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Sample size justification in phase III/IV clinical trials

D Richardson¹, S Leurgans

¹AAASPS Data Management Center, Chicago, Ill. 60612, USA.

Neuroepidemiology

|May 21, 1998

Summary

Justifying sample size for clinical trials can be challenging due to unknown parameters. This study proposes a robust power analysis approach using a range of values for better funding acquisition and trial design.

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Area of Science:

Clinical Trials
Biostatistics
Medical Research

Background:

Sample size justification is crucial for clinical trial funding.
Standard sample size calculations rely on unknown parameters, risking misspecification.
This uncertainty complicates trial planning and funding acquisition.

Purpose of the Study:

To propose an alternative sample size justification method for clinical trials.
To advocate for a power analysis approach using a range of parameter values.
To demonstrate this method's utility in a secondary stroke prevention trial.

Main Methods:

Utilizing a power analysis framework.
Incorporating a range of plausible values for unknown parameters.
Applying the methodology to a real-world clinical trial scenario (secondary stroke prevention).

Main Results:

The proposed power analysis approach offers a more robust justification for sample size.
This method addresses the issue of parameter misspecification inherent in traditional calculations.
Demonstrated feasibility and potential benefits in the context of stroke prevention research.

Conclusions:

A power analysis approach using a range of parameter values provides a flexible and reliable method for sample size justification.
This strategy enhances the rigor of funding proposals and trial design.
Recommended for use in clinical trial planning, particularly when parameter uncertainty exists.

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