Francesco Saverio Mennini1,2, Andrea Marcellusi3,4,5, Lara Gitto1, Florenzo Iannone6. 1. Economic Evaluation and HTA (EEHTA) CEIS, Faculty of Economics, University of Rome "Tor Vergata", Rome, Italy. 2. Institute for Leadership and Management in Health, Kingston University London, London, UK. 3. Economic Evaluation and HTA (EEHTA) CEIS, Faculty of Economics, University of Rome "Tor Vergata", Rome, Italy. andrea.marcellusi@uniroma2.it. 4. Institute for Leadership and Management in Health, Kingston University London, London, UK. andrea.marcellusi@uniroma2.it. 5. National Research Council (CNR), Institute for Research on Population and Social Policies (IRPPS), Rome, Italy. andrea.marcellusi@uniroma2.it. 6. Rheumatology Unit, DIM, University of Bari, Bari, Italy.
Abstract
BACKGROUND: Rheumatoid arthritis (RA) is an autoimmune disease with a substantial medical and economic burden. In Italy, it affects approximately 280,000 people, therefore representing the musculoskeletal disease with the highest economic impact in terms of costs for the National Health Service and the social security system. OBJECTIVE: The aim of this study was to estimate the annual economic burden of RA in Italy and determine the potential cost reduction considering the most effective biologic treatment for early rapidly progressing RA (ERPRA) patients. METHODS: The model developed considers both direct costs that are mainly due to the pharmacological treatments, and indirect costs, which also include the productivity lost because of the disease. A systematic literature review provided the epidemiological and economic data used to inform the model. A one-way probabilistic sensitivity analysis based on 5000 Monte Carlo simulations was performed. Furthermore, specific scenario analyses were developed for those patients presenting an ERPRA, with the aim of evaluating the effectiveness of different biologic treatments for this subgroup of patients and estimating potential cost reduction. RESULTS: The total economic burden associated with RA was estimated to be €2.0 billion per year (95% confidence interval [CI] €1.8-2.3 billion). Forty-five percent of the expenditure was due to indirect costs (95% CI €0.8-1.0 billion); 45% depended on direct medical costs (95% CI €0.7-1.1 billion), and the residual 10% was determined by direct non-medical costs (95% CI €0.16-0.25 billion). In particular, the costs estimated for ERPRA patients totalled €76,171,181, of which approximately €18 million was associated with patients with a high level of anti-citrullinated protein antibodies (ACPA). The results of the analysis outline how it is possible to obtain a cost reduction for ERPRA patients of between €1 and €3 million by varying the number of patients with a high level of immunoglobulin G treated with the most effective biologic drug. In fact, the latter may determine higher efficacy outcomes, especially for poor prognostic ERPRA patients, ensuing higher levels of productivity. CONCLUSIONS: This study presents a pioneering approach to estimate the direct and indirect costs of RA. The model developed is a useful tool for policy makers as it allows to understand the economic implications of RA treatment in Italy, identify the most effective allocation of resources, and select the most appropriate treatment for ERPRA patients.
BACKGROUND:Rheumatoid arthritis (RA) is an autoimmune disease with a substantial medical and economic burden. In Italy, it affects approximately 280,000 people, therefore representing the musculoskeletal disease with the highest economic impact in terms of costs for the National Health Service and the social security system. OBJECTIVE: The aim of this study was to estimate the annual economic burden of RA in Italy and determine the potential cost reduction considering the most effective biologic treatment for early rapidly progressing RA (ERPRA) patients. METHODS: The model developed considers both direct costs that are mainly due to the pharmacological treatments, and indirect costs, which also include the productivity lost because of the disease. A systematic literature review provided the epidemiological and economic data used to inform the model. A one-way probabilistic sensitivity analysis based on 5000 Monte Carlo simulations was performed. Furthermore, specific scenario analyses were developed for those patients presenting an ERPRA, with the aim of evaluating the effectiveness of different biologic treatments for this subgroup of patients and estimating potential cost reduction. RESULTS: The total economic burden associated with RA was estimated to be €2.0 billion per year (95% confidence interval [CI] €1.8-2.3 billion). Forty-five percent of the expenditure was due to indirect costs (95% CI €0.8-1.0 billion); 45% depended on direct medical costs (95% CI €0.7-1.1 billion), and the residual 10% was determined by direct non-medical costs (95% CI €0.16-0.25 billion). In particular, the costs estimated for ERPRA patients totalled €76,171,181, of which approximately €18 million was associated with patients with a high level of anti-citrullinated protein antibodies (ACPA). The results of the analysis outline how it is possible to obtain a cost reduction for ERPRA patients of between €1 and €3 million by varying the number of patients with a high level of immunoglobulin G treated with the most effective biologic drug. In fact, the latter may determine higher efficacy outcomes, especially for poor prognostic ERPRA patients, ensuing higher levels of productivity. CONCLUSIONS: This study presents a pioneering approach to estimate the direct and indirect costs of RA. The model developed is a useful tool for policy makers as it allows to understand the economic implications of RA treatment in Italy, identify the most effective allocation of resources, and select the most appropriate treatment for ERPRA patients.
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