[논문]Sample Size Calculations for the Development of Biosimilar Products Based on Binary Endpoints

Kang, Seung-Ho; Jung, Ji-Yong; Baik, Seon-Hye

doi:10.5351/csam.2015.22.4.389

Sample Size Calculations for the Development of Biosimilar Products Based on Binary Endpoints 원문보기

Communications for statistical applications and methods = 한국통계학회논문집, v.22 no.4, 2015년, pp.389 - 399

Kang, Seung-Ho (Department of Applied Statistics, Yonsei University) , Jung, Ji-Yong (Department of Applied Statistics, Yonsei University) , Baik, Seon-Hye (Department of Applied Statistics, Yonsei University)

Abstract ▼ AI-Helper

It is important not to overcalculate sample sizes for clinical trials due to economic, ethical, and scientific reasons. Kang and Kim (2014) investigated the accuracy of a well-known sample size calculation formula based on the approximate power for continuous endpoints in equivalence trials, which has been widely used for Development of Biosimilar Products. They concluded that this formula is overly conservative and that sample size should be calculated based on an exact power. This paper extends these results to binary endpoints for three popular metrics: the risk difference, the log of the relative risk, and the log of the odds ratio. We conclude that the sample size formulae based on the approximate power for binary endpoints in equivalence trials are overly conservative. In many cases, sample sizes to achieve 80% power based on approximate powers have 90% exact power. We propose that sample size should be computed numerically based on the exact power.

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문제 정의

In this paper, we studied the accuracy of sample size calculation formulae based on the approximate power for binary endpoints in equivalence trials. The risk difference, the log of the relative risk, and the log of the odds ratio were investigated.

제안 방법

In order to investigate how many sample size differences are produced by two different powers, the R code was made to compute sample sizes based on exact and approximate powers. Tables 4–6 display sample sizes needed to achieve 80% and 90% power using two different powers for risk difference, the log of the relative risk, and the odds ratio log, respectively.
The primary endpoint is often binary; therefore, it is important to investigate the accuracy of sample size calculation formulae for binary endpoints in equivalence trials. This paper extends the results of Kang and Kim (2014) to binary endpoints for three popular metrics: the risk difference, the log of the relative risk, and the log of the odds ratio.

이론/모형

Test statistics for each hypothesis can be constructed using the central limit theorem, Slutsky’s theorem, and the delta method.

후속연구

This paper proposes that sample sizes for binary endpoints in equivalence trials should be calculated based on the exact power. The R code to calculate the sample sizes based on the exact power is available from the authors upon request.

참고문헌 (16)

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상세보기
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상세보기
Chow, S. C. and Liu, J. P. (2010). Statistical assessment of biosimilar products, Journal of Biopharmaceutical Statistics, 20, 10-30.

상세보기
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상세보기
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상세보기
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상세보기
Kang, S. H. and Kim, Y. (2014). Sample size calculations for the development of biosimilar products. Journal of Biopharmaceutical Statistics, 24, 1215-1224.

상세보기
Li, Y., Liu, Q., Wood, P. and Johri, A. (2013). Statistical considerations in biosimilar clinical efficacy trials with asymmetrical margins, Statistics in Medicine, 32, 393-405.

상세보기
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상세보기
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상세보기
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상세보기
Wang, H., Chow, S. C. and Li, G. (2002). On sample size calculation based on odds ratio in clinical trials, Journal of Biopharmaceutical Statistics, 12, 471-483.

상세보기
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