Department of Medicine and Clinical Science, Kyushu University, Fukuoka, Japan.
Department of Internal Medicine, Faculty of Medicine, Division of Nephrology and Rheumatology, Fukuoka University, Fukuoka, Japan.
Nephrol Dial Transplant. 2021 Jan 25;36(2):365-374. doi: 10.1093/ndt/gfaa275.
Cardiovascular disease (CVD) is a major cause of death in kidney transplant (KT) recipients. To improve their long-term survival, it is clinically important to estimate the risk of CVD after living donor KT via adequate pre-transplant CVD screening.
A derivation cohort containing 331 KT recipients underwent living donor KT at Kyushu University Hospital from January 2006 to December 2012. A prediction model was retrospectively developed and risk scores were investigated via a Cox proportional hazards regression model. The discrimination and calibration capacities of the prediction model were estimated via the c-statistic and the Hosmer-Lemeshow goodness of fit test. External validation was estimated via the same statistical methods by applying the model to a validation cohort of 300 KT recipients who underwent living donor KT at Tokyo Women's Medical University Hospital.
In the derivation cohort, 28 patients (8.5%) had CVD events during the observation period. Recipient age, CVD history, diabetic nephropathy, dialysis vintage, serum albumin and proteinuria at 12 months after KT were significant predictors of CVD. A prediction model consisting of integer risk scores demonstrated good discrimination (c-statistic 0.88) and goodness of fit (Hosmer-Lemeshow test P = 0.18). In a validation cohort, the model demonstrated moderate discrimination (c-statistic 0.77) and goodness of fit (Hosmer-Lemeshow test P = 0.15), suggesting external validity.
The above-described simple model for predicting CVD after living donor KT was accurate and useful in clinical situations.
心血管疾病（CVD）是肾移植（KT）受者的主要死亡原因。为了提高他们的长期生存率，通过充分的移植前 CVD 筛查来评估活体供者 KT 后 CVD 的风险在临床上非常重要。
一个包含 331 名 KT 受者的队列在 2006 年 1 月至 2012 年 12 月期间在九州大学医院进行了活体供者 KT。通过 Cox 比例风险回归模型回顾性地开发了一个预测模型，并对风险评分进行了研究。通过 c 统计量和 Hosmer-Lemeshow 拟合优度检验来估计预测模型的区分能力和校准能力。通过相同的统计方法将模型应用于在东京女子医科大学医院接受活体供者 KT 的 300 名 KT 受者的验证队列，以评估外部验证。
在推导队列中，28 名患者（8.5%）在观察期间发生了 CVD 事件。受者年龄、CVD 病史、糖尿病肾病、透析时间、KT 后 12 个月的血清白蛋白和蛋白尿是 CVD 的显著预测因素。由整数风险评分组成的预测模型显示出良好的区分能力（c 统计量 0.88）和拟合优度（Hosmer-Lemeshow 检验 P=0.18）。在验证队列中，该模型显示出中等的区分能力（c 统计量 0.77）和拟合优度（Hosmer-Lemeshow 检验 P=0.15），表明具有外部有效性。
该描述活体供者 KT 后 CVD 预测的简单模型准确且在临床情况下有用。
