• PharmacoEconomics · Jul 2012

    Review Meta Analysis

    Cost utility of tumour necrosis factor-α inhibitors for rheumatoid arthritis: an application of Bayesian methods for evidence synthesis in a Markov model.

    • Christine M Nguyen, Mark Bounthavong, Margaret A S Mendes, Melissa L D Christopher, Josephine N Tran, Rashid Kazerooni, and Anthony P Morreale.
    • Veterans Affairs San Diego Healthcare System, San Diego, CA, USA.
    • Pharmacoeconomics. 2012 Jul 1;30(7):575-93.

    BackgroundRheumatoid arthritis (RA) is a chronic autoimmune disease that affects approximately 1.5 million people in the US. Tumour necrosis factor (TNF)-α inhibitors have been shown to effectively treat and maintain remission in patients with moderately to severely active RA compared with conventional agents. The high acquisition cost of TNF-α inhibitors prohibits access, which mandates economic investigations into their affordability. The lack of head-to-head comparisons between these agents makes it difficult to determine which agent is the most cost effective.ObjectiveThis study aimed to determine which TNF-α inhibitor was the most cost-effective agent for the treatment of moderately to severely active RA from the US healthcare payer's perspective.MethodsA Markov model was constructed to analyse the cost utility of five TNF-α inhibitors (in combination with methotrexate [+MTX]) versus MTX monotherapy using Bayesian methods for evidence synthesis. The model had a cycle length of 3 months and an overall time horizon of 5 years. Transition probabilities and utility scores were based on published studies. Total direct costs were adjusted to year 2009 $US using the medical component of the Consumer Price Index. All costs and QALYs were discounted at a rate of 3% per year. Patient response to the different strategies was determined by the American College of Rheumatology (ACR)50 criteria. One-way and probabilistic sensitivity analyses (PSAs) were performed to test the robustness of the base-case scenario. The base-case scenario was changed to ACR20 criteria (scenario 1) and ACR70 criteria (scenario 2) to determine the model's robustness. Cost-effectiveness acceptability curves and cost-effectiveness frontiers were used to estimate the cost-effectiveness probability of each treatment strategy. A willingness-to-pay (WTP) threshold was defined as three times the US GDP per capita ($US139,143 per additional QALY gained). Primary results were presented as incremental cost-effective ratios (ICERs).ResultsEtanercept+MTX was the most cost-effective treatment strategy in the base-case scenario up to a WTP threshold of $US2 185,497 per QALY gained. At a WTP threshold of greater than $US2 185,497 per QALY gained, certolizumab+MTX was the most cost-effective treatment strategy. One-way analyses showed that the base-case scenario was sensitive to the probability of achieving ACR50 criteria for MTX and each TNF-α inhibitor, and changes in the utility score for patients who achieved the ACR50 criteria. With the exception of infliximab, all of the TNF-α inhibitors were sensitive to drug cost per cycle. In the scenario analyses, certolizumab+MTX was a dominant treatment strategy using ACR20 criteria, but etanercept+MTX was a dominant treatment strategy using ACR70 criteria.ConclusionsEtanercept+MTX was a cost-effective treatment strategy in the base-case scenario; however, the model was sensitive to parameter uncertainties and ACR response criteria. Although Bayesian methods were used to determine transition probabilities, future studies will need to focus on head-to-head comparisons of multiple TNF-α inhibitors to provide valid comparisons.

      Pubmed     Full text   Copy Citation     Plaintext  

      Add institutional full text...

    Notes

     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…

What will the 'Medical Journal of You' look like?

Start your free 21 day trial now.

We guarantee your privacy. Your email address will not be shared.