Abstract
The most widely used design for a Phase III comparative study for demonstrating the biosimilarity between a biosimilar product and a renovator biological product is the equivalence trial, whose aim is to show that the difference between two population means of a primary endpoint is less than a prespecified equivalence margin. A well-known sample size formula for the equivalence trial is given by n1 = kn2 n2 = (zα + zβ/2)2 ω2 (δ |μT - μR|)2 (1 + 1k). Since this formula is obtained based on the approximate power rather than the exact power, we investigate in this article the accuracy of the sample size formula. We conclude that the sample size formula is very conservative. Specifically, we show that the exact power based on the sample size calculated from the formula to have power is actually under some conditions. Therefore, the use of the sample size formula may cause a huge extra cost to biotechnology companies. We propose that the sample size should be calculated based on the exact power precisely and numerically. The R code to calculate the sample size numerically is provided in this article.
| Original language | English |
|---|---|
| Pages (from-to) | 1215-1224 |
| Number of pages | 10 |
| Journal | Journal of Biopharmaceutical Statistics |
| Volume | 24 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2014 Nov 2 |
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All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Pharmacology
- Pharmacology (medical)
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Sample size calculations for the development of biosimilar products. / Kang, Seung Ho; Kim, Yongjo.
In: Journal of Biopharmaceutical Statistics, Vol. 24, No. 6, 02.11.2014, p. 1215-1224.Research output: Contribution to journal › Article
TY - JOUR
T1 - Sample size calculations for the development of biosimilar products
AU - Kang, Seung Ho
AU - Kim, Yongjo
PY - 2014/11/2
Y1 - 2014/11/2
N2 - The most widely used design for a Phase III comparative study for demonstrating the biosimilarity between a biosimilar product and a renovator biological product is the equivalence trial, whose aim is to show that the difference between two population means of a primary endpoint is less than a prespecified equivalence margin. A well-known sample size formula for the equivalence trial is given by n1 = kn2 n2 = (zα + zβ/2)2 ω2 (δ |μT - μR|)2 (1 + 1k). Since this formula is obtained based on the approximate power rather than the exact power, we investigate in this article the accuracy of the sample size formula. We conclude that the sample size formula is very conservative. Specifically, we show that the exact power based on the sample size calculated from the formula to have power is actually under some conditions. Therefore, the use of the sample size formula may cause a huge extra cost to biotechnology companies. We propose that the sample size should be calculated based on the exact power precisely and numerically. The R code to calculate the sample size numerically is provided in this article.
AB - The most widely used design for a Phase III comparative study for demonstrating the biosimilarity between a biosimilar product and a renovator biological product is the equivalence trial, whose aim is to show that the difference between two population means of a primary endpoint is less than a prespecified equivalence margin. A well-known sample size formula for the equivalence trial is given by n1 = kn2 n2 = (zα + zβ/2)2 ω2 (δ |μT - μR|)2 (1 + 1k). Since this formula is obtained based on the approximate power rather than the exact power, we investigate in this article the accuracy of the sample size formula. We conclude that the sample size formula is very conservative. Specifically, we show that the exact power based on the sample size calculated from the formula to have power is actually under some conditions. Therefore, the use of the sample size formula may cause a huge extra cost to biotechnology companies. We propose that the sample size should be calculated based on the exact power precisely and numerically. The R code to calculate the sample size numerically is provided in this article.
UR - http://www.scopus.com/inward/record.url?scp=84910025405&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84910025405&partnerID=8YFLogxK
U2 - 10.1080/10543406.2014.941984
DO - 10.1080/10543406.2014.941984
M3 - Article
C2 - 25032735
AN - SCOPUS:84910025405
VL - 24
SP - 1215
EP - 1224
JO - Journal of Biopharmaceutical Statistics
JF - Journal of Biopharmaceutical Statistics
SN - 1054-3406
IS - 6
ER -