Goldfarb-Rumyantzev Alexander S, Scandling John D, Pappas Lisa, Smout Randall J, Horn Susan
Division of Nephrology and Hypertension, University of Utah Health Sciences Center, Salt Lake City, UT 84112, USA.
Clin Transplant. 2003 Dec;17(6):485-97. doi: 10.1046/j.0902-0063.2003.00051.x.
Pre- and post-transplant predictive factors of graft survival for optimal and expanded criteria grafts have been studied in the past. The goal of our study was to evaluate the recent large set of United Network of Organ Sharing records (1990-1998) to generate a prediction algorithm of 3-yr graft survival based on pre-transplant variables alone. The dataset of patients with end-stage renal disease and cadaveric kidney or kidney-pancreas transplantation (1990-1998) used in the study consisted of 37,407 records. Logistic regression (LM) and a tree-based model (TBM) were used to identify predictors of 3-yr allograft survival and to generate prediction algorithm. Donor and recipient demographic characteristics (age, race, and gender) and body mass index showed non-linear, while human leukocyte antigen match showed strong linear relationships with 3-yr graft survival. Prediction of the probability of graft survival from the model, achieved a good match with the observed survival of the separate dataset, with a correlation of r = 0.998 for LM and r = 0.984 for TBM. The positive predictive value (PV) of allograft survival with LM and TBM was 76.0% and the negative PV was 63 and 53.8% for LM and TBM, respectively. Both LM and the TBM can potentially be used in clinical practice for long-term prediction of kidney allograft survival based on pre-transplant variables.
过去已经对最佳标准和扩展标准移植物移植前后的移植物存活预测因素进行了研究。我们研究的目的是评估器官共享联合网络最近的大量记录（1990 - 1998年），以仅基于移植前变量生成一个3年移植物存活的预测算法。该研究中使用的终末期肾病患者及尸体肾或肾 - 胰联合移植（1990 - 1998年）的数据集包含37407条记录。使用逻辑回归（LM）和基于树的模型（TBM）来识别3年同种异体移植物存活的预测因素并生成预测算法。供体和受体的人口统计学特征（年龄、种族和性别）以及体重指数呈现非线性关系，而人类白细胞抗原匹配与3年移植物存活呈现强线性关系。通过模型预测移植物存活概率，与单独数据集观察到的存活率有很好的匹配，逻辑回归的相关系数r = 0.998，基于树的模型的相关系数r = 0.984。逻辑回归和基于树的模型同种异体移植物存活的阳性预测值（PV）分别为76.0%，逻辑回归和基于树的模型的阴性预测值分别为63%和53.8%。逻辑回归和基于树的模型都有可能在临床实践中用于基于移植前变量对肾同种异体移植物存活进行长期预测。
