Confounding Factors in Exposure-Response Analyses and Mitigation Strategies for Monoclonal Antibodies in Oncology

2020 
Dose selection and optimization is an important topic in drug development to maximize treatment benefits for all patients. While exposure-response (E-R) analysis is a useful method to inform dose-selection strategy, in oncology, special considerations for prognostic factors are needed due to their potential to confound the E-R analysis for monoclonal antibodies. The current review focuses on three different approaches to mitigate the confounding effects for monoclonal antibodies in oncology: (1) cox-proportional hazards modeling and case-matching, (2) tumor growth inhibition-overall survival (TGI-OS) modeling, and (3) multiple dose level study design. In the presence of confounding effects, studying multiple dose levels may be required to reveal the true E-R relationship. However, it is impractical for pivotal trials in oncology drug development programs. Therefore, the strengths and weaknesses of the other two approaches are considered, and the favorable utility of TGI-OS modeling to address confounding in E-R analyses is described. In the broader scope of oncology drug development, this review discusses the downfall of the current emphasis on E-R analyses using data from single dose level trials, and proposes that development programs be designed to study more dose levels in earlier trials.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    0
    References
    0
    Citations
    NaN
    KQI
    []