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The Predicted Impact of Ipilimumab Usage on Survival in Previously Treated Advanced or Metastatic Melanoma in the UK

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  • James Larkin
  • Anthony J Hatswell
  • Paul Nathan
  • Maximilian Lebmeier
  • Dawn Lee

Abstract

Background: Evaluating long-term prognosis is important for physicians, patients and payers. This study reports the results of a model developed to predict long-term survival for UK patients receiving second-line ipilimumab. Methods: MDX010-20 trial data were used to predict survival for ipilimumab versus UK best supportive care. Two aspects of this analysis required novel approaches: 1) The overall survival Kaplan–Meier data shape is unusual: an initial steep decline is observed before a ‘plateau’. 2) The need to extrapolate beyond the trial end (4.6 years). Based upon UK clinician advice, a three-part curve fit was used: from 0–1.5 years, Kaplan–Meier data from the trial; from 1.5–5 years, standard parametric curve fits; after 5 years, long-term data from the American Joint Committee on Cancer registry. Results: This approach provided good internal validity: low mean absolute error and good match to median and mean trial data. Lifetime predicted means were 2.77 years for ipilimumab and 1.07 for best supportive care, driven by increased long-term survival with ipilimumab. Conclusion: To understand the full benefit of treatment and to meet reimbursement requirements, accurate estimation of treatment benefit is key. Models, such as the one presented, can be used to extrapolate beyond trials.

Suggested Citation

  • James Larkin & Anthony J Hatswell & Paul Nathan & Maximilian Lebmeier & Dawn Lee, 2015. "The Predicted Impact of Ipilimumab Usage on Survival in Previously Treated Advanced or Metastatic Melanoma in the UK," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-11, December.
    • Handle: RePEc:plo:pone00:0145524
    DOI: 10.1371/journal.pone.0145524
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    Cited by:

    1. Jonathan Dando & Maximilian Lebmeier, 2020. "A novel valuation model for medical intervention development based on progressive dynamic changes that integrates Health Technology Assessment outcomes with early-stage innovation and indication-speci," Journal of Innovation and Entrepreneurship, Springer, vol. 9(1), pages 1-28, December.
    2. Ash Bullement & Matthew D. Stevenson & Gianluca Baio & Gemma E. Shields & Nicholas R. Latimer, 2023. "A Systematic Review of Methods to Incorporate External Evidence into Trial-Based Survival Extrapolations for Health Technology Assessment," Medical Decision Making, , vol. 43(5), pages 610-620, July.
    3. Zhaojing Che & Nathan Green & Gianluca Baio, 2023. "Blended Survival Curves: A New Approach to Extrapolation for Time-to-Event Outcomes from Clinical Trials in Health Technology Assessment," Medical Decision Making, , vol. 43(3), pages 299-310, April.
    4. Yang Meng & Nadine Hertel & John Ellis & Edith Morais & Helen Johnson & Zoe Philips & Neil Roskell & Andrew Walker & Dawn Lee, 2018. "The cost-effectiveness of nivolumab monotherapy for the treatment of advanced melanoma patients in England," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(8), pages 1163-1172, November.

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