4.7 Article

Long-Term Survival Outcome Between Living Donor and Deceased Donor Liver Transplant for Hepatocellular Carcinoma: Intention-to-Treat and Propensity Score Matching Analyses

Journal

ANNALS OF SURGICAL ONCOLOGY
Volume 26, Issue 5, Pages 1454-1462

Publisher

SPRINGER
DOI: 10.1245/s10434-019-07206-0

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Background. Previous studies comparing outcomes of hepatocellular carcinoma (HCC) patients after living donor liver transplantation (LDLT) and deceased donor liver transplantation (DDLT) showed conflicting results, and most studies measured survival outcomes from the time of liver transplantation (LT). Method. This retrospective study was aimed to evaluate the long-term outcomes of HCC patients listed for LT using intention-to-treat (ITT) and propensity score matching (PSM) analyses. Clinicopathological data were retrieved from a prospectively collected database. Results. From 1995 to 2014, 375 HCC patients were listed for LT. ITT-LDLT group had 188 patients, whereas ITT-DDLT group had 187 patients. Twenty-seven patients (14.4%) and 122 patients (65.2%) were delisted from LDLT and DDLT waitlist, respectively. The 1-, 3- and 5-year overall survival rates were significantly better in ITT-LDLT group than ITT-DDLT group (94.1 vs. 77.5%, 81.4 vs. 48.7% and 75.9 vs. 40.8%). High alphafetoprotein (AFP) and ITT-DDLT treatment arm were independent poor prognostic factors affecting overall survival. LDLT group (n = 161) had more young patients, poorer liver function, higher AFP, more tumors outside Milan/UCSF criteria, when compared with DDLT group (n = 85). After PSM, the 1-, 3- and 5-year overall (95.4 vs. 98.5%, 80.0 vs. 92.3% and 73.4 vs. 84.4%) and recurrence-free (87.7% vs. 90.8%, 76.9% vs. 83.1% and 72.2% vs. 81.5%) survival rates were comparable between the matched LDLT and the matched DDLT group, respectively. Conclusion. Survival benefit of LDLT was observed for HCC patients with ITT analysis. Despite a more advanced tumor stage, overall and recurrence-free survival rates were comparable between LDLT and DDLT using PSM analysis.

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