Posttransplant mortality risk assessment for adult-to-adult right-lobe living donor liver recipients with benign end-stage liver disease

Abstract

Objective. A model for living donor liver transplantation (LDLT) outcomes, in concert with pretransplant disease severity assessment, would facilitate informed decision-making on both sides considering donation and transplantation. So far, however, few of studies have focused on models specifically for adult-to-adult right-lobe LDLT recipients with benign end-stage liver diseases. Therefore, we aimed to develop such a prognostic model based on easily obtainable and objective pretransplant characteristics. Methods. With data retrospectively collected on 120 recipients, we used Cox proportional-hazards regression to analyze six donor characteristics and 33 pretransplant recipient variables for correlation with posttransplant mortality. In both a modeling set and a prospective validation set with 30 recipients, the performances of the new Cox model, MELD, and MELD-Na⁺ were assessed by measuring both calibration ability and discriminative power with the Hosmer–Lemeshow test and receiver operating characteristic analysis, respectively. Results. By univariate and multivariate analysis, donor age, serum total bilirubin, creatinine, and HBV-DNA level were significantly associated with posttransplant mortality. The Cox model, employing these four variables, yielded good calibration ability in the modeling set χ ² = 2.465, p = 0.653) and the validation set χ ² = 2.836, p = 0.586), and high discriminative power in the modeling set (c-statistic = 0.826, p = 0.001) and validation set (c-statistic = 0.816, p = 0.028). The calibration ability and discriminative power of MELD and MELD-Na⁺ in both sets were poor. Conclusions. The newly derived Cox model was valuable in posttransplant mortality risk assessment for adult-to-adult right-lobe LDLT recipients with benign end-stage liver diseases.

Key Words::

• hepatitis B virus
• living donor liver transplantation
• model for end-stage liver disease
• prognostic model

Acknowledgments

This work was supported by grants from the National Basic Research Program of China (also called the 973 Program) (No. 2009CB522401), the Ph.D. Programs Foundation of Ministry of Education of China (No. 20110181120037), and the China Postdoctoral Science Foundation (No. 20090461343). The authors thank Shawna Williams for her editing assistance in the preparation of this manuscript.

Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.