Impact of baseline characteristics on outcomes of advanced HCC patients treated with sorafenib: a secondary analysis of a phase III study.

Clinical Oncology Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt. omar.abdelrhman@med.asu.edu.eg.

Journal of cancer research and clinical oncology. 2018;(5):901-908
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Abstract

BACKGROUND The current study aims to investigate the impact of baseline characteristics on the outcomes of sorafenib-treated advanced Hepatocellular carcinoma (HCC) patients in the setting of a clinical trial. METHODS This is a secondary analysis of the comparator arm (sorafenib arm) of the NCT00699374 study which is a phase III multicenter study conducted between 2008 and 2010. The univariate probability of overall and progression-free survival was assessed among different patient subsets through Kaplan-Meier analysis and log-rank testing. Multivariate analysis of factors affecting overall and progression-free survival was then conducted through Cox regression analysis. RESULTS All patients within the comparator (sorafenib) arm were included in the analysis (N = 544 patients). In multivariate analysis, prior hepatectomy (P = 0.028), prior locoregional treatment (P = 0.048), grade 1 ALBI score (P < 0.001), ECOG performance score of 0 (P < 0.001), BMI ≥ 25 (P = 0.026), AFP < 200 (P = 0.001), and no extra-hepatic spread (P = 0.007) were associated with better overall survival. Likewise, in multivariate analysis, non-Asian race (P = 0.004), grade 1 ALBI score (P = 0.001), ECOG performance score of 0 (P = 0.006), and no extra-hepatic spread (P = 0.005) were associated with better progression-free survival. Moreover, development of high-grade hand-foot skin reaction was associated with a statistically significant improvement in overall survival (P = 0.003), which was further confirmed in a multivariate analysis adjusted for other relevant baseline factors (P = 0.002). CONCLUSION Within a cohort of highly selected advanced HCC patients, baseline patient-, liver-, and disease-centered variables play an important role in predicting patient outcomes. This information is important in terms of therapeutic decision-making and patient counseling.

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MeSH terms : Phenylurea Compounds