IDEAS home Printed from https://ideas.repec.org/a/spr/eujhec/v21y2020i1d10.1007_s10198-019-01117-3.html
   My bibliography  Save this article

Cost-effectiveness analysis of the first-line EGFR-TKIs in patients with non-small cell lung cancer harbouring EGFR mutations

Author

Listed:
  • Marscha S. Holleman

    (Erasmus University Rotterdam)

  • Maiwenn J. Al

    (Erasmus University Rotterdam)

  • Remziye Zaim

    (Erasmus University Rotterdam)

  • Harry J. M. Groen

    (University of Groningen and University Medical Center Groningen)

  • Carin A. Uyl-de Groot

    (Erasmus University Rotterdam)

Abstract

Objectives To compare the cost-effectiveness of first-line gefitinib, erlotinib, afatinib, and osimertinib in patients with non-small cell lung cancer (NSCLC) harbouring epidermal growth factor receptor (EGFR) mutations. Methods A systematic review and network meta-analysis (NMA) were conducted to compare the relative efficacy of gefitinib, erlotinib, afatinib, and osimertinib in EGFR-mutated NSCLC. To assess the cost-effectiveness of these treatments, a Markov model was developed from Dutch societal perspective. The model was based on the clinical studies included in the NMA. Incremental costs per life-year (LY) and per quality-adjusted life-year (QALY) gained were estimated. Deterministic and probabilistic sensitivity analyses (PSA) were conducted. Results Total discounted per patient costs for gefitinib, erlotinib, afatinib, and osimertinib were €65,889, €64,035, €69,418, and €131,997, and mean QALYs were 1.36, 1.39, 1.52, and 2.01 per patient, respectively. Erlotinib dominated gefitinib. Afatinib versus erlotinib yielded incremental costs of €27,058/LY and €41,504/QALY gained. Osimertinib resulted in €91,726/LY and €128,343/QALY gained compared to afatinib. PSA showed that gefitinib, erlotinib, afatinib, and osimertinib had 13%, 19%, 43%, and 26% probability to be cost-effective at a threshold of €80,000/QALY. A price reduction of osimertinib of 30% is required for osimertinib to be cost-effective at a threshold of €80,000/QALY. Conclusions Osimertinib has a better effectiveness compared to all other TKIs. However, at a Dutch threshold of €80,000/QALY, osimertinib appears not to be cost-effective.

