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Abstract：
The study aimed to evaluate the performance of a predictive model using the kidney failure risk equation (KFRE) for end-stage renal disease (ESRD) in diabetes and to investigate the impact of glomerular filtration rate (GFR) as estimated by different equations on the performance of the KFRE model in diabetes.
A total of 18,928 individuals with diabetes without ESRD history from the UK Biobank, a prospective cohort study initiated in 2006-2010, were included in this study. Modification of diet in renal disease (MDRD), chronic kidney disease epidemiology collaboration (CKD-EPI) or revised Lund-Malmö (r-LM) were used to estimate GFR in the KFRE model. Cox proportional risk regression was used to determine the correlation coefficients between each variable and ESRD risk in each model. Harrell\'s C-index and net reclassification improvement (NRI) index were used to evaluate the differentiation of the models. Analysis was repeated in subgroups based on albuminuria and hemoglobin A1C (HbA1c) levels.
Overall, 132 of the 18,928 patients developed ESRD after a median follow-up of 12 years. The Harrell\'s C-index based on GFR estimated by CKD-EPI, MDRD, and r-LM was 0.914 (95% CI = 0.8812-0.9459), 0.908 (95% CI = 0.8727-0.9423), and 0.917 (95% CI = 0.8837-0.9496), respectively. Subgroup analysis revealed that in diabetic patients with macroalbuminuria, the KFRE model based on GFR estimated by r-LM (KFRE-eGFRr-LM) had better differentiation compared to the KFRE model based on GFR estimated by CKD-EPI (KFRE-eGFRCKD-EPI) with a KFRE-eGFRr-LM C-index of 0.846 (95% CI = 0.797-0.894, p = 0.025), while the KFRE model based on GFR estimated by MDRD (KFRE-eGFRMDRD) showed no significant difference compared to the KFRE-eGFRCKD-EPI (KFRE-eGFRMDRD C-index of 0.837, 95% CI = 0.785-0.889, p = 0.765). Subgroup analysis of poor glycemic control (HbA1c >8.5%) demonstrated the same trend. Compared to KFRE-eGFRCKD-EPI (C-index = 0.925, 95% CI = 0.874-0.976), KFRE-eGFRr-LM had a C-index of 0.935 (95% CI = 0.888-0.982, p = 0.071), and KFRE-eGFRMDRD had a C-index of 0.925 (95% CI = 0.874-0.976, p = 0.498).
In adults with diabetes, the r-LM equation performs better than the CKD-EPI and MDRD equations in the KFRE model for predicting ESRD, especially for those with macroalbuminuria and poor glycemic control (HbA1c >8.5%).
A total of 18,928 individuals with diabetes without ESRD history from the UK Biobank, a prospective cohort study initiated in 2006-2010, were included in this study. Modification of diet in renal disease (MDRD), chronic kidney disease epidemiology collaboration (CKD-EPI) or revised Lund-Malmö (r-LM) were used to estimate GFR in the KFRE model. Cox proportional risk regression was used to determine the correlation coefficients between each variable and ESRD risk in each model. Harrell\'s C-index and net reclassification improvement (NRI) index were used to evaluate the differentiation of the models. Analysis was repeated in subgroups based on albuminuria and hemoglobin A1C (HbA1c) levels.
Overall, 132 of the 18,928 patients developed ESRD after a median follow-up of 12 years. The Harrell\'s C-index based on GFR estimated by CKD-EPI, MDRD, and r-LM was 0.914 (95% CI = 0.8812-0.9459), 0.908 (95% CI = 0.8727-0.9423), and 0.917 (95% CI = 0.8837-0.9496), respectively. Subgroup analysis revealed that in diabetic patients with macroalbuminuria, the KFRE model based on GFR estimated by r-LM (KFRE-eGFRr-LM) had better differentiation compared to the KFRE model based on GFR estimated by CKD-EPI (KFRE-eGFRCKD-EPI) with a KFRE-eGFRr-LM C-index of 0.846 (95% CI = 0.797-0.894, p = 0.025), while the KFRE model based on GFR estimated by MDRD (KFRE-eGFRMDRD) showed no significant difference compared to the KFRE-eGFRCKD-EPI (KFRE-eGFRMDRD C-index of 0.837, 95% CI = 0.785-0.889, p = 0.765). Subgroup analysis of poor glycemic control (HbA1c >8.5%) demonstrated the same trend. Compared to KFRE-eGFRCKD-EPI (C-index = 0.925, 95% CI = 0.874-0.976), KFRE-eGFRr-LM had a C-index of 0.935 (95% CI = 0.888-0.982, p = 0.071), and KFRE-eGFRMDRD had a C-index of 0.925 (95% CI = 0.874-0.976, p = 0.498).
