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Related Experiment Videos

Identifying the maximum safe dose: a multiple testing approach.

L A Hothorn1, D Hauschke

  • 1Department of Epidemiology and Biostatistics, University of California at San Francisco, USA.

Journal of Biopharmaceutical Statistics
|March 10, 2000
PubMed
Summary
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This study introduces a new statistical method for identifying the maximum safe dose (MAXSD) in clinical trials. The method prioritizes avoiding false negatives to ensure patient safety when determining safe dosage levels.

Area of Science:

  • Pharmacology
  • Biostatistics
  • Toxicology

Background:

  • Determining the maximum safe dose (MAXSD) is crucial for both clinical dose-finding and toxicological studies.
  • MAXSD is defined as the highest dose without a significant safety risk compared to a control.
  • Controlling false-negative errors is paramount in safety assessments.

Purpose of the Study:

  • To propose a novel multiple testing procedure for equivalence in many-to-one designs.
  • To establish a method for identifying MAXSD with a focus on controlling false-negative rates.
  • To present and discuss statistical tests for shifted and ratio hypotheses in dose-response safety evaluations.

Main Methods:

  • Development of a multiple testing procedure for equivalence in a many-to-one design.

Related Experiment Videos

  • Utilizing a priori ordered contrasts (shifted control vs. dose).
  • Defining an acceptable risk delta in advance for hypothesis testing.

    • Main Results:

    • The proposed procedure allows for the identification of MAXSD by controlling the false-negative error rate.
    • Statistical tests for both shifted and ratio hypotheses are presented.
    • The methodology is designed for scenarios where safety is the primary concern.

    Conclusions:

    • The developed statistical procedure effectively aids in identifying the maximum safe dose (MAXSD).
    • This approach enhances safety assessments in clinical trials by prioritizing the control of false-negative errors.
    • The method provides a robust framework for evaluating dose-related safety effects.