IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0261940.html
   My bibliography  Save this article

Model-based cost-effectiveness analyses comparing combinations of urate lowering therapy and anti-inflammatory treatment in gout patients

Author

Listed:
  • Celine Johanna van de Laar
  • Carly A Janssen
  • Matthijs Janssen
  • Martijn A H Oude Voshaar
  • Maiwenn J AL
  • Mart A F J van de Laar

Abstract

Objectives: To assess the cost-effectiveness of various combinations of urate lowering therapy (ULT) and anti-inflammatory treatment in the management of newly diagnosed gout patients, from the Dutch societal perspective. Methods: A probabilistic patient-level simulation estimating costs and quality-adjusted life years (QALYs) comparing gout and hyperuricemia treatment strategies was performed. ULT options febuxostat, allopurinol and no ULT were considered. Flare treatments naproxen, colchicine, prednisone, and anakinra were considered. A Markov Model was constructed to simulate gout disease. Health states were no flare, and severe pain, mild pain, moderate pain, or no pain in the presence of a flare. Model input was derived from patient level clinical trial data, meta-analyses or from previously published health-economic evaluations. The results of probabilistic sensitivity analyses were presented using incremental cost-effectiveness ratios (ICERs), and summarized using cost-effectiveness acceptability curves (CEACs). Scenario analyses were performed. Results: The ICER for allopurinol versus no ULT was €1,381, when combined with naproxen. Febuxostat yielded the highest utility, but also the highest costs (€4,385 vs. €4,063 for allopurinol), resulting in an ICER of €25,173 when compared to allopurinol. No ULT was not cost-effective, yielding the lowest utility. For the gout flare medications, comparable effects on utility were achieved. Combined with febuxostat, naproxen was the cheapest option (€4,404), and anakinra the most expensive (€4,651). The ICER of anakinra compared to naproxen was €818,504. Colchicine and prednisone were dominated by naproxen. Conclusion: Allopurinol and febuxostat were both cost-effective compared to No ULT. Febuxostat was cost-effective in comparison with allopurinol at higher willingness-to-pay thresholds. For treating gout flares, colchicine, naproxen and prednisone offered comparable health economic implications, although naproxen was the favoured option.

