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Abstract Number: 1000

Comparison Of The Cost-Effectiveness Of The Treatment Strategies With and Without Biological Response Modifiers For Patients With Recently Diagnosed Rheumatoid Arthritis Following A Clinical Guideline For Treatment Selection

An Tran-Duy1, Annelies Boonen2, Wietske Kievit3, Piet L.C.M. van Riel4, Mart A.F.J. van de Laar5 and Johan L. Severens6, 1Department of Internal Medicine, Maastricht University Medical Center, Maastricht, Netherlands, 2Department of Internal Medicine, Division of Rheumatology, Maastricht University Medical Center, Maastricht, Netherlands, 3Department of Rheumatology and DREAM registry, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands, 4Rheumatology, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands, 5Rheumatology, Medisch Spectrum Twente & University of Twente, Enschede, Netherlands, 6Institute of Health Policy and Management, Erasmus University Rotterdam, Rotterdam, Netherlands

Meeting: 2013 ACR/ARHP Annual Meeting

Keywords: Clinical practice guidelines, rheumatoid arthritis (RA) and tumor necrosis factor (TNF)

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Session Information

Title: Epidemiology and Health Services II & III

Session Type: Abstract Submissions (ACR)

Background/Purpose: In clinical practice, management of rheumatoid arthritis (RA) is characterized by a sequence of drugs which is determined based on patient characteristics, notably disease activity and treatment history. However, existing cost-effectiveness models do not reflect this clinical process of treatment decisions. In the last decade, biologic response modifiers (BRMs) became available in the treatment of RA. While these drugs show large efficacy in trials, they are expensive. This study aimed at quantifying the cost-effectiveness of the treatment strategy including BRMs (Strategy B) compared with the treatment strategy without BRMs (Strategy A) following a formal guideline for treatment of recently diagnosed RA.

Methods: A discrete event simulation model was developed to simulate life-time health utility and costs of individual patients using a societal perspective. Treatment effect on DAS28 and time to events were estimated using Dutch observational studies (DREAM and Nijmegen Inception cohorts). Long-term progression of HAQ was quantified using a linear mixed model.  Health care and sick leave costs were estimated using two-part models. Health utilities (EQ-5D) were predicted using a mixture model with adjusted limited dependent variable. Treatment decisions were based on the recommendations of the Dutch Society for Rheumatology for treatment of RA. A number of 10,000 theoretical patients were tracked individually until death. For uncertainty analysis of the model outcomes, Monte Carlo simulations were performed with 1,000 sets of parameters sampled from the probability distributions. SAS, R and Delphi were used for data analysis and model development.

Results: The recommended treatment selection based on DAS28 and treatment history was well simulated. Incremental cost per quality-adjusted life year gained (ICER) in Strategy B compared with Strategy A was €124,095. At willingness-to-pay thresholds above €119,167 per QALY, Strategy B dominated Strategy A in terms of cost-effectiveness but the probability that the Strategy B is cost-effective never exceeded 0.87.

Conclusion: Incorporation of the treatment decisions based on a clinical guideline in a cost-effectiveness model for RA is feasible, which makes the model more realistic.  Our model can be used as a tool to assess the effects of changes in clinical practice of RA management on disease progression of patients and on the corresponding incremental cost-effectiveness.


Disclosure:

A. Tran-Duy,

Pfizer B.V., The Netherlands,

2;

A. Boonen,

Pfizer B.V., The Netherlands,

5;

W. Kievit,
None;

P. L. C. M. van Riel,
None;

M. A. F. J. van de Laar,
None;

J. L. Severens,

Pfizer B.V., The Netherlands,

2.

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/comparison-of-the-cost-effectiveness-of-the-treatment-strategies-with-and-without-biological-response-modifiers-for-patients-with-recently-diagnosed-rheumatoid-arthritis-following-a-clinical-guideline/

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