Departments of Medicine, School of Medicine, the Johns Hopkins University, Baltimore, Maryland, USA.
J Am Geriatr Soc. 2012 Jan;60(1):1-7. doi: 10.1111/j.1532-5415.2011.03652.x.
To develop a prediction model for kidney transplantation (KT) outcomes specific to older adults with end-stage renal disease (ESRD) and to use this model to estimate the number of excellent older KT candidates who lack access to KT.
Secondary analysis of data collected by the United Network for Organ Sharing and U.S. Renal Disease System.
Retrospective analysis of national registry data.
Model development: Medicare-primary older recipients (aged ≥ 65) of a first KT between 1999 and 2006 (N = 6,988). Model application: incident Medicare-primary older adults with ESRD between 1999 and 2006 without an absolute or relative contraindication to transplantation (N = 128,850).
Comorbid conditions were extracted from U.S. Renal Disease System Form 2728 data and Medicare claims.
The prediction model used 19 variables to estimate post-KT outcome and showed good calibration (Hosmer-Lemeshow P = .44) and better prediction than previous population-average models (P < .001). Application of the model to the population with incident ESRD identified 11,756 excellent older transplant candidates (defined as >87% predicted 3-year post-KT survival, corresponding to the top 20% of transplanted older adults used in model development), of whom 76.3% (n = 8,966) lacked access. It was estimated that 11% of these candidates would have identified a suitable live donor had they been referred for KT.
A risk-prediction model specific to older adults can identify excellent KT candidates. Appropriate referral could result in significantly greater rates of KT in older adults.
针对患有终末期肾病(ESRD)的老年患者,开发一种特定于肾移植(KT)结局的预测模型,并使用该模型估计缺乏 KT 机会的优秀老年 KT 候选者的数量。
对美国器官共享联合网络和美国肾脏疾病系统收集的数据进行二次分析。
国家注册数据的回顾性分析。
模型开发:1999 年至 2006 年间接受首次 KT 的 Medicare 主要老年受者(年龄≥65 岁)(N=6988)。模型应用:1999 年至 2006 年间患有 ESRD 且无绝对或相对移植禁忌的新 Medicare 主要老年患者(N=128850)。
合并症从美国肾脏疾病系统表格 2728 数据和 Medicare 理赔中提取。
该预测模型使用 19 个变量来估计 KT 后的结果,表现出良好的校准(Hosmer-Lemeshow P=0.44),并且比以前的人群平均模型有更好的预测能力(P<0.001)。将该模型应用于新发 ESRD 人群,确定了 11756 名优秀的老年移植候选者(定义为预测 3 年后 KT 后生存率>87%,相当于模型开发中使用的移植老年患者的前 20%),其中 76.3%(n=8966)缺乏机会。据估计,这些候选者中有 11%如果被推荐进行 KT,他们会找到合适的活体供者。
一种特定于老年患者的风险预测模型可以识别优秀的 KT 候选者。适当的转诊可以显著提高老年患者的 KT 率。