Suggested Citation

  • Marscha S. Holleman & Maiwenn J. Al & Remziye Zaim & Harry J. M. Groen & Carin A. Uyl-de Groot, 2020. "Cost-effectiveness analysis of the first-line EGFR-TKIs in patients with non-small cell lung cancer harbouring EGFR mutations," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(1), pages 153-164, February.
  • Handle: RePEc:spr:eujhec:v:21:y:2020:i:1:d:10.1007_s10198-019-01117-3
    DOI: 10.1007/s10198-019-01117-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10198-019-01117-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10198-019-01117-3?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wenhua Liang & Xuan Wu & Wenfeng Fang & Yuanyuan Zhao & Yunpeng Yang & Zhihuang Hu & Cong Xue & Jing Zhang & Jianwei Zhang & Yuxiang Ma & Ting Zhou & Yue Yan & Xue Hou & Tao Qin & Xiaoxiao Dinglin & Y, 2014. "Network Meta-Analysis of Erlotinib, Gefitinib, Afatinib and Icotinib in Patients with Advanced Non-Small-Cell Lung Cancer Harboring EGFR Mutations," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-11, February.
    2. Drummond, Michael F. & Sculpher, Mark J. & Torrance, George W. & O'Brien, Bernie J. & Stoddart, Greg L., 2005. "Methods for the Economic Evaluation of Health Care Programmes," OUP Catalogue, Oxford University Press, edition 3, number 9780198529453, Decembrie.
    3. Nicky J. Welton & Howard H. Z. Thom, 2015. "Value of Information," Medical Decision Making, , vol. 35(5), pages 564-566, 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. 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.
    2. Lee, Alice J. & Ames, Daniel R., 2017. "“I can’t pay more” versus “It’s not worth more”: Divergent effects of constraint and disparagement rationales in negotiations," Organizational Behavior and Human Decision Processes, Elsevier, vol. 141(C), pages 16-28.
    3. Hussain, Hadia & Murtaza, Murtaza & Ajmal, Areeb & Ahmed, Afreen & Khan, Muhammad Ovais Khalid, 2020. "A study on the effects of social media advertisement on consumer’s attitude and customer response," MPRA Paper 104675, University Library of Munich, Germany.
    4. A. G. Fatullayev & Nizami A. Gasilov & Şahin Emrah Amrahov, 2019. "Numerical solution of linear inhomogeneous fuzzy delay differential equations," Fuzzy Optimization and Decision Making, Springer, vol. 18(3), pages 315-326, September.
    5. Arun Advani & William Elming & Jonathan Shaw, 2023. "The Dynamic Effects of Tax Audits," The Review of Economics and Statistics, MIT Press, vol. 105(3), pages 545-561, May.
    6. Saha, Sanjib & Gerdtham, Ulf-G. & Toresson, Håkan & Minthon, Lennart & Jarl, Johan, 2018. "Economic Evaluation of Interventions for Screening of Dementia," Working Papers 2018:20, Lund University, Department of Economics.
    7. Mark Oppe & Daniela Ortín-Sulbarán & Carlos Vila Silván & Anabel Estévez-Carrillo & Juan M. Ramos-Goñi, 2021. "Cost-effectiveness of adding Sativex® spray to spasticity care in Belgium: using bootstrapping instead of Monte Carlo simulation for probabilistic sensitivity analyses," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(5), pages 711-721, July.
    8. Aghion, Philippe & Akcigit, Ufuk & Lequien, Matthieu & Stantcheva, Stefanie, 2017. "Tax simplicity and heterogeneous learning," LSE Research Online Documents on Economics 86613, London School of Economics and Political Science, LSE Library.
    9. Marie Bjørneby & Annette Alstadsæter & Kjetil Telle, 2018. "Collusive tax evasion by employers and employees. Evidence from a randomized fi eld experiment in Norway," Discussion Papers 891, Statistics Norway, Research Department.
    10. Chuangen Gao & Shuyang Gu & Jiguo Yu & Hai Du & Weili Wu, 2022. "Adaptive seeding for profit maximization in social networks," Journal of Global Optimization, Springer, vol. 82(2), pages 413-432, February.
    11. Koessler, Frederic & Laclau, Marie & Renault, Jérôme & Tomala, Tristan, 2022. "Long information design," Theoretical Economics, Econometric Society, vol. 17(2), May.
    12. Ties Hoomans & Johan Severens & Nicole Roer & Gepke Delwel, 2012. "Methodological Quality of Economic Evaluations of New Pharmaceuticals in the Netherlands," PharmacoEconomics, Springer, vol. 30(3), pages 219-227, March.
    13. Khan, Md. Tajuddin & Kishore, Avinash & Joshi, Pramod Kumar, 2016. "Gender dimensions on farmers’ preferences for direct-seeded rice with drum seeder in India:," IFPRI discussion papers 1550, International Food Policy Research Institute (IFPRI).
    14. Annette Alstadsæter & Wojciech Kopczuk & Kjetil Telle, 2019. "Social networks and tax avoidance: evidence from a well-defined Norwegian tax shelter," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 26(6), pages 1291-1328, December.
    15. Sebastian Kaumanns, 2019. "“Some fuzzy math”: relational information on debt value adjustments by managers and the financial press," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 755-794, December.
    16. Samuel J Gershman, 2015. "A Unifying Probabilistic View of Associative Learning," PLOS Computational Biology, Public Library of Science, vol. 11(11), pages 1-20, November.
    17. Arun Advani, 2022. "Who does and doesn't pay taxes?," Fiscal Studies, John Wiley & Sons, vol. 43(1), pages 5-22, March.
    18. Steve Fortin & Ahmad Hammami & Michel Magnan, 2021. "Re‐exploring Fair Value Accounting and Value Relevance: An Examination of Underlying Securities," Abacus, Accounting Foundation, University of Sydney, vol. 57(2), pages 220-250, June.
    19. de Camargo Fiorini, Paula & Roman Pais Seles, Bruno Michel & Chiappetta Jabbour, Charbel Jose & Barberio Mariano, Enzo & de Sousa Jabbour, Ana Beatriz Lopes, 2018. "Management theory and big data literature: From a review to a research agenda," International Journal of Information Management, Elsevier, vol. 43(C), pages 112-129.
    20. Jacobs, Mattis & Kurtz, Christian & Simon, Judith & Böhmann, Tilo, 2021. "Value Sensitive Design and power in socio-technical ecosystems," Internet Policy Review: Journal on Internet Regulation, Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin, vol. 10(3), pages 1-26.

    More about this item

    Keywords

    Cost-effectiveness analysis; Non-small cell lung cancer; EGFR-TKI; Gefitinib; Erlotinib; Afatinib; Osimertinib;
    All these keywords.

    JEL classification:

    • I19 - Health, Education, and Welfare - - Health - - - Other
    • C59 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Other
    • C69 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Other

    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:spr:eujhec:v:21:y:2020:i:1:d:10.1007_s10198-019-01117-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.