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Epidemiology/Health Services Research

Patient Health Utility Equations for a Type 2 Diabetes Model

  1. Simon J. Neuwahl1⇑,
  2. Ping Zhang2,
  3. Haiying Chen3,
  4. Hui Shao2,4,
  5. Michael Laxy2,5,6,7,
  6. Andrea M. Anderson3,
  7. Timothy E. Craven3,
  8. Thomas J. Hoerger1, and
  9. the Look AHEAD Research Group*
  1. 1RTI International, Durham, NC
  2. 2Centers for Disease Control and Prevention, Atlanta, GA
  3. 3Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC
  4. 4Department of Pharmaceutical Outcomes and Policy, University of Florida College of Pharmacy, Gainesville, Florida
  5. 5Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany
  6. 6German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
  7. 7Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, Neuherberg, Germany
  1. Corresponding author: Simon J. Neuwahl, sneuwahl{at}rti.org
Diabetes Care 2021 Feb; 44(2): 381-389. https://doi.org/10.2337/dc20-1207
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Abstract

OBJECTIVE To estimate the health utility impact of diabetes-related complications in a large, longitudinal U.S. sample of people with type 2 diabetes.

RESEARCH DESIGN AND METHODS We combined Health Utilities Index Mark 3 data on patients with type 2 diabetes from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) and Look AHEAD (Action for Health in Diabetes) trials and their follow-on studies. Complications were classified as events if they occurred in the year preceding the utility measurement; otherwise, they were classified as a history of the complication. We estimated utility decrements associated with complications using a fixed-effects regression model.

RESULTS Our sample included 15,252 persons with an average follow-up of 8.2 years and a total of 128,873 person-visit observations. The largest, statistically significant (P < 0.05) health utility decrements were for stroke (event, −0.109; history, −0.051), amputation (event, −0.092; history, −0.150), congestive heart failure (event, −0.051; history, −0.041), dialysis (event, −0.039), estimated glomerular filtration rate (eGFR) <30 mL/min/1.73 m2 (event, −0.043; history, −0.025), angina (history, −0.028), and myocardial infarction (MI) (event, −0.028). There were smaller effects for laser photocoagulation and eGFR <60 mL/min/1.73 m2. Decrements for dialysis history, angina event, MI history, revascularization event, revascularization history, laser photocoagulation event, and hypoglycemia were not significant (P ≥ 0.05).

CONCLUSIONS With use of a large study sample and a longitudinal design, our estimated health utility scores are expected to be largely unbiased. Estimates can be used to describe the health utility impact of diabetes complications, improve cost-effectiveness models, and inform diabetes policies.

Footnotes

  • ↵* A complete list of the authors and members of the Look AHEAD trial can be found in the supplementary material online.

  • The contents of this article are the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention.

  • This article contains supplementary material online at https://doi.org/10.2337/figshare.13166159.

  • Received May 20, 2020.
  • Accepted October 29, 2020.
  • © 2020 by the American Diabetes Association
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Diabetes Care: 44 (2)

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Patient Health Utility Equations for a Type 2 Diabetes Model
Simon J. Neuwahl, Ping Zhang, Haiying Chen, Hui Shao, Michael Laxy, Andrea M. Anderson, Timothy E. Craven, Thomas J. Hoerger, the Look AHEAD Research Group
Diabetes Care Feb 2021, 44 (2) 381-389; DOI: 10.2337/dc20-1207

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Patient Health Utility Equations for a Type 2 Diabetes Model
Simon J. Neuwahl, Ping Zhang, Haiying Chen, Hui Shao, Michael Laxy, Andrea M. Anderson, Timothy E. Craven, Thomas J. Hoerger, the Look AHEAD Research Group
Diabetes Care Feb 2021, 44 (2) 381-389; DOI: 10.2337/dc20-1207
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