Exploring structural uncertainty and impact of health state utility values on lifetime outcomes in diabetes economic simulation models: Findings from the Ninth Mount Hood Diabetes Quality-of-Life Challenge
Tew M, Willis M, Asseburg C, Bennett H, Brennan A, Feenstra T, Gahn J, Gray A, Heathcote L, Herman W, Isaman Deanna, Kuo S, Lamotte M, Leal J, McEwan P, Nilsson A, Palmer A, Patel R, Pollard D, Ramos M, Sailer F, Schramm W, Shao H, Shi L, Si L, Smolen H, Thomas C, Tran-Duy An, Yang C, Ye W, Yu X, Zhang P, Clarke P
Structural uncertainty can affect model-based economic simulation estimates and study conclusions. Unfortunately, unlike parameter uncertainty, relatively little is known about its magnitude of impact on life years (LYs) and quality-adjusted life years (QALYs) in modelling of diabetes. We leveraged the Mount Hood Diabetes Challenge Network, a biennial conference attended by international diabetes modelling groups, to assess structural uncertainty in simulating QALYs in type 2 diabetes simulation models.
Eleven type 2 diabetes simulation modelling groups participated in the 9th Mount Hood Diabetes Challenge. Modelling groups simulated five diabetes-related intervention profiles using pre-defined baseline characteristics, and a standard utility value set for diabetes-related complications. LYs and QALYs were reported. Simulations were repeated using lower and upper limits of the 95% confidence intervals of utility inputs. Changes in LYs and QALYs from tested interventions were compared across models. Additional analyses were conducted post-challenge to investigate drivers of cross-model differences.
Substantial cross-model variability in incremental LYs and QALYs was observed, particularly for HbA1c and BMI intervention profiles. For a 0.5%-point permanent HbA1c reduction, LY gains ranged from 0.050 to 0.750. For one-unit permanent BMI reduction, incremental QALYs varied from a small d crease in QALY (-0.024) to an increase of 0.203. Changes in utility values of health states had a much smaller impact (to the hundredth of a decimal place) on incremental QALYs. Microsimulation models were found to generate a mean of 3.41 more LYs than cohort simulation models(p=0.049).
Variations in utility values contribute to a lesser extent than uncertainty captured as structural uncertainty. These findings reinforce the importance of assessing structural uncertainty thoroughly because the choice of model (or models) can influence study results, which can serve as evidence for resource allocation decisions.
Medical Decision Making, 2022;42(5):599-611
First published online: December 15, 2021