Matching-Adjusted Indirect Comparisons Applied for Comparative Efficacy of Haematologic Cancer Drugs within Health Economic Analysis

Bogdan Muresan

    Research output: ThesisThesis fully internal (DIV)

    223 Downloads (Pure)


    Despite clarity in the matching-adjusted indirect comparison (MAIC) methodological guidelines, more research was needed to better understand MAIC applicability in practice, its impact on health economic models, and the outlook of reimbursement agencies on submissions including MAICs.
    The aim of the current thesis was to evaluate how MAICs are used in practice to assess the comparative efficacy of haematologic cancer drugs for health economic modelling purposes.
    Methods Literature review studies were used to assess the underlying evidence of current treatment options for several haematologic cancer indications. MAICs were employed to indirectly compare the efficacy and safety of such treatments while accounting for the specificity of the underlying data. The MAIC findings were incorporated into a cost-effectiveness model and extrapolated over a lifetime span. Different extrapolation models were tested and compared to assess the best fit to the underlying survival curves.
    Literature shows that haematologic cancer treatments are mainly assessed in single-arm trials with few- to no head-to-head comparisons. While MAICs could close these evidence gaps, a lack of methodological uniformity in the way they are conducted in practice and their results reported could lead to biased or frail outcomes further being incorporated into health economic models. Extrapolation of such outcomes with suboptimal parametric curves could add to the compounding uncertainty and result into weak health technology assessment submissions.
    The current doctoral thesis is advocating for more standardized methodology and reporting standards through a timely reconciliation of the theoretical guidelines with the practical realities.
    Original languageEnglish
    QualificationDoctor of Philosophy
    Awarding Institution
    • University of Groningen
    • Postma, Maarten, Supervisor
    • Ouwens, Mario, Co-supervisor, External person
    Award date22-Mar-2023
    Place of Publication[Groningen]
    Publication statusPublished - 2023

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