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    Biases in study design, implementation, and data analysis that distort the appraisal of clinical benefit and ESMO-Magnitude of Clinical Benefit Scale (ESMO-MCBS) scoring

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    Authors
    Gyawali, B.
    de Vries, E. G. E.
    Dafni, U.
    Amaral, T.
    Barriuso, Jorge
    Bogaerts, J.
    Calles, A.
    Curigliano, G.
    Gomez-Roca, C.
    Kiesewetter, B.
    Oosting, S.
    Passaro, A.
    Pentheroudakis, G.
    Piccart, M.
    Roitberg, F.
    Tabernero, J.
    Tarazona, N.
    Trapani, D.
    Wester, R.
    Zarkavelis, G.
    Zielinski, C.
    Zygoura, P.
    Cherny, N. I.
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    Affiliation
    Department of Oncology, Queen's University, Kingston, Ontario, Canada
    Issue Date
    2021
    
    Metadata
    Show full item record
    Abstract
    Background: The European Society for Medical Oncology-Magnitude of Clinical Benefit Scale (ESMO-MCBS) is a validated, widely used tool developed to score the clinical benefit from cancer medicines reported in clinical trials. ESMO-MCBS scores assume valid research methodologies and quality trial implementation. Studies incorporating flawed design, implementation, or data analysis may generate outcomes that exaggerate true benefit and are not generalisable. Failure to either indicate or penalise studies with bias undermines the intention and diminishes the integrity of ESMO-MCBS scores. This review aimed to evaluate the adequacy of the ESMO-MCBS to address bias generated by flawed design, implementation, or data analysis and identify shortcomings in need of amendment. Methods: As part of a refinement of the ESMO-MCBS, we reviewed trial design, implementation, and data analysis issues that could bias the results. For each issue of concern, we reviewed the ESMO-MCBS v1.1 approach against standards derived from Helsinki guidelines for ethical human research and guidelines from the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use, the Food and Drugs Administration, the European Medicines Agency, and European Network for Health Technology Assessment. Results: Six design, two implementation, and two data analysis and interpretation issues were evaluated and in three, the ESMO-MCBS provided adequate protections. Seven shortcomings in the ability of the ESMO-MCBS to identify and address bias were identified. These related to (i) evaluation of the control arm, (ii) crossover issues, (iii) criteria for non-inferiority, (iv) substandard post-progression treatment, (v) post hoc subgroup findings based on biomarkers, (vi) informative censoring, and (vii) publication bias against quality-of-life data. Conclusion: Interpretation of the ESMO-MCBS scores requires critical appraisal of trials to understand caveats in trial design, implementation, and data analysis that may have biased results and conclusions. These will be addressed in future iterations of the ESMO-MCBS.
    Citation
    Gyawali B, de Vries EGE, Dafni U, Amaral T, Barriuso J, Bogaerts J, et al. Biases in study design, implementation, and data analysis that distort the appraisal of clinical benefit and ESMO-Magnitude of Clinical Benefit Scale (ESMO-MCBS) scoring. ESMO Open. 2021 Jun;6(3):100117.
    Journal
    ESMO Open
    URI
    http://hdl.handle.net/10541/624039
    DOI
    10.1016/j.esmoop.2021.100117
    PubMed ID
    33887690
    Additional Links
    https://dx.doi.org/10.1016/j.esmoop.2021.100117
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.esmoop.2021.100117
    Scopus Count
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