Development of risk models for major adverse chronic renal outcomes among patients with type 2 diabetes mellitus using insurance claims: a retrospective observational study

Objective: To develop and validate models allowing the prediction of major adverse chronic renal outcomes (MACRO) in patients with type 2 diabetes mellitus (T2DM) using insurance claims data.
Methods: The Optum Integrated Real World Evidence Electronic Health Records and Claims de-identified database (10/01/2006–09/30/2016) was used to identify T2DM patients ≥50 years old. Risk factors were assessed over a 12-month baseline period, and MACRO were subsequently assessed until the end of data availability, continuous enrollment, or death. Separate models were built for moderate-to-severe diabetic kidney disease (DKD), end-stage renal disease (ESRD), and renal death. A random split-sample approach was employed, where 70% of the sample served for model development (training set) and the remaining 30% served for validation (testing set). C-statistics were used to assess model performance.
Results: A total of 160,031 patients were included. Risk factors associated with MACRO for all models included adapted diabetes complications severity index, heart failure, anemia, diabetic nephropathy, and CKD. C-statistics ranged between 0.70 (moderate-to-severe DKD) and 0.84 (renal death) in the testing set. A substantial proportion (e.g. 88.7% for moderate-to-severe DKD) of patients predicted to be at high-risk of MACRO did not have diabetic nephropathy, proteinuria, or CKD at baseline.
Conclusions: The models developed using insurance claims data could reliably predict the risk of MACRO in patients with T2DM and enabled patients at higher-risk of DKD to be identified in the absence of baseline diabetic nephropathy, CKD, or proteinuria. These models could help establish strategies to reduce the risk of MACRO in T2DM patients.

研究目标：开发并验证可用于预测2型糖尿病（type 2 diabetes mellitus, T2DM）患者主要不良慢性肾脏结局（major adverse chronic renal outcomes, MACRO）的模型，所用数据为保险索赔数据。
研究方法：使用Optum整合真实世界证据电子病历与去标识化索赔数据库（Optum Integrated Real World Evidence Electronic Health Records and Claims de-identified database，2006年10月1日—2016年9月30日），筛选年龄≥50岁的2型糖尿病患者。在12个月的基线期内评估患者的危险因素，随后随访记录主要不良慢性肾脏结局，直至数据可用期限结束、患者连续参保终止或死亡。针对中重度糖尿病肾病（diabetic kidney disease, DKD）、终末期肾病（end-stage renal disease, ESRD）及肾性死亡分别构建预测模型。采用随机拆分抽样法，将70%的样本用于模型开发（训练集），剩余30%用于模型验证（测试集）。以C统计量评估模型性能。
研究结果：最终共纳入160031例患者。所有模型对应的MACRO危险因素包括改良版糖尿病并发症严重程度指数、心力衰竭、贫血、糖尿病肾病及慢性肾脏病（chronic kidney disease, CKD）。测试集的C统计量范围为0.70（中重度DKD）至0.84（肾性死亡）。被预测为MACRO高风险的患者中，有相当比例（如中重度DKD对应的88.7%）在基线时未患有糖尿病肾病、蛋白尿或慢性肾脏病。
研究结论：本研究基于保险索赔数据开发的模型，可可靠预测2型糖尿病患者的主要不良慢性肾脏结局风险，并能在基线无糖尿病肾病、慢性肾脏病或蛋白尿的情况下，识别出糖尿病肾病高风险人群。此类模型可为制定降低2型糖尿病患者主要不良慢性肾脏结局风险的干预策略提供支撑。