Department of Urology, Shahid Modarres Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Urology-Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Int Urol Nephrol. 2023 Oct;55(10):2447-2456. doi: 10.1007/s11255-023-03670-6. Epub 2023 Jun 27.
To compare the predictive values of Charlson comorbidity index (CCI), modified Charlson comorbidity index kidney transplant (mCCI-KT) and recipient risk score (RRS) indices in prediction of patient and graft survival in kidney transplant patients.
In this retrospective study, all patients who underwent a live-donor KT from 2006 to 2010, were included. Demographic data, comorbidities and survival time after KT were extracted and the association between above indices with patient and graft survival were compared.
In ROC curve analysis of 715 included patients, all three indicators were weak in predicting graft rejection with the area under curve (AUC) less than 0.6. The best models for predicting the overall survival were mCCI-KT and CCI with AUC of 0.827 and 0.780, respectively. Sensitivity and specificity of mCCI-KT at cut point of 1 were 87.2 and 75.6. Sensitivity and specificity of CCI at cut point of 3 were 84.6 and 68.3 and for RRS at cut point of 3 were 51.3 and 81.2, respectively.
The mCCI-KT index followed by the CCI index provided the best model in predicting the 10-year patient survival; however, they were poor in predicting graft survival and this model can be used for better stratifying transplant candidates prior to surgery.
比较 Charlson 合并症指数(CCI)、改良 Charlson 合并症指数肾脏移植(mCCI-KT)和受者风险评分(RRS)指数在预测肾脏移植患者患者和移植物生存中的预测价值。
在这项回顾性研究中,纳入了 2006 年至 2010 年期间接受活体供肾移植的所有患者。提取人口统计学数据、合并症和移植后生存时间,并比较上述指标与患者和移植物生存之间的关系。
在对 715 例纳入患者的 ROC 曲线分析中,所有三个指标预测移植物排斥的曲线下面积(AUC)均小于 0.6,均较弱。预测总体生存率的最佳模型是 mCCI-KT 和 CCI,AUC 分别为 0.827 和 0.780。mCCI-KT 在切点为 1 时的敏感性和特异性分别为 87.2%和 75.6%。CCI 在切点为 3 时的敏感性和特异性分别为 84.6%和 68.3%,RRS 在切点为 3 时的敏感性和特异性分别为 51.3%和 81.2%。
mCCI-KT 指数随后是 CCI 指数,在预测 10 年患者生存率方面提供了最佳模型;然而,它们在预测移植物生存率方面表现不佳,该模型可用于在手术前更好地对移植候选者进行分层。