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Background: Small-for-size grafts (SFSGs) in living donor liver transplantation (LDLT) could optimize donor postoperative outcomes and also expand the potential donor pool. Evidence on whether SFSGs would affect medium-term and long-term recipient graft survival is lacking., Aim: To evaluate the impact of small-for-size liver grafts on medium-term and long-term graft survival in adult to adult LDLT., Methods: A systematic review and meta-analysis were performed by searching eligible studies published before January 24, 2019 on PubMed, EMBASE, and Web of Science databases. The primary outcomes were 3-year and 5-year graft survival. Incidence of small-for-size syndrome and short term mortality were also extracted., Results: This meta-analysis is reported according to the guidelines of the PRISMA 2009 Statement. Seven retrospective observational studies with a total of 1821 LDLT recipients were included in the meta-analysis. SFSG is associated with significantly poorer medium-term graft survival. The pooled odds ratio for 3-year graft survival was 1.58 [95% confidence interval 1.10-2.29, P = 0.014]. On the other hand, pooled results of the studies showed that SFSG had no significant discriminatory effect on 5-year graft survival with an odds ratio of 1.31 (95% confidence interval 0.87-1.97, P = 0.199). Furthermore, incidence of small-for-size syndrome detected in recipients of SFSG ranged from 0-11.4% in the included studies., Conclusion: SFSG is associated with inferior medium-term but not long-term graft survival. Comparable long-term graft survival based on liver graft size shows that smaller grafts could be accepted for LDLT with appropriate flow modulatory measures. Close follow-up for graft function is warranted within 3 years after liver transplantation., Competing Interests: Conflict-of-interest statement: The authors deny any conflict of interest., (©The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved.)

Background: Liver transplantation (LT) is regarded as the best treatment for both primary and recurrent hepatocellular carcinoma (HCC). Post-transplant HCC recurrence rate is relatively low but significant, ranging from 10%-30% according to different series. When recurrence happens, it is usually extrahepatic and associated with poor prognosis. A predictive model that allows patient stratification according to recurrence risk can help to individualize post-transplant surveillance protocol and guidance of the use of anti-tumor immunosuppressive agents., Aim: To develop a scoring system to predict HCC recurrence after LT in an Asian population., Methods: Consecutive patients having LT for HCC from 1995 to 2016 at our hospital were recruited. They were randomized into the training set and the validation set in a 60:40 ratio. Multivariable Cox regression model was used to identity factors associated with HCC recurrence. A risk score was assigned to each factor according to the odds ratio. Accuracy of the score was assessed by the area under the receiver operating characteristic curve., Results: In total, 330 patients were eligible for analysis (183 in training and 147 in validation). Recurrent HCC developed in 14.2% of them. The median follow-up duration was 65.6 mo. The 5-year disease-free and overall survival rates were 78% and 80%, respectively. On multivariate analysis, alpha-fetoprotein > 400 ng/mL [ P = 0.012, hazard ratio (HR) 2.92], sum of maximum tumor size and number ( P = 0.013, HR 1.15), and salvage LT ( P = 0.033, HR 2.08) were found to be independent factors for disease-free survival. A risk score was calculated for each patient with good discriminatory power (c-stat 0.748 and 0.85, respectively, in the training and validation sets). With the derived scores, patients were classified into low- (0-9), moderate- (> 9-14), and high-risk groups (> 14), and the risk of HCC recurrence in the training and validation sets was 10%, 20%, 54% (c-stat 0.67) and 4%, 22%, 62% (c-stat 0.811), accordingly. The risk stratification model was validated with chi-squared goodness-of-fit test ( P = 0.425)., Conclusion: A validated predictive model featuring alpha-fetoprotein, salvage LT, and the sum of largest tumor diameter and total number of tumor nodule provides simple and reliable guidance for individualizing postoperative surveillance strategy., Competing Interests: Conflict-of-interest statement: None of the authors has any conflict of interest.