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4L-5
VALUE OF INFORMATION ANALYSES OF GOUT THERAPIES: USING A META-MODELING APPROACH

** Purpose: ** Gout is the
most common inflammatory arthritis in the United States, and several urate-lowering treatment strategies are used to manage
symptoms. The value of collecting additional information of key parameters in
the cost-effectiveness of urate-lowering treatment
strategies for the management of gout is unknown. We apply a meta-modeling approach to
calculate the expected value of perfect information (EVPI), expected value of
partial perfect information (EVPPI), and the expected value of sample
information for parameters (EVPSI) on all model parameters (e.g., utilities,
efficacy, and cost).

** Methods: ** We used
a previously developed model that evaluated the cost-effectiveness of five urate-lowering
strategies: no treatment, allopurinol or febuxostat only, allopurinol- febuxostat
sequential therapy, and febuxostat-allopurinol sequential therapy. Health
states in the model accounted for disease status: controlled, uncontrolled on
medication, and uncontrolled off medication. To quantify uncertainty in the
model we conducted a probabilistic sensitivity analysis (PSA). We implemented a
linear regression meta-model to the dataset generated from the PSA. Conceptually
similar parameters were evaluated together (e.g., utilities) since a single
study is likely to inform all of these parameters. To inform future research design
we extrapolated EVPI, EVPPI, and EVPSI on a United States population level for
an annual incidence of 29,376 new gout patients assuming a decision lifetime of
10 years. Finally, we calculated
the optimal sample size of a future study assuming a patient survey would be administered
during a clinical visit (fixed cost $6,000; cost per patient $100) to evaluate
the parameter group of interest.

** Results: ** Population
EVPI varies by a decision maker's willingness-to-pay (WTP) per quality-adjusted
life year and is $227 million for WTP of $100,000. EVPPI is highest for utility
parameters when WTP is $50,000-$100,000. Figure 1 shows population EVPSI for
parameters evaluating utilities, cost of research, expected net benefit of
sampling (ENBS), and the optimal sample size for a survey conducted in a clinic
evaluating gout patients' health utilities. Given a WTP of $100,000, the
optimal sample size of a survey based research study evaluating the health
utility of gout patients is 8,600. If the costs of research
doubles the optimal sample size is 5,700.

** Conclusions: ** Future studies should be conducted to
evaluate utility of gout patients.