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Open Access Original investigation

Baseline comparison of three health utility measures and the feeling thermometer among participants in the action to control cardiovascular risk in diabetes trial

Dennis W Raisch12*, Patricia Feeney3, David C Goff4, KM Venkat Narayan5, Patrick J O’Connor6, Ping Zhang7, Don G Hire8 and Mark D Sullivan9

Author Affiliations

1 University of New Mexico Health Sciences Center, 1 University of New Mexico, Albuquerque, NM, 87131, USA

2 VA Cooperative Studies Program, Clinical Research Pharmacy Coordinating Center, Albuquerque, NM, USA

3 Wake Forest University Health Sciences, Medical Center Blvd, Winston Salem, NC, 27157-1063, USA

4 Public Health Sciences and Internal Medicine, Wake Forest University Health Sciences, Medical Center Blvd, Winston Salem, NC, 27157-1063, USA

5 Hubert Prof, Global Hlth & Epidemiology, Hubert Department of Global Health, School of Public Health, Emory University, Rollins School of Public Health, Grace Crum Rollins Building, 1518 Clifton Road, Atlanta, 30322, Georgia

6 Senior Clinical Investigator, HealthPartners Research Foundation, Minneapolis, MN, USA

7 Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, 30341, USA

8 Wake Forest University Health Sciences, Medical Center Blvd, Winston Salem, NC, 27157-1063, USA

9 Psychiatry and Behavioral Sciences, University of Washington, Box 356560, Seattle, WA, 98195, USA

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Cardiovascular Diabetology 2012, 11:35  doi:10.1186/1475-2840-11-35

Published: 19 April 2012

Abstract

Background

Health utility (HU) measures are used as overall measures of quality of life and to determine quality adjusted life years (QALYs) in economic analyses. We compared baseline values of three HUs including Short Form 6 Dimensions (SF-6D), and Health Utilities Index, Mark II and Mark III (HUI2 and HUI3) and the feeling thermometer (FT) among type 2 diabetes participants in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. We assessed relationships between HU and FT values and patient demographics and clinical variables.

Methods

ACCORD was a randomized clinical trial to test if intensive controls of glucose, blood pressure and lipids can reduce the risk of major cardiovascular disease (CVD) events in type 2 diabetes patients with high risk of CVD. The health-related quality of life (HRQOL) sub-study includes 2,053 randomly selected participants. Interclass correlations (ICCs) and agreement between measures by quartile were used to evaluate relationships between HU’s and the FT. Multivariable regression models specified relationships between patient variables and each HU and the FT.

Results

The ICCs were 0.245 for FT/SF-6D, 0.313 for HUI3/SF-6D, 0.437 for HUI2/SF-6D, 0.338 for FT/HUI2, 0.337 for FT/HUI3 and 0.751 for HUI2/HUI3 (P < 0.001 for all). Common classification by quartile was found for the majority (62%) of values between HUI2 and HUI3, which was significantly (P < 0.001) higher than between other HUs and the FT: SF-6D/HUI3 = 40.8%, SF-6D/HUI2 = 40.9%, FT/HUI3 = 35.0%, FT/HUI2 = 34.9%, and FT/SF-6D = 31.9%. Common classification was higher between SF-6D/HUI2 and SF-6D/HUI3 (P < 0.001) than between FT/SF-6D, FT/HUI2, and FT/HUI3. The mean difference in HU values per patient ranged from −0.024 ± 0.225 for SF-6D/ HUI3 to −0.124 ± 0.133 for SF-6D/HUI2. Regression models were significant; clinical and demographic variables explained 6.1% (SF-6D) to 7.7% (HUI3) of the variance in HUs.

Conclusions

The agreements between the different HUs were poor except for the two HUI measures; therefore HU values derived different measures may not be comparable. The FT had low agreement with HUs. The relationships between HUs and demographic and clinical measures demonstrate how severity of diabetes and other clinical and demographic factors are associated with HUs and FT measures.

Trial registration

ClinicalTrials.gov Identifier: NCT00000620

Keywords:
Diabetes mellitus, Type 2/*complications /physiopathology/psychology; Health status indicators; Randomized controlled clinical trial; Humans; Regression analysis; Glycemic control