgeons to better make surgical plan. In this study, we aim at establishing a nomogram to preoperatively predict the occurrence of microvascular invasion in liver cancer. METHOD: A total of 405 patients with postoperative pathological reports who underwent curative hepatocellular carcinoma resection in the Third Affiliated Hospital of Sun Yat-sen University from 2013 to 2015 were collected in this study. Among these patients, 290 were randomly assigned to the development group while others were assigned to the validation group. The MVI predictive factors were selected by Lasso regression analysis. Nomogram was established to preoperatively predict the MVI risk in HCC based on these predictive factors. The discrimination, calibration, and effectiveness of nomogram were evaluated by internal validation. RESULTS: Lasso regression analysis revealed that discomfort of right upper abdomen, vascular invasion, lymph node metastases, unclear tumor boundary, tumor necrosis, tumor size, higher alkaline phosphatase were predictive MVI factors in HCC. The nomogram was established with the value of AUROC 0.757 (0.716-0.809) and 0.768 (0.703-0.814) in the development and the validation groups. Well-fitted calibration was in both development and validation groups. Decision curve analysis confirmed that the predictive model provided more benefit than treat all or none patients. The predictive model demonstrated sensitivity of 58.7%, specificity of 80.7% at the cut-off value of 0.312. CONCLUSION: Nomogram was established for predicting preoperative risk of MVI in HCC. Better treatment plans can be formulated according to the predicted results.
Authors: Beom Kyung Kim; Kwang Hyub Han; Young Nyun Park; Mi Suk Park; Kyung Sik Kim; Jin Sub Choi; Byung Soo Moon; Chae Yoon Chon; Young Myoung Moon; Sang Hoon Ahn Journal: J Surg Oncol Date: 2008-03-01 Impact factor: 3.454
Authors: Sasan Roayaie; Iris N Blume; Swan N Thung; Maria Guido; Maria-Isabel Fiel; Spiros Hiotis; Daniel M Labow; Josep M Llovet; Myron E Schwartz Journal: Gastroenterology Date: 2009-06-12 Impact factor: 22.682