Simulation of Quality-Adjusted Survival in Chronic Diseases
Alison J. Hayes,
Philip M. Clarke,
Merryn Voysey and
Anthony Keech
Medical Decision Making, 2011, vol. 31, issue 4, 559-570
Abstract:
Background . Recent studies have demonstrated that measures of health-related quality of life can predict complications and mortality in patients with diabetes, even after adjustment for clinical risk factors. Methods . The authors developed a simulation model of disease progression in type 2 diabetes to investigate the impact of patient quality of life on lifetime outcomes and its potential response to therapy. Changes in health utility over time are captured as a result of complications and aging. All risk equations, model parameter estimates, and input data were derived from patient-level data from the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial. Results . Healthier patients with type 2 diabetes enjoy more life years, quality-adjusted life years (QALYs), and more life years free of complications. A 65-year-old patient at full health (utility = 1) can expect to live approximately 2 years longer and achieve 6 more QALYs than a patient at average health (utility = 0.8), given similar clinical risk factors. For patients with higher EQ-5D utility, the additional years lived without complications contribute more to longer life expectancy than years lived with complications. Conclusions . The authors have developed a model for progression of disease in diabetes that has a number of novel features; it captures the observed relationships between measures of quality of life and future outcomes, the number of states have been minimized, and it can be parameterized with just 4 risk equations. Underlying the simple model structure is important patient-level heterogeneity in health and outcomes. The simulations suggest that differences in patients’ EQ-5D utility can account for large differences in QALYs, which could be relevant in cost-utility analyses.
Keywords: simulation, survival; quality of life; QALYs; type 2 diabetes, risk modeling (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:31:y:2011:i:4:p:559-570
DOI: 10.1177/0272989X11409049
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