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Prioritizing Future Research on Allopurinol and Febuxostat for the Management of Gout: Value of Information Analysis
by
Kuntz, Karen M.
, Jutkowitz, Eric
, Choi, Hyon K.
, Jalal, Hawre
, Alarid-Escudero, Fernando
in
Allopurinol
/ Allopurinol - administration & dosage
/ Allopurinol - therapeutic use
/ Analysis
/ Approximation
/ Clinical trials
/ Cost analysis
/ Cost-Benefit Analysis
/ Costs
/ Dosage and administration
/ Drug Administration Schedule
/ Drug therapy
/ Expected values
/ Febuxostat - administration & dosage
/ Febuxostat - therapeutic use
/ Gout
/ Gout - drug therapy
/ Health Administration
/ Health care expenditures
/ Health care policy
/ Health Economics
/ Humans
/ Markov Chains
/ Medicine
/ Medicine & Public Health
/ Models, Economic
/ Observational studies
/ Original Research Article
/ Pharmacoeconomics and Health Outcomes
/ Population
/ Public Health
/ Quality of Life Research
/ Regression analysis
/ Research Design
/ Rheumatism
/ Studies
/ Uric acid
2017
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Prioritizing Future Research on Allopurinol and Febuxostat for the Management of Gout: Value of Information Analysis
by
Kuntz, Karen M.
, Jutkowitz, Eric
, Choi, Hyon K.
, Jalal, Hawre
, Alarid-Escudero, Fernando
in
Allopurinol
/ Allopurinol - administration & dosage
/ Allopurinol - therapeutic use
/ Analysis
/ Approximation
/ Clinical trials
/ Cost analysis
/ Cost-Benefit Analysis
/ Costs
/ Dosage and administration
/ Drug Administration Schedule
/ Drug therapy
/ Expected values
/ Febuxostat - administration & dosage
/ Febuxostat - therapeutic use
/ Gout
/ Gout - drug therapy
/ Health Administration
/ Health care expenditures
/ Health care policy
/ Health Economics
/ Humans
/ Markov Chains
/ Medicine
/ Medicine & Public Health
/ Models, Economic
/ Observational studies
/ Original Research Article
/ Pharmacoeconomics and Health Outcomes
/ Population
/ Public Health
/ Quality of Life Research
/ Regression analysis
/ Research Design
/ Rheumatism
/ Studies
/ Uric acid
2017
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Prioritizing Future Research on Allopurinol and Febuxostat for the Management of Gout: Value of Information Analysis
by
Kuntz, Karen M.
, Jutkowitz, Eric
, Choi, Hyon K.
, Jalal, Hawre
, Alarid-Escudero, Fernando
in
Allopurinol
/ Allopurinol - administration & dosage
/ Allopurinol - therapeutic use
/ Analysis
/ Approximation
/ Clinical trials
/ Cost analysis
/ Cost-Benefit Analysis
/ Costs
/ Dosage and administration
/ Drug Administration Schedule
/ Drug therapy
/ Expected values
/ Febuxostat - administration & dosage
/ Febuxostat - therapeutic use
/ Gout
/ Gout - drug therapy
/ Health Administration
/ Health care expenditures
/ Health care policy
/ Health Economics
/ Humans
/ Markov Chains
/ Medicine
/ Medicine & Public Health
/ Models, Economic
/ Observational studies
/ Original Research Article
/ Pharmacoeconomics and Health Outcomes
/ Population
/ Public Health
/ Quality of Life Research
/ Regression analysis
/ Research Design
/ Rheumatism
/ Studies
/ Uric acid
2017
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Prioritizing Future Research on Allopurinol and Febuxostat for the Management of Gout: Value of Information Analysis
Journal Article
Prioritizing Future Research on Allopurinol and Febuxostat for the Management of Gout: Value of Information Analysis
2017
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Overview
Objectives
The aim of this study was to quantify the value of conducting additional research and reducing uncertainty regarding the cost effectiveness of allopurinol and febuxostat for the management of gout.
Methods
We used a previously developed Markov model that evaluated the cost effectiveness of nine urate-lowering strategies: no treatment, allopurinol-only fixed dose (300 mg), allopurinol-only dose escalation (up to 800 mg), febuxostat-only fixed dose (80 mg), febuxostat-only dose escalation (up to 120 mg), allopurinol–febuxostat sequential therapy fixed dose, allopurinol–febuxostat sequential therapy dose escalation, febuxostat–allopurinol sequential therapy fixed dose, and febuxostat–allopurinol sequential therapy dose escalation. Each strategy was evaluated over the lifetime of a hypothetical gout patient. We calculated population expected value of perfect information (EVPI). We used a linear regression meta-modeling approach to calculate population expected value of partial perfect information (EVPPI), and a Gaussian approximation to calculate the population expected value of sample information for parameters (EVSI) and the expected net benefit of sampling (ENBS) for four potential study designs: (1) an allopurinol efficacy trial; (2) a febuxostat efficacy trial; (3) a prospective observational study evaluating health utilities; and (4) a comprehensive study evaluating the efficacy of allopurinol and febuxostat and health utilities. A 5-year decision time horizon was used in the base-case analysis.
Results
EVPI varied by a decision maker’s willingness-to-pay (WTP) per quality-adjusted life-year (QALY) and was $US900 million for WTP of $US60,000 per QALY. Population EVPPI was highest across all WTP values for study design #4. For study design #4 and a WTP of $US60,000 per QALY, the optimal sample size was 735 patients per study arm.
Conclusions
Future studies are needed to evaluate the effectiveness of allopurinol and febuxostat dose escalation.
Publisher
Springer International Publishing,Springer,Springer Nature B.V
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