Prognostic stratification and nomogram for survival prediction in hepatocellular carcinoma patients treated with radiotherapy for lymph node metastasis

Chan Woo Wee, Kyubo Kim, Eui Kyu Chie, Su Jong Yu, Yoon Jun Kim, Jung Hwan Yoon

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Objective: To establish a prognostic model for overall survival prediction in patients with hepatocellular carcinoma (HCC) treated with external beam radiotherapy (RT) for lymph node (LN) metastasis. Methods: 105 patients with HCC underwent RT for LN metastasis. The median age, biologically effective RT dose and follow-up period were 60 years, 59Gy10 and 5.7 months, respectively. 51 patients had symptoms related to LN metastasis. Results: The median survival (MS) was 5.8 months for all patients. For patients with LN-related symptoms, MS was 3.8 months compared with 10.7 months for those without LN-related symptoms. On multivariate analysis of pre-RT factors, symptoms related to LN metastasis [hazard ratio (HR) 2.93], Child-Pugh Class B-C (HR 2.77), uncontrolled intrahepatic disease (HR 2.74) and non-nodal distant metastasis (HR 1.62) were significantly poor prognostic factors for survival (all p<0.05). Prognostic grouping into three groups by the number of risk factors also had a significant predictive value for survival, with patients having 0, 1, 2 and 3-4 risk factors demonstrating MS of 18.0, 11.7, 5.7 and 3.0 months, respectively (p<0.001). A clinical nomogram based on the four prognostic factors was formulated and demonstrated good accuracy for predicting 6-month survival with a concordance index of 0.77. Conclusion: In a heterogeneous group of patients with HCC treated with RT for LN metastasis, the presence of LN-related symptoms was highly associated with poor survival. The prognostic grouping and nomogram developed by the present study can be effectively used for the prediction of survival. Advances in knowledge: Patients treated with RT for LN metastases harbour various clinical features. Prognostic model and nomogram can help in predicting survival in these patients.

Original languageEnglish
Article number20160383
JournalBritish Journal of Radiology
Volume89
Issue number1065
DOIs
StatePublished - 2016

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