title: A Quantitative Method for Weight Selection in SGDDP.
abstract: Ethnic factors pose major challenge to evaluating the treatment effect of a new drug in a targeted ethnic (TE) population in emerging regions based on the results from a multiregional clinical trial (MRCT). To address this issue with statistical rigor, Huang et al. (2012) proposed a new design of a simultaneous global drug development program (SGDDP) which used weighted Z tests to combine the information collected from the nontargeted ethnic (NTE) group in the MRCT with that from the TE group in both the MRCT and a simultaneously designed local clinical trial (LCT). An important and open question in the SGDDP design was how to downweight the information collected from the NTE population to reflect the potential impact of ethnic factors and ensure that the effect size for TE patients is clinically meaningful. In this paper, we will relate the weight selection for the SGDDP to Method 1 proposed in the Japanese regulatory guidance published by the Ministry of Health, Labour and Welfare (MHLW) in 2007. Method 1 is only applicable when true effect sizes are assumed to be equal for both TE and NTE groups. We modified the Method 1 formula for more general scenarios, and use it to develop a quantitative method of weight selection for the design of the SGDDP which, at the same time, also provides sufficient power to descriptively check the consistency of the effect size for TE patients to a clinically meaningful magnitude.
authors.affiliation: a Office of Biostatistics, Center for Drug Evaluation, SFDA , Beijing , P. R . China.
authors.forename: Qin
authors.initials: Q
authors.lastname: Huang
authors.affiliation: b Biostatistics and Programming , Johnson & Johnson , Raritan, New Jersey , USA.
authors.forename: Gang
authors.initials: G
authors.lastname: Chen
authors.affiliation: b Biostatistics and Programming , Johnson & Johnson , Raritan, New Jersey , USA.
authors.forename: Zhilong
authors.initials: Z
authors.lastname: Yuan
authors.affiliation: c Department of Statistics , Penn State University, State College , Pennsylvania , USA.
authors.forename: Ying
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: b Biostatistics and Programming , Johnson & Johnson , Raritan, New Jersey , USA.
authors.forename: Judy
authors.initials: J
authors.lastname: Wenrich
mesh_terms: D000465:Algorithms; D002986:Clinical Trials as Topic / Q000331:legislation & jurisprudence / Q000706:statistics & numerical data; D003627:Data Interpretation, Statistical; D005006:Ethnicity / Q000706:statistics & numerical data*; D006801:Humans; D007564:Japan; D010601:Pharmacology, Clinical / Q000331:legislation & jurisprudence / Q000706:statistics & numerical data*; D012107:Research Design / Q000331:legislation & jurisprudence / Q000706:statistics & numerical data; D018401:Sample Size
keywords: Bridging; Drug development; Ethnic factors; MRCT; Weighted Z test