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Futility Monitoring in Clinical Trials

  1. Author:
    Ortega-Villa, Ana M [ORCID]
    Grieco, Megan C [ORCID]
    Rubenstein,Kevin [ORCID]
    Wang,Jing
    Proschan, Michael A [ORCID]

  2. Author Address

    Office of Biostatistics Research, National Institute of Allergy and Infectious Diseases, Bethesda, Maryland, USA., Axle Informatics, Bethesda, Maryland, USA., Clinical Monitoring Research Program Directorate, Frederick National Laboratory for Cancer Research, Frederick, Maryland, USA.,
    1. Year: 2025
    2. Date: Jun
  2. Journal: Statistics in Medicine
    1. 44
    2. 13-14
    3. Pages: e70157
  4. Type of Article: Article
  5. Article Number: e70157
  1. Abstract:

    At the beginning of a phase III clinical trial, there is great optimism. After all, the phase II trial results were encouraging. Then, early data from the phase III trial trend in the wrong way, but there is still an opportunity for the trend to reverse and become statistically significant by the end. At what point does optimism become denial of reality? How do we decide when a clinical trial is futile? What does futility even mean? This tutorial reviews different concepts and tools for evaluating futility, including conditional and predictive power, reverse conditional power, predicted interval plots, revised unconditional power, and beta spending functions. Published 2025. This article is a U.S. Government work and is in the public domain in the USA. Statistics in Medicine published by John Wiley & Sons Ltd.

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External Sources

  1. View Full Text
  2. DOI: 10.1002/sim.70157
  3. PMID: 40497544
  4. PMCID: PMC12153251

Library Notes

  1. Fiscal Year: FY2024-2025
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