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.
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.
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.
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.
- Content Type Journal Article
- Pages 1-12
- DOI 10.1007/s11136-012-0139-1
- Authors
- Mangala Rajan, Center for Healthcare Knowledge Management, Veterans Health Administration New Jersey, East Orange, NJ, USA
- Kuan-Chi Lai, Robert Wood Johnson Medical School – University of Medicine and Dentistry of New Jersey, New Brunswick, NJ, USA
- Chin-Lin Tseng, Center for Healthcare Knowledge Management, Veterans Health Administration New Jersey, East Orange, NJ, USA
- Shirley Qian, Department of Health Policy and Management, Center for the Assessment of Pharmaceutical Practices (CAPP), Boston University School of Public Health, Boston, MA, USA
- Alfredo Selim, Department of Health Policy and Management, Center for the Assessment of Pharmaceutical Practices (CAPP), Boston University School of Public Health, Boston, MA, USA
- Lewis Kazis, Department of Health Policy and Management, Center for the Assessment of Pharmaceutical Practices (CAPP), Boston University School of Public Health, Boston, MA, USA
- Leonard Pogach, Center for Healthcare Knowledge Management, Veterans Health Administration New Jersey, East Orange, NJ, USA
- Anushua Sinha, Center for Healthcare Knowledge Management, Veterans Health Administration New Jersey, East Orange, NJ, USA
- Journal Quality of Life Research
- Online ISSN 1573-2649
- Print ISSN 0962-9343