Suggested Citation

  • Celine Johanna van de Laar & Carly A Janssen & Matthijs Janssen & Martijn A H Oude Voshaar & Maiwenn J AL & Mart A F J van de Laar, 2022. "Model-based cost-effectiveness analyses comparing combinations of urate lowering therapy and anti-inflammatory treatment in gout patients," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-13, January.
    • Handle: RePEc:plo:pone00:0261940
    DOI: 10.1371/journal.pone.0261940
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0261940
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0261940&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0261940?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Andrew H. Briggs & A. E. Ades & Martin J. Price, 2003. "Probabilistic Sensitivity Analysis for Decision Trees with Multiple Branches: Use of the Dirichlet Distribution in a Bayesian Framework," Medical Decision Making, , vol. 23(4), pages 341-350, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. A. E. Ades & Karl Claxton & Mark Sculpher, 2006. "Evidence synthesis, parameter correlation and probabilistic sensitivity analysis," Health Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 373-381, April.
    2. Alan Brennan & Samer Kharroubi & Anthony O'Hagan & Jim Chilcott, 2007. "Calculating Partial Expected Value of Perfect Information via Monte Carlo Sampling Algorithms," Medical Decision Making, , vol. 27(4), pages 448-470, July.
    3. Rachael DiSantostefano & Andrea Biddle & John Lavelle, 2006. "The Long-Term Cost Effectiveness of Treatments for Benign Prostatic Hyperplasia," PharmacoEconomics, Springer, vol. 24(2), pages 171-191, February.
    4. Pedram Sendi & Huldrych F Günthard & Mathew Simcock & Bruno Ledergerber & Jörg Schüpbach & Manuel Battegay & for the Swiss HIV Cohort Study, 2007. "Cost-Effectiveness of Genotypic Antiretroviral Resistance Testing in HIV-Infected Patients with Treatment Failure," PLOS ONE, Public Library of Science, vol. 2(1), pages 1-8, January.
    5. Nick Bansback & Roberta Ara & Sue Ward & Aslam Anis & Hyon Choi, 2009. "Statin Therapy in Rheumatoid Arthritis," PharmacoEconomics, Springer, vol. 27(1), pages 25-37, January.
    6. Ya-Chen Shih & Josephine Mauskopf & Rohit Borker, 2007. "A Cost-Effectiveness Analysis of First-Line Controller Therapies for Persistent Asthma," PharmacoEconomics, Springer, vol. 25(7), pages 577-590, July.
    7. Laura McCullagh & Cathal Walsh & Michael Barry, 2012. "Value-of-Information Analysis to Reduce Decision Uncertainty Associated with the Choice of Thromboprophylaxis after Total Hip Replacement in the Irish Healthcare Setting," PharmacoEconomics, Springer, vol. 30(10), pages 941-959, October.
    8. Kenneth J. Smith & Amber E. Barnato & Mark S. Roberts, 2006. "Teaching Medical Decision Modeling: A Qualitative Description of Student Errors and Curriculum Responses," Medical Decision Making, , vol. 26(6), pages 583-588, November.
    9. Naren Kumar Surendra & Mohd Rizal Abdul Manaf & Lai Seong Hooi & Sunita Bavanandan & Fariz Safhan Mohamad Nor & Shahnaz Shah Firdaus Khan & Ong Loke Meng & Abdul Halim Abdul Gafor, 2019. "Cost utility analysis of end stage renal disease treatment in Ministry of Health dialysis centres, Malaysia: Hemodialysis versus continuous ambulatory peritoneal dialysis," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-16, October.
    10. Andrija S Grustam & Nasuh Buyukkaramikli & Ron Koymans & Hubertus J M Vrijhoef & Johan L Severens, 2019. "Value of information analysis in telehealth for chronic heart failure management," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-23, June.
    11. Mylene Lagarde & John Cairns, 2012. "Modelling human resources policies with Markov models: an illustration with the South African nursing labour market," Health Care Management Science, Springer, vol. 15(3), pages 270-282, September.
    12. Ankur Pandya & Ashley A Eggman & Hooman Kamel & Ajay Gupta & Bruce R Schackman & Pina C Sanelli, 2016. "Modeling the Cost Effectiveness of Neuroimaging-Based Treatment of Acute Wake-Up Stroke," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-13, February.
    13. Yuanhui Zhang & Haipeng Wu & Brian T. Denton & James R. Wilson & Jennifer M. Lobo, 2019. "Probabilistic sensitivity analysis on Markov models with uncertain transition probabilities: an application in evaluating treatment decisions for type 2 diabetes," Health Care Management Science, Springer, vol. 22(1), pages 34-52, March.
    14. Bruce Wang & Joshua A Roth & Hiep Nguyen & Eugene Felber & Wes Furnback & Louis P Garrison, 2015. "The Short-Term Cost-Effectiveness of Once-Daily Liraglutide Versus Once-Weekly Exenatide for the Treatment of Type 2 Diabetes Mellitus in the United States," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-13, April.
    15. Christopher Knight & Josephine Mauskopf & Mats Ekelund & Amitabh Singh & Shiyi Yang & Robert Boggs, 2012. "Cost-effectiveness of treatment with etanercept for psoriasis in Sweden," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 13(2), pages 145-156, April.
    16. Charles Christian Adarkwah & Afschin Gandjour & Maren Akkerman & Silvia M Evers, 2011. "Cost-Effectiveness of Angiotensin-Converting Enzyme Inhibitors for the Prevention of Diabetic Nephropathy in The Netherlands – A Markov Model," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-10, October.
    17. Regina Rendas-Baum & Min Yang & Joseph Gricar & Gene Wallenstein, 2010. "Cost-effectiveness analysis of treatments for premenstrual dysphoric disorder," Applied Health Economics and Health Policy, Springer, vol. 8(2), pages 129-140, March.
    18. Edmund Jones & David Epstein & Leticia García-Mochón, 2017. "A Procedure for Deriving Formulas to Convert Transition Rates to Probabilities for Multistate Markov Models," Medical Decision Making, , vol. 37(7), pages 779-789, October.
    19. Rungskunroch, Panrawee & Jack, Anson & Kaewunruen, Sakdirat, 2021. "Benchmarking on railway safety performance using Bayesian inference, decision tree and petri-net techniques based on long-term accidental data sets," Reliability Engineering and System Safety, Elsevier, vol. 213(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0261940. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.