BACKGROUND: Advanced hepatocellular carcinoma (HCC) patients who are not candidates for surgery or locoregional therapy are the focus of clinical trials of systemic therapy, as their overall prognosis remains poor. However, the current prognostic systems cannot reliably select appropriate candidates for systemic therapy trials based on the probability of 3-month survival. In this study, the authors constructed a new prognostic score system, the Advanced Liver Cancer Prognostic System (ALCPS), which can objectively predict the probability of 3-month survival. METHODS: Between 1990 and 2005, 1470 patients with advanced HCC who were not amendable to surgery or locoregional therapy were included in the analysis. The prognostic score system was developed from the multivariate Cox model through a point system and validated in an independent set. Okuda staging and Cancer of the Liver Italian Program (CLIP) score were also applied to the validation set to compare their predictive accuracy. RESULTS: The ALCPS was based on 11 prognostic factors with different weights: ascites, abdominal pain, weight loss, Child-Pugh grade, alkaline phosphatase, total bilirubin, alpha-fetal protein, urea, portal vein thrombosis, tumor size, and presence of lung metastases. It stratified patients in both training and validation sets to different prognostic groups with significant difference in 3-month overall survival (P < .0001). By using the patients in the validation set with known 3-month survival status, the ALCPS showed significantly better predictive power (area under the curve [AUC], 0.77) than Okuda score (AUC, 0.66; P < .001) and CLIP score (AUC, 0.71; P = .002). CONCLUSIONS: The new prognostic system can objectively help the clinicians to select appropriate candidates for evaluation of treatment efficacy in systemic therapy trials for advanced HCC.
BACKGROUND: Advanced hepatocellular carcinoma (HCC) patients who are not candidates for surgery or locoregional therapy are the focus of clinical trials of systemic therapy, as their overall prognosis remains poor. However, the current prognostic systems cannot reliably select appropriate candidates for systemic therapy trials based on the probability of 3-month survival. In this study, the authors constructed a new prognostic score system, the Advanced Liver Cancer Prognostic System (ALCPS), which can objectively predict the probability of 3-month survival. METHODS: Between 1990 and 2005, 1470 patients with advanced HCC who were not amendable to surgery or locoregional therapy were included in the analysis. The prognostic score system was developed from the multivariate Cox model through a point system and validated in an independent set. Okuda staging and Cancer of the Liver Italian Program (CLIP) score were also applied to the validation set to compare their predictive accuracy. RESULTS: The ALCPS was based on 11 prognostic factors with different weights: ascites, abdominal pain, weight loss, Child-Pugh grade, alkaline phosphatase, total bilirubin, alpha-fetal protein, urea, portal vein thrombosis, tumor size, and presence of lung metastases. It stratified patients in both training and validation sets to different prognostic groups with significant difference in 3-month overall survival (P < .0001). By using the patients in the validation set with known 3-month survival status, the ALCPS showed significantly better predictive power (area under the curve [AUC], 0.77) than Okuda score (AUC, 0.66; P < .001) and CLIP score (AUC, 0.71; P = .002). CONCLUSIONS: The new prognostic system can objectively help the clinicians to select appropriate candidates for evaluation of treatment efficacy in systemic therapy trials for advanced HCC.
Authors: Xavier Adhoute; Guillaume Penaranda; Jean Luc Raoul; Patrice Le Treut; Emilie Bollon; Jean Hardwigsen; Paul Castellani; Hervé Perrier; Marc Bourlière Journal: World J Hepatol Date: 2016-06-18
Authors: Ke Hao; John M Luk; Nikki P Y Lee; Mao Mao; Chunsheng Zhang; Mark D Ferguson; John Lamb; Hongyue Dai; Irene O Ng; Pak C Sham; Ronnie T P Poon Journal: BMC Cancer Date: 2009-11-03 Impact factor: 4.430