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Real-World Diagnosis and Treatment of Diabetic Kidney Disease

Abstract

Introduction

People with type 2 diabetes mellitus (T2DM) and diabetic kidney disease (DKD) have increased morbidity and mortality risk. Angiotensin-converting enzyme inhibitors (ACEi) or angiotensin II receptor blockers (ARB) are recommended to slow kidney function decline in DKD. This representative, real-world data analysis of patients with T2DM was performed to detect onset of DKD and determine methods and timing of DKD diagnosis and time to initiation of ACEi/ARB therapy.

Methods

Patients diagnosed with T2DM before January 1, 2016 who developed DKD between January 1, 2017 and June 30, 2019 were identified from a longitudinal ambulatory electronic health record (EHR) dataset (Veradigm Inc). Each record was analyzed using the CLinical INTelligence engine (CLINT™, HealthPals, Inc.) to identify delays and gaps in diagnosing DKD. DKD was diagnosed through two reduced estimated glomerular filtration rate (eGFR; < 60 mL/min/1.73 m2) measurements at least 90 days apart, a single elevated urine albumin-to-creatinine ratio (UACR; > 30 mg/g) measurement, or ICD-9/10 diagnosis codes for DKD and/or albuminuria. Time to diagnose (TTD), time to treat (TTT), and diagnosis to treatment time were assessed.

Results

Of 6,499,409 patients with T2DM before January 2016, 245,978 developed DKD between January 1, 2017 and June 30, 2019. In this DKD cohort, ca. 50% were first identified through EHR diagnosis and ca. 50% by UACR or eGFR lab-based diagnosis. In patients who had UACR/eGFR assessed, more than 90% exhibited DKD-level results on the first diagnostic test. Average TTD after eGFR labs was 2 years; average TTT with ACEi/ARB was 6–9 months after DKD lab evidence. The majority of patients who developed DKD received ACEi/ARB therapy 6–7 months after diagnosis.

Conclusion

In a contemporary, large national cohort of patients with T2DM, progression to DKD was common but likely underrepresented. The low rate of DKD-screening labs, along with sizable delays in diagnosis of DKD and initiation of ACEi/ARB therapy, indicates that many patients who progress to DKD are not being properly treated.

Plain Language Summary

Diabetic kidney disease is kidney disease that occurs in patients with type 2 diabetes and is associated with greater risk of death and other adverse cardiovascular and kidney outcomes. Unfortunately, diabetic kidney disease is underdiagnosed because of lack of awareness and its early asymptomatic presentation. Early detection and treatment of diabetic kidney disease with medicines such as angiotensin-converting enzyme inhibitors (also known as ACE inhibitors) or angiotensin II receptor blockers (also known as ARBs) is important for the prevention of disease progression and the development of other serious conditions. This real-world analysis evaluated electronic health record data from more than 6 million patients with diabetes to detect the onset of diabetic kidney disease and to determine timing of treatment and gaps in medical care. Results from the study show that there are often significant delays in the diagnosis of diabetic kidney disease, even when laboratory evidence is available. Furthermore, many patients are not undergoing regular renal function testing, thus missing the opportunity for diagnosis (and subsequent treatment) of earlier onset, less severe disease. After diagnosis, patients with diabetic kidney disease experience significant delay until they receive appropriate treatment with an ACE inhibitor or ARB. The low rate of kidney function screening coupled with delays in diagnosis and treatment initiation suggest that many patients who progress to diabetic kidney disease are not being properly treated. The results from this study highlight the need to improve diagnostic and treatment protocols to address these significant gaps in care.

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Acknowledgements

Funding

This study and medical writing support for this publication were funded by Janssen Scientific Affairs, LLC, Titusville, NJ. The sponsor also funded the journal’s Rapid Service Fee.

Medical Writing Assistance

Medical writing support was provided by Kimberly Dittmar, PhD, and Lisa Shannon, PharmD, of Cello Health Communications/MedErgy, and was funded by Janssen Scientific Affairs, LLC.

Authorship

All named authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship for this article, take responsibility for the integrity of the work as a whole, and have given their approval for this version to be published.

Authors’ Contributions

Fatima Rodriguez, Donghyun J. Lee, and Rajesh Dash contributed to the data analysis and interpretation and drafted, reviewed, and approved the manuscript. Sanchit S. Gad contributed to the data analysis and drafted, reviewed, and approved the manuscript. Matheus P. Santos and Robert J. Beetel contributed to the data analysis and reviewed and approved the manuscript. Joseph Vasey and Matthew R. Weir contributed to the data interpretation and reviewed and approved the manuscript. Robert A. Bailey, Aarti Patel, and Jaime Blais contributed to the study design and data interpretation and reviewed and approved the manuscript.

Disclosures

Fatima Rodriguez reports equity from HealthPals and Carta; and consulting with Novartis, Janssen, and Novo Nordisk. Donghyun J. Lee, Sanchit S. Gad, Matheus P. Santos, and Robert J. Beetel are full-time employees of HealthPals. Joseph Vasey is a full-time employee of Veradigm. Robert A. Bailey, Aarti Patel, and Jaime Blais are full-time employees of Janssen Scientific Affairs, LLC. Matthew R. Weir has served as a scientific advisor for Janssen, AstraZeneca, Novo Nordisk, Merck, Boehringer Ingelheim, Bayer, and Vifor. Rajesh Dash reports equity from HealthPals, Heartbeam, and iMedrix; and consulting with Bayer and AstraZeneca.

Compliance with Ethics Guidelines

The analyzed retrospective EMR data underwent privacy certification before being made available for the purposes of this research. As a noninterventional, retrospective database study using a certified Health Insurance Portability and Accountability Act–compliant de-identified research database, approval by an institutional review board or ethics board was not necessary. No identifying information was analyzed nor is any included in the manuscript. Veradigm owns the database used in this study and participated in the analysis and manuscript development.

Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Correspondence to Rajesh Dash.

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Rodriguez, F., Lee, D.J., Gad, S.S. et al. Real-World Diagnosis and Treatment of Diabetic Kidney Disease. Adv Ther 38, 4425–4441 (2021). https://doi.org/10.1007/s12325-021-01777-9

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  • DOI: https://doi.org/10.1007/s12325-021-01777-9

Keywords

  • Diabetic kidney disease
  • Electronic health record
  • Medical care gaps
  • Real-world evidence
  • Renoprotection
  • Therapeutic care gaps