Prognostic value of low skeletal muscle mass in hepatocellular carcinoma patients treated with sorafenib or lenvatinib: A meta-analysis
DOI:
https://doi.org/10.17179/excli2020-3111Keywords:
low skeletal muscle mass, sorafenib, lenvatinib, hepatocellular carcinoma, prognosisAbstract
Growing evidence indicates that skeletal muscle depletion has a notable effect on the prognosis of hepatocellular carcinoma (HCC) patients, though study results are still controversial. Our meta-analysis aimed at evaluating the prognostic significance of low skeletal muscle mass (LSMM) in HCC patients treated with sorafenib or lenvatinib.We systematically reviewed for PubMed, Cochrane, and Embase databases from their inception to August 2020 and obtained all relevant articles describing an association between LSMM and HCC patients treated with sorafenib or lenvatinib. Demographic and characteristics of included studies, diagnostic criteria of skeletal muscle depletion, and main outcomes (overall survival, progression-free survival, time to treatment failure) were retrieved. Associations were expressed by calculating hazard ratios (HRs) and 95 % confidence intervals (CIs).The meta-analysis enrolled 11 studies comprising 1148 patients. Without significant heterogeneity between studies, LSMM was significantly associated with poor overall survival (crude HR=1.58, 95 % CI: 1.36–1.83; adjusted HR=1.83, 95 % CI: 1.46–2.29) and time to treatment failure (crude HR=1.85, 95 % CI: 1.34–2.54; adjusted HR=1.72, 95 % CI: 1.24–2.38). However, there was no significantly association between LSMM and progression-free survival (adjusted HR=1.44, 95 % CI: 0.95–2.20). Symmetry of distribution on the funnel plot did not show significant publication bias.This meta-analysis supported that LSMM is significantly associated with poor overall survival and time to treatment failure in HCC patients after sorafenib or lenvatinib administration. This negative effect was pronounced even after adjustment for confounders. Future studies should be carried out on larger samples and study regions based on standardized thresholds of LSMM.
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Copyright (c) 2021 Jun Guan, Qin Yang, Chao Chen, Gang Wang, Haihong Zhu
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