Ioannou George N
Division of Gastroenterology, Department of Medicine, Hepatitis C Resource Center, Health Services Research and Development, Seattle, WA, USA.
Liver Transpl. 2006 Nov;12(11):1594-606. doi: 10.1002/lt.20764.
This study aimed to develop and validate a comprehensive model that predicts survival after liver transplantation based on pretransplant donor and recipient characteristics. Complete data were available from the United Network for Organ Sharing for 20,301 persons who underwent liver transplantation in the United States between 1994 and 2003. Proportional-hazards regression was used to identify the donor and recipient characteristics that best predicted survival and incorporate these characteristics in a multivariate model. A data-splitting approach was used to compare survival predicted by the model to the observed survival in samples not used in the derivation of the model. A model was derived using 4 donor characteristics (age, cold ischemia time, gender, and race/ethnicity) and 9 recipient characteristics (age, body max index, model for end-stage liver disease score, United Network for Organ Sharing priority status, gender, race/ethnicity, diabetes mellitus, cause of liver disease, and serum albumin) that adequately predicted survival after liver transplantation in patients without hepatitis C virus, and a slightly different model was used for patients with hepatitis C virus. The models illustrate that variations in both pretransplant donor and recipient characteristics have a large effect on posttransplant survival. In conclusion, the models presented here can be used to derive scores that are proportional to the excess risk of graft loss after liver transplantation for potential donors, recipients, or donor/recipient combinations. The models may be used to inform liver transplant candidates and their doctors what posttransplant survival would be expected when a given donor is offered and may be particularly helpful for marginal or high-risk donors.
本研究旨在开发并验证一个综合模型，该模型可根据移植前供体和受体的特征预测肝移植后的生存率。完整数据来自器官共享联合网络，涉及1994年至2003年间在美国接受肝移植的20301人。采用比例风险回归来确定最能预测生存率的供体和受体特征，并将这些特征纳入多变量模型。使用数据拆分方法将模型预测的生存率与未用于模型推导的样本中的观察生存率进行比较。使用4个供体特征（年龄、冷缺血时间、性别和种族/民族）和9个受体特征（年龄、身体质量指数、终末期肝病模型评分、器官共享联合网络优先状态、性别、种族/民族、糖尿病、肝病病因和血清白蛋白）推导了一个模型，该模型能充分预测无丙型肝炎病毒患者肝移植后的生存率，对于丙型肝炎病毒患者则使用了稍有不同的模型。这些模型表明，移植前供体和受体特征的差异对移植后生存率有很大影响。总之，这里提出的模型可用于得出与肝移植后潜在供体、受体或供体/受体组合的移植物丢失额外风险成比例的分数。这些模型可用于告知肝移植候选者及其医生，当提供特定供体时预期的移植后生存率，对边缘或高风险供体可能特别有帮助。
