Statistical assessment of biosimilarity based on the relative distance between follow-on biologics for binary endpoints.
A new three-arm parallel design was recently proposed to investigate the biosimilarity between a biological product and a reference product by using the relative distance. The purpose of this article is to extend their results to binary endpoints for three popular metrics: the risk difference, the log relative risk, and the log odds ratio. The relative distances based on the three metrics are defined, and corresponding test procedures are developed. The type I error rates and powers are investigated theoretically and empirically.
a Department of Applied Statistics , Yonsei University , Seoul , Korea.
Wooyoung
W
Shin
a Department of Applied Statistics , Yonsei University , Seoul , Korea.
Seung-Ho
SH
Kang
D000465:Algorithms; D059451:Biosimilar Pharmaceuticals / Q000008:administration & dosage / Q000493:pharmacokinetics / Q000627:therapeutic use*; D023381:Endpoint Determination / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D016017:Odds Ratio; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D012107:Research Design / Q000706:statistics & numerical data*; D013810:Therapeutic Equivalency
D059451:Biosimilar Pharmaceuticals
Equivalence trial; log odds ratio; log relative risk; power; risk difference; sample size formula