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

Journal Article (Journal Article)

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.

Full Text

Duke Authors

Cited Authors

  • Wysham, CH; Gauthier-Loiselle, M; Bailey, RA; Manceur, AM; Lefebvre, P; Greenberg, M; Duh, MS; Young, JB

Published Date

  • February 2020

Published In

Volume / Issue

  • 36 / 2

Start / End Page

  • 219 - 227

PubMed ID

  • 31625766

Pubmed Central ID

  • 31625766

Electronic International Standard Serial Number (EISSN)

  • 1473-4877

International Standard Serial Number (ISSN)

  • 0300-7995

Digital Object Identifier (DOI)

  • 10.1080/03007995.2019.1682981


  • eng