Development and Validation of a Nomogram for Predicting Incidence of Early Allograft Dysfunction Following Liver Transplantation
Development and Validation of a Nomogram for Predicting Incidence of Early Allograft Dysfunction Following Liver Transplantation
复制标题
预测肝移植后早期同种异体移植物功能障碍发生率的列线图的开发和验证
DOI：
10.1016/j.transproceed.2017.03.083
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发表时间：
2017-07-01
影响因子：
0.9
通讯作者：
He, X. S.
中科院分区：
文献类型：
--
作者：
Yang, L.;Xin, E. Y.;He, X. S.
目标。早期同种异体移植功能障碍（EAD）是肝移植术后常见的并发症，与受体的死亡率和发病率密切相关。我们试图建立一个预测ead发病率的nomogram。基于2013年至2015年199例已故供体肝移植的供体、受体和手术数据的多变量分析，我们确定了FAD的5个显著危险因素并建立了nomogram。该模型在2016年1月至6月期间招募的42名患者中进行了前瞻性验证。用受试者工作特征曲线下面积（AUC）测定预测准确度和判别能力。标定曲线显示了nomogram预测值与实际观测值的一致性。训练组和验证组的EAD发病率分别为55.91%（104/199）和54.76%（23/42）。在训练集中，根据单变量和多变量分析结果，识别供者性别、供者血清γ -谷氨酰转肽酶水平、供者血清尿素水平、供者合并症（呼吸、心脏、肾功能不全）、终末期肝病受体模型评分等5个独立危险因素，并将其组装成nomogram。采用自举重新抽样的内部验证和采用42例外部队列的前瞻性验证的AUC分别为0.74和0.60。图预测结果与实际观测结果吻合较好。从计分表中可以看出，当总分低于72分时，出现BAD的概率在30%以下。但当总数达到139时，EAD的风险增加到60%。我们已经建立并验证了一个nomogram，可以为肝移植受者提供个体化的EAD预测。实用的预后模型可以帮助临床医生准确地确定肝移植，使器官分配更加合理。
Objective. Early allograft dysfunction (EAD) is frequent complication post-liver transplantation and is closely related to recipient's mortality and morbidity. We sought to develop a nomogram for predicting incidence of EAD.Methods. Based on multivariate analysis of donor, recipient, and operation data of 199 liver transplants from deceased donors between 2013 and 2015, we identified 5 significant risk factors for FAD to build a nomogram. The model was subjected to prospective validation with a cohort of 42 patients who was recruited between January and June 2016. The predictive accuracy and discriminative ability were measured by area under the receiver operating characteristic curve (AUC). The agreement between nomogram prediction and actual observation was showed by the calibration curve.Results. Incidence rate of EAD in the training set and validation cohort were 55.91% (104/199) and 54.76% (23/42), respectively. In the training set, according to the results of univariable and multivariable analysis, 5 independent risk factors including donor gender, donor serum gamma-glutamyl transpeptidase level, donor serum urea level, donor comorbidities (respiratory, cardiac, and renal dysfunction), and recipient Model for End-stage Liver Disease score were identified and assembled into the nomogram. The AUC of internal validation using bootstrap resampling and prospective validation using the external cohort of 42 patients was 0.74 and 0.60, respectively. The calibration curves for probability of EAD showed acceptable agreement between nomogram prediction and actual observation. According to the score table, the probability of BAD was under 30% when the total point tally was under 72. But when the total was up to 139, the risk of EAD increased to 60%.Conclusion. We've established and validated a nomogram that can provide individual prediction of EAD for liver transplant recipients. The practical prognostic model may help clinicians to qualify the liver graft accurately, making a more reasonable allocation of organs.