Design and validation of a scoring model for differential diagnosis of diabetic nephropathy and nondiabetic renal diseases in type 2 diabetic patients
2型糖尿病患者中糖尿病肾病和非糖尿病肾病鉴别诊断评分模型的建立与验证
Funding information: Key Research & Development Plan of Hunan Province, Grant/Award Number: 2016JC2061; National Key R&D Program of China, Grant/Award Number: 2018YFC1314002
Abstract
enBackground
We aim to design a scoring model for differential diagnosis between diabetic nephropathy (DN) and nondiabetic renal disease (NDRD) in type 2 diabetic patients through a combination of clinical variables.
Methods
A total of 170 patients with type 2 diabetes who underwent kidney biopsies were included and divided into three groups according to pathological findings: DN group (n = 46), MIX group (DN + NDRD, n = 54), NDRD group (n = 70). Clinical characteristics and laboratory data were collected and compared among groups. Variables with a significant statistical difference between DN and NDRD patients were analyzed by logistic regression to predict the presence of NDRD; then a scoring model was established based on the regression coefficient and further validated in an independent cohort of 67 patients prospectively.
Results
On biopsy, 72.9% of patients had NDRD, and the most common pathological type was membranous nephropathy. The established scoring model for predicting NDRD included five predictors: age, systolic blood pressure, hemoglobin, duration of diabetes, and absence of diabetic retinopathy. The model demonstrated good discrimination and calibration (area under curve [AUC] 0.863, 95% CI, 0.800-0.925; Hosmer-Lemeshow [H-L] P = .062). Furthermore, high prediction accuracy (AUC = 0.900; 95% CI, 0.815-0.985) in the validation cohort proved the stability of the model.
Conclusions
We present a simple, robust scoring model for predicting the presence of NDRD with high accuracy (0.85) for the first time. This decision support tool provides a noninvasive method for differential diagnosis of DN and NDRD, which may help clinicians assess the risk-benefit ratio of kidney biopsy for type 2 diabetic patients with renal impairment.
摘要
zh背景
本研究旨在通过整合相关临床指标, 建立2型糖尿病患者中糖尿病肾病(diabetic nephropathy, DN)和非糖尿病肾病(non-diabetic renal disease, NDRD)的鉴别诊断评分模型。
方法
纳入170例接受肾脏穿刺活检术的2型糖尿病患者, 根据病理结果分为三组: DN 组(n=46), MIX 组(DN+NDRD, n=54), NDRD 组(n=70), 比较分析三组患者的临床及实验室数据, 将DN与NDRD两组患者有显著差异的变量通过 logistic多元回归分析预测 NDRD, 基于回归系数建立诊断评分模型, 并在另一独立验证队列(n=67)中前瞻性地验证模型准确度。
结果
活检患者中NDRD的检出率为72.9%, 其中最常见的病理类型为膜性肾病。NDRD诊断评分模型包括5个预测因素:年龄、收缩压、血红蛋白、糖尿病病程和排除糖尿病视网膜病变。该模型具有良好的区分度(曲线下面积[area under the curve, AUC]= 0.863; 95%CI 0.800-0.925)和校准度(H-L检验 P=0.062)。应用于验证队列时依然呈现出较高的准确率(AUC=0.900; 95% CI, 0.815-0.985), 提示其预测稳定性较好。
结论
本研究首次建立了用于预测NDRD诊断的评分模型, 准确率为85%, 可以作为一种无创性鉴别诊断方法有效地区分DN和NDRD的工具, 因此有助于医生评估有肾脏损害的2型糖尿病患者肾活检的风险-收益比。
CONFLICT OF INTEREST
The authors declare no conflicts of interest.
