Competing risk model for prognostic comparison between clear cell type and common type hepatocellular carcinoma: A population‐based propensity score matching study

Author:

Zhong Xiao1,Hu Xingwang1,Fan Xue‐Gong1ORCID

Affiliation:

1. Department of Infectious Diseases, Hunan Key Laboratory of Viral Hepatitis, Xiangya Hospital Central South University Changsha China

Abstract

AbstractBackgroundClear cell type hepatocellular carcinoma (HCC) is an uncommon neoplasm with an ambivalent prognosis compared to common type HCC.MethodsFirst, patients with clear cell or common type HCC were enrolled from the Surveillance, Epidemiology, and End Results (SEER) database, and their demographic and clinical characteristics were identified. Next, overall survival (OS), disease‐specific survival (DSS), and subgroup analysis of the two types of HCC were performed. Next, we utilized a competing risk model to focus on cancer‐caused death. Finally, propensity score matching (PSM) was employed to reduce the confounding factors based on the histopathological type, and sensitivity analysis was conducted.ResultsA total of 205 cases of clear cell type HCC and 29,954 cases of common type HCC were enrolled in our study. Patients with clear cell type HCC were older and predominantly female than those with common type HCC. OS and DSS were not significantly different between the two groups, and histopathological type was not a prognostic factor of HCC, as verified by the competing risk model. Patient characteristics adjusted by PSM and sensitivity analysis confirmed this conclusion. In subgroup analysis, patients with clear cell type HCC at grade III ~ IV and with lymph nodes metastasis had a better prognosis compared to common type HCC.ConclusionsThis study revealed that the prognosis of clear cell type HCC is similar to common type HCC. Tumor differentiation grade and status of lymph node metastasis affect the prognosis of HCC.

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Cancer Research,Radiology, Nuclear Medicine and imaging,Oncology

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