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Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Sample size calculation for the sequential parallel comparison design with binary endpoint using exact methods.

Guogen Shan¹, Yahui Zhang¹

¹Department of Biostatistics, University of Florida, Gainesville, FL, USA.

Journal of Applied Statistics

|February 14, 2025

Summary

This summary is machine-generated.

High placebo responses can derail drug trials. This study introduces an exact conditional approach for sample size calculation in sequential parallel comparison designs (SPCD), improving reliability for small to medium sample sizes and extreme response rates.

Keywords:

62K05 62L05 Binary endpoint exact approach placebo response sequential parallel comparison design

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Area of Science:

Clinical Trial Design
Biostatistics
Pharmaceutical Research

Background:

High placebo responses in clinical trials can obscure true drug efficacy, potentially leading to the failure of promising pharmaceutical candidates.
The sequential parallel comparison design (SPCD) is a strategy employed to mitigate the impact of high placebo responses.
Current statistical methods for binary outcomes in SPCD often rely on asymptotic distributions, which perform poorly in small to medium sample sizes.

Purpose of the Study:

To propose an exact conditional approach for sample size calculation in SPCD to address the limitations of asymptotic methods.
To ensure robust control of the type I error rate under an unconditional framework for clinical trial sample size determination.
To compare the performance of exact sample sizes with existing methods for SPCD and randomized parallel studies.

Main Methods:

Developed an exact conditional approach for sample size calculation.
Utilized existing test statistics to order the sample space for the exact calculation.
Compared proposed exact sample sizes with those derived from asymptotic methods and standard randomized parallel designs.

Main Results:

The proposed exact conditional approach effectively controls the type I error rate.
Exact sample size calculations demonstrate superior performance compared to asymptotic methods, particularly for small to medium sample sizes.
The method is also recommended for SPCD scenarios involving extreme response rates.

Conclusions:

The exact conditional approach provides a more reliable method for sample size calculation in SPCD, especially when dealing with limited participant numbers or unusual response rates.
This methodology enhances the statistical rigor of clinical trials employing SPCD, thereby increasing the likelihood of accurately assessing drug effectiveness.
Recommendations are made for the adoption of exact sample sizes in SPCD for small- to medium sample sizes and extreme response rate scenarios.