Literature DB >> 30637484

Validated nomogram for the prediction of disease-free survival after hepatectomy for hepatocellular carcinoma within the Milan criteria: individualizing a surveillance strategy.

Ka Wing Ma1, Wong Hoi She1, Tan To Cheung1, Albert Chi Yan Chan1, Wing Chiu Dai1, James Yan Yue Fung2, Chung Mau Lo1, Kenneth Siu Ho Chok3.   

Abstract

OBJECTIVE: We sought to develop a nomogram for the prediction of tumor recurrence after resection of hepatocellular carcinoma (HCC) within the Milan criteria.
METHOD: Consecutive HCC patients admitted for hepatectomy between 1994 and 2014 were enrolled in this study. Patients were excluded if they had recurrent HCC or tumors beyond the Milan criteria. Patients were randomized and assigned to the derivation and validation sets in a 1:1 ratio. Independent factors for disease-free survival were identified using the Cox regression model. A nomogram was derived and validated with the receiver-operating characteristic (ROC) and calibration curves.
RESULTS: There were 617 eligible patients included in the analysis. The median age was 59 years, 481 were male, and 87.8% of the patients were hepatitis B virus carriers. The median follow-up was 68.7 months. The 5-year overall survival rate was 73.3% and HCC recurrence was detected in 55% of the patients. In the derivation set, a nomogram was constructed based on the seven independent factors for disease-free survival: age, alpha-fetoprotein, preoperative prothrombin time, magnitude of hepatectomy, postoperative complication, number of tumor nodules, and presence of microvascular invasion. A satisfactory discrimination ability was observed in both the derivation and validation sets (c-stat 0.672 and 0.665, respectively). The calibration plot yielded agreement between the predicted and observed outcomes, using the derived nomogram.
CONCLUSION: A validated nomogram quantifies the risk of recurrence after hepatectomy for HCC within the Milan criteria, and assists with the planning of individual postoperative surveillance protocols.

Entities:  

Keywords:  Hepatocellullar carconoma; Nomogram; Prediction; Recurrence

Mesh:

Year:  2019        PMID: 30637484     DOI: 10.1007/s00595-019-1764-x

Source DB:  PubMed          Journal:  Surg Today        ISSN: 0941-1291            Impact factor:   2.549


  5 in total

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Authors:  Xiao-Hui Wang; Bing Liao; Wen-Jie Hu; Cai-Xue Tu; Cai-Ling Xiang; Sheng-Hua Hao; Xian-Hai Mao; Xiao-Ming Qiu; Xiao-Jun Yang; Xiao Yue; Ming Kuang; Bao-Gang Peng; Shao-Qiang Li
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3.  15-lncRNA-Based Classifier-Clinicopathologic Nomogram Improves the Prediction of Recurrence in Patients with Hepatocellular Carcinoma.

Authors:  Qiong Zhang; Gang Ning; Hongye Jiang; Yanlin Huang; Jinsong Piao; Zhen Chen; Xiaojun Tan; Jiangyu Zhang; Genglong Liu
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4.  A Novel Nomogram to Predict Prolonged Survival After Hepatectomy in Repeat Recurrent Hepatocellular Carcinoma.

Authors:  Qiongxuan Fang; Ruifeng Yang; Dongbo Chen; Ran Fei; Pu Chen; Kangjian Deng; Jie Gao; Weijia Liao; Hongsong Chen
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5.  Establishment of a prognostic model for predicting short-term disease-free survival in cases of hepatitis B-related hepatocellular carcinoma with the TP53 249Ser mutation in southern China.

Authors:  Wei Qin; Chuangye Han; Rongyun Mai; Tingdong Yu; Liming Shang; Xinping Ye; Guangzhi Zhu; Hao Su; Xiwen Liao; Zhengtao Liu; Long Yu; Xiaoguang Liu; Chengkun Yang; Xiangkun Wang; Minhao Peng; Tao Peng
Journal:  Transl Cancer Res       Date:  2020-08       Impact factor: 1.241

  5 in total

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