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 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.
Transparency
Declaration of funding
This work was supported by Janssen Scientific Affairs, LLC, and the study sponsor was involved in the study design; the collection, analysis and interpretation of data; the writing of the report; and in the decision to submit the article for publication; authors maintained control over the final content.
Declaration of financial and other interests
CHW and JBY acted as consultants for Janssen Scientific Affairs, LLC. MGL, AMM, PL, MG, and MSD are employees of Analysis Group, Inc., which has received consultancy fees from Janssen Scientific Affairs, LLC. RAB is an employee of Janssen Scientific Affairs, LLC and may own stock or stock options. CMRO peer reviewers on this manuscript have no relevant financial or other relationships to disclose.
Author contributions
All authors participated to the conception and design of the study, analysis or interpretation of the data presented in this manuscript, and critically revised the intellectual content of this manuscript. MGL, AM, PL, and MG participated in the acquisition/collection of data. All authors have approved the final article.
Acknowledgements
Medical writing assistance was provided by Samuel Rochette, an employee of Analysis Group, Inc.