World journal of gastroenterology · 2014
Criteria-specific long-term survival prediction model for hepatocellular carcinoma patients after liver transplantation.
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Teng Fei, Wang Gui-Hua, Tao Yi-Feng, Guo Wen-Yuan, Wang Zheng-Xin, Ding Guo-Shan, Shi Xiao-Min, Fu Zhi-Ren
Аннотация
AIM: To establish a model to predict long-term survival of hepatocellular carcinoma (HCC) patients after liver transplantation (MHCAT).
METHODS: Two hundred and twenty-three patients with HCC were followed for at least six years to identify independent risk factors for long-term survival after liver transplantation (LT). The criteria for HCC liver transplantation included the Milan, University of California San Francisco, Hangzhou and Shanghai Fudan criteria. The Cox regression model was used to build MHCAT specifying these criteria. A survival analysis was carried out for patients with high or low risk.
RESULTS: The one-, three- and five-year cumulative survival of HCC patients after LT was 78.9%, 53.2% and 46.4%, respectively. Of the HCC patients, the proportion meeting the Hangzhou and Fudan criteria was significantly higher than the proportion meeting the Milan criteria (64.6% vs 39.5%, 52.0% vs 39.5%, P < 0.05). Moreover, the proportion meeting the Hangzhou criteria was also significantly higher than the proportion meeting other criteria (P < 0.01). Pre-operative alfa-fetoprotein level, intraoperative blood loss and retransplantation were common significant predictors of long-term survival in HCC patients with reference to the Milan, University of California San Francisco and Fudan criteria, whereas in MHCAT based on the Hangzhou criteria, total bilirubin, intraoperative blood loss and retransplantation were independent predictors. The c-statistic for MHCAT was 0.773-0.824, with no statistical difference among these four criteria. According to the MHCAT scoring system, patients with low risk showed a higher five-year survival than those with high risk (P < 0.001).
CONCLUSION: MHCAT can effectively predict long-term survival for HCC patients, but needs to be verified by multi-center retrospective or randomized controlled trials.
METHODS: Two hundred and twenty-three patients with HCC were followed for at least six years to identify independent risk factors for long-term survival after liver transplantation (LT). The criteria for HCC liver transplantation included the Milan, University of California San Francisco, Hangzhou and Shanghai Fudan criteria. The Cox regression model was used to build MHCAT specifying these criteria. A survival analysis was carried out for patients with high or low risk.
RESULTS: The one-, three- and five-year cumulative survival of HCC patients after LT was 78.9%, 53.2% and 46.4%, respectively. Of the HCC patients, the proportion meeting the Hangzhou and Fudan criteria was significantly higher than the proportion meeting the Milan criteria (64.6% vs 39.5%, 52.0% vs 39.5%, P < 0.05). Moreover, the proportion meeting the Hangzhou criteria was also significantly higher than the proportion meeting other criteria (P < 0.01). Pre-operative alfa-fetoprotein level, intraoperative blood loss and retransplantation were common significant predictors of long-term survival in HCC patients with reference to the Milan, University of California San Francisco and Fudan criteria, whereas in MHCAT based on the Hangzhou criteria, total bilirubin, intraoperative blood loss and retransplantation were independent predictors. The c-statistic for MHCAT was 0.773-0.824, with no statistical difference among these four criteria. According to the MHCAT scoring system, patients with low risk showed a higher five-year survival than those with high risk (P < 0.001).
CONCLUSION: MHCAT can effectively predict long-term survival for HCC patients, but needs to be verified by multi-center retrospective or randomized controlled trials.
Предметные рубрики MeSH
AdultBlood Loss, SurgicalCarcinoma, HepatocellularDecision Support TechniquesFemaleHumansKaplan-Meier EstimateLiver NeoplasmsLiver TransplantationMaleMiddle AgedPredictive Value of TestsProportional Hazards ModelsRegistriesReoperationRisk AssessmentRisk FactorsTime FactorsTreatment Outcomealpha-Fetoproteins