In adults with diabetes, the r-LM equation performs better than the CKD-EPI and MDRD equations in the KFRE model for predicting ESRD, especially for those with macroalbuminuria and poor glycemic control (HbA1c >8.5%).
摘要：
该研究旨在使用肾衰竭风险方程（KFRE）评估糖尿病终末期肾病（ESRD）的预测模型的性能，并研究不同方程估计的肾小球滤过率（GFR）对糖尿病中KFRE模型性能的影响。
来自英国生物银行的18,928名没有ESRD病史的糖尿病患者，一项始于2006-2010年的前瞻性队列研究被纳入本研究.肾脏疾病（MDRD）的饮食改良，在KFRE模型中,使用慢性肾脏病流行病学合作(CKD-EPI)或修订的Lund-Malmö(r-LM)来估计GFR.Cox比例风险回归用于确定每个模型中每个变量与ESRD风险之间的相关系数。使用Harrell的C指数和净分类改进（NRI）指数来评估模型的差异。根据蛋白尿和血红蛋白A1C（HbA1c）水平在亚组中重复分析。
总的来说，18,928名患者中有132名在中位随访12年后发展为ESRD。基于CKD-EPI估计的GFR的HarrellC指数，MDRD,r-LM为0.914(95%CI=0.8812-0.9459)，0.908（95%CI=0.8727-0.9423），和0.917（95%CI=0.8837-0.9496），分别。亚组分析显示，在有大量白蛋白尿的糖尿病患者中，与基于CKD-EPI估计的GFR的KFRE模型（KFRE-eGFRCKD-EPI）相比，基于r-LM估计的GFR的KFRE模型（KFRE-eGFRCKD-EPI）具有更好的区分度-eGFRr-LMC指数为0.846（95％CI=0.797-0.894，p=0.025），而基于MDRD估计的GFR的KFRE模型（KFRE-eGFRMDRD）与KFRE-eGFRCKD-EPI相比没有显着差异（KFRE-eGFRMDRDC指数为0.837，95％CI=0.785-0.889，p=0.765）。血糖控制不良(HbA1c>8.5%)的亚组分析显示出相同的趋势。与KFRE-eGFRCKD-EPI相比（C指数=0.925，95%CI=0.874-0.976），KFRE-eGFRr-LM的C指数为0.935(95%CI=0.888-0.982，p=0.071)，KFRE-eGFRMDRD的C指数为0.925(95%CI=0.874-0.976，p=0.498)。
在患有糖尿病的成年人中，在预测ESRD的KFRE模型中,r-LM方程的性能优于CKD-EPI和MDRD方程,尤其是那些大量白蛋白尿和血糖控制不良（HbA1c>8.5％）。
来自英国生物银行的18,928名没有ESRD病史的糖尿病患者，一项始于2006-2010年的前瞻性队列研究被纳入本研究.肾脏疾病（MDRD）的饮食改良，在KFRE模型中,使用慢性肾脏病流行病学合作(CKD-EPI)或修订的Lund-Malmö(r-LM)来估计GFR.Cox比例风险回归用于确定每个模型中每个变量与ESRD风险之间的相关系数。使用Harrell的C指数和净分类改进（NRI）指数来评估模型的差异。根据蛋白尿和血红蛋白A1C（HbA1c）水平在亚组中重复分析。
总的来说，18,928名患者中有132名在中位随访12年后发展为ESRD。基于CKD-EPI估计的GFR的HarrellC指数，MDRD,r-LM为0.914(95%CI=0.8812-0.9459)，0.908（95%CI=0.8727-0.9423），和0.917（95%CI=0.8837-0.9496），分别。亚组分析显示，在有大量白蛋白尿的糖尿病患者中，与基于CKD-EPI估计的GFR的KFRE模型（KFRE-eGFRCKD-EPI）相比，基于r-LM估计的GFR的KFRE模型（KFRE-eGFRCKD-EPI）具有更好的区分度-eGFRr-LMC指数为0.846（95％CI=0.797-0.894，p=0.025），而基于MDRD估计的GFR的KFRE模型（KFRE-eGFRMDRD）与KFRE-eGFRCKD-EPI相比没有显着差异（KFRE-eGFRMDRDC指数为0.837，95％CI=0.785-0.889，p=0.765）。血糖控制不良(HbA1c>8.5%)的亚组分析显示出相同的趋势。与KFRE-eGFRCKD-EPI相比（C指数=0.925，95%CI=0.874-0.976），KFRE-eGFRr-LM的C指数为0.935(95%CI=0.888-0.982，p=0.071)，KFRE-eGFRMDRD的C指数为0.925(95%CI=0.874-0.976，p=0.498)。
在患有糖尿病的成年人中，在预测ESRD的KFRE模型中,r-LM方程的性能优于CKD-EPI和MDRD方程,尤其是那些大量白蛋白尿和血糖控制不良（HbA1c>8.5％）。
