A tutorial on sensitivity analyses in clinical trials: The what, why, when and how

Lehana Thabane, Lawrence Mbuagbaw, Shiyuan Zhang, Zainab Samaan, Maura Marcucci, Chenglin Ye, Marroon Thabane, Lora Giangregorio, Brittany Dennis, Daisy Kosa, Victoria Borg Debono, Rejane Dillenburg, Vincent Fruci, Monica Bawor, Juneyoung Lee, George Wells, Charles H. Goldsmith

    Research output: Contribution to journalReview articlepeer-review

    622 Citations (Scopus)

    Abstract

    Background: Sensitivity analyses play a crucial role in assessing the robustness of the findings or conclusions based on primary analyses of data in clinical trials. They are a critical way to assess the impact, effect or influence of key assumptions or variations - such as different methods of analysis, definitions of outcomes, protocol deviations, missing data, and outliers - on the overall conclusions of a study. The current paper is the second in a series of tutorial-type manuscripts intended to discuss and clarify aspects related to key methodological issues in the design and analysis of clinical trials. Discussion. In this paper we will provide a detailed exploration of the key aspects of sensitivity analyses including: 1) what sensitivity analyses are, why they are needed, and how often they are used in practice; 2) the different types of sensitivity analyses that one can do, with examples from the literature; 3) some frequently asked questions about sensitivity analyses; and 4) some suggestions on how to report the results of sensitivity analyses in clinical trials. Summary. When reporting on a clinical trial, we recommend including planned or posthoc sensitivity analyses, the corresponding rationale and results along with the discussion of the consequences of these analyses on the overall findings of the study.

    Original languageEnglish
    Article number92
    JournalBMC Medical Research Methodology
    Volume13
    Issue number1
    DOIs
    Publication statusPublished - 2013

    Bibliographical note

    Funding Information:
    This work was supported in part by funds from the CANNeCTIN programme.

    Keywords

    • Clinical trials
    • Robustness
    • Sensitivity analysis

    ASJC Scopus subject areas

    • Epidemiology
    • Health Informatics

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