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    Modelling the Survival Outcomes of Immuno-Oncology Drugs in Economic Evaluations: A Systematic Approach to Data Analysis and Extrapolation

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    Author
    Gibson, E; Koblbauer, I; Begum, N; Dranitsaris, G; Liew, D; McEwan, P; Monfared, AAT; Yuan, Y; Juarez-Garcia, A; Tyas, D; ...
    Date
    2017-12-01
    Source Title
    PharmacoEconomics
    Publisher
    ADIS INT LTD
    University of Melbourne Author/s
    Liew, Danny
    Affiliation
    Medicine and Radiology
    Metadata
    Show full item record
    Document Type
    Journal Article
    Citations
    Gibson, E., Koblbauer, I., Begum, N., Dranitsaris, G., Liew, D., McEwan, P., Monfared, A. A. T., Yuan, Y., Juarez-Garcia, A., Tyas, D. & Lees, M. (2017). Modelling the Survival Outcomes of Immuno-Oncology Drugs in Economic Evaluations: A Systematic Approach to Data Analysis and Extrapolation. PHARMACOECONOMICS, 35 (12), pp.1257-1270. https://doi.org/10.1007/s40273-017-0558-5.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/256820
    DOI
    10.1007/s40273-017-0558-5
    Abstract
    BACKGROUND: New immuno-oncology (I-O) therapies that harness the immune system to fight cancer call for a re-examination of the traditional parametric techniques used to model survival from clinical trial data. More flexible approaches are needed to capture the characteristic I-O pattern of delayed treatment effects and, for a subset of patients, the plateau of long-term survival. OBJECTIVES: Using a systematic approach to data management and analysis, the study assessed the applicability of traditional and flexible approaches and, as a test case of flexible methods, investigated the suitability of restricted cubic splines (RCS) to model progression-free survival (PFS) in I-O therapy. METHODS: The goodness of fit of each survival function was tested on data from the CheckMate 067 trial of monotherapy versus combination therapy (nivolumab/ipilimumab) in metastatic melanoma using visual inspection and statistical tests. Extrapolations were validated using long-term data for ipilimumab. RESULTS: Modelled PFS estimates using traditional methods did not provide a good fit to the Kaplan-Meier (K-M) curve. RCS estimates fit the K-M curves well, particularly for the plateau phase. RCS with six knots provided the best overall fit, but RCS with one knot performed best at the plateau phase and was preferred on the grounds of parsimony. CONCLUSIONS: RCS models represent a valuable addition to the range of flexible approaches available to model survival when assessing the effectiveness and cost-effectiveness of I-O therapy. A systematic approach to data analysis is recommended to compare the suitability of different approaches for different diseases and treatment regimens.

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