Development of risk models for major adverse chronic renal outcomes among patients with type 2 diabetes mellitus using insurance claims: a retrospective observational study
- 6 November 2019
- journal article
- research article
- Published by Taylor & Francis Ltd in Current Medical Research and Opinion
- Vol. 36 (2), 219-227
- https://doi.org/10.1080/03007995.2019.1682981
Abstract
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 OptumTM 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 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.Keywords
This publication has 39 references indexed in Scilit:
- Development and Validation of a General Population Renal Risk ScoreClinical Journal of the American Society of Nephrology, 2011
- Predicting Renal Risk in the General PopulationClinical Journal of the American Society of Nephrology, 2011
- Updating and Validating the Charlson Comorbidity Index and Score for Risk Adjustment in Hospital Discharge Abstracts Using Data From 6 CountriesAmerican Journal of Epidemiology, 2011
- Healthcare costs associated with nephrology care in pre-dialysis chronic kidney disease patientsJournal of Medical Economics, 2010
- Predicting the risk of Chronic Kidney Disease in Men and Women in England and Wales: prospective derivation and external validation of the QKidney®ScoresBMC Family Practice, 2010
- A Strategy for Health Care Reform — Toward a Value-Based SystemThe New England Journal of Medicine, 2009
- A Simple Algorithm to Predict Incident Kidney DiseaseJAMA Internal Medicine, 2008
- 10-Year Follow-up of Intensive Glucose Control in Type 2 DiabetesThe New England Journal of Medicine, 2008
- Screening strategies for chronic kidney disease in the general population: follow-up of cross sectional health surveyBMJ, 2006
- Development and progression of nephropathy in type 2 diabetes: The United Kingdom Prospective Diabetes Study (UKPDS 64)Kidney International, 2003