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Estimating utilities for chronic kidney disease, using SF-36 and SF-12-based measures: challenges in a population of veterans with diabetes

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Abstract

Purpose

Using transformations of existing quality-of-life data to estimate utilities has the potential to efficiently provide investigators with utility information. We used within-method and across-method comparisons and estimated disutilities associated with increasing chronic kidney disease (CKD) severity.

Methods

In an observational cohort of veterans with diabetes (DM) and pre-existing SF-36/SF-12 responses, we used six transformation methods (SF-12 to EQ-5D, SF-36 to HUI2, SF-12 to SF-6D, SF-36 to SF-6D, SF-36 to SF-6D (Bayesian method), and SF-12 to VR-6D) to estimate unadjusted utilities. CKD severity was staged using glomerular filtration rate estimated from serum creatinines, with the modification of diet in renal disease formula. We then used multivariate regression to estimate disutilities specifically associated with CKD severity stage.

Results

Of 67,963 patients, 22,273 patients had recent-onset DM and 45,690 patients had prevalent DM. For the recent-onset group, the adjusted disutility associated with CKD derived from the six transformation methods ranged from 0.0029 to 0.0045 for stage 2; −0.004 to −0.0009 for early stage 3; −0.017 to −0.010 for late stage 3; −0.023 to −0.012 for stage 4; −0.078 to −0.033 for stage 5; and −0.012 to −0.001 for ESRD/dialysis.

Conclusion

Disutility did not increase monotonically as CKD severity increased. Differences in disutilities estimated using the six different methods were found. Both findings have implications for using such estimates in economic analyses.

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Acknowledgments

This work was funded by VHA Health Services Research and Development Grant “Medications and Diabetes Morbidity in the VA Diabetes Epidemiology Cohort” [Principal investigators: Donald Miller and Leonard Pogach]. Preliminary results from this paper were presented at the 2011 VHA Health Services Research and Development annual meeting (Baltimore, MD) and at the 2011 Society for Medical Decision Making annual meeting (Chicago, IL). The authors thank Heather Franklin for her assistance with manuscript preparation and Sri Ram Pentakota for his feedback. Financial support for this study was provided by the Veterans’ Health Administration/Health Services Research and Development (VHA/HSR&D). The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report.

Conflict of interest

All authors report no financial conflicts of interest.

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Authors and Affiliations

  1. Center for Healthcare Knowledge Management, Veterans Health Administration New Jersey, East Orange, NJ, USA

    Mangala Rajan, Chin-Lin Tseng, Leonard Pogach & Anushua Sinha

  2. Robert Wood Johnson Medical School - University of Medicine and Dentistry of New Jersey, New Brunswick, NJ, USA

    Kuan-Chi Lai

  3. Department of Preventive Medicine and Community Health, New Jersey Medical School - University of Medicine and Dentistry of New Jersey, 185 South Orange Avenue, MSB F506, Newark, NJ, 07101, USA

    Chin-Lin Tseng, Leonard Pogach & Anushua Sinha

  4. Department of Health Policy and Management, Center for the Assessment of Pharmaceutical Practices (CAPP), Boston University School of Public Health, Boston, MA, USA

    Shirley Qian, Alfredo Selim & Lewis Kazis

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  1. Mangala Rajan
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Correspondence to Anushua Sinha.

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SF-36® and SF-12® are registered trademarks of the Medical Outcomes Trust.

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Rajan, M., Lai, KC., Tseng, CL. et al. Estimating utilities for chronic kidney disease, using SF-36 and SF-12-based measures: challenges in a population of veterans with diabetes. Qual Life Res 22, 53–64 (2013). https://doi.org/10.1007/s11136-012-0139-1

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