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題名 Sample size requirements for evaluation of bridging evidence
作者 薛慧敏;劉仁沛;Chen, J. J.
Liu, Jen-Pei;Hsueh, Hueymiin;James J. Chen
關鍵詞 Extrapolation;Similarity;Equivalence limit;Hierarchical Model
日期 2002-12
上傳時間 19-Dec-2008 14:51:07 (UTC+8)
摘要 This paper addresses issues concerning methodologies on the sample size required for statistical evaluation of bridging evidence for a registration of pharmaceutical products in a new region. The bridging data can be either in the Complete Clinical Data Package (CCDP) generated during clinical drug development for submission to the original region or from a bridging study conducted in the new region after the pharmaceutical product was approved in the original region. When the data are in the CCDP, the randomized parallel dose-response design stratified to the ethnic factors and region will generate internally valid data for evaluating similarity concurrently between the regions for assessment of the ability of extrapolation to the new region. Formula for sample size under this design is derived. The required sample size for evaluation of similarity between the regions can be at least four times as large as that needed for evaluation of treatment effects only. For a bridging study conducted in the new region in which the data of the foreign and new regions are not generated concurrently, a hierarchical model approach to incorporating the foreign bridging information into the data generated by the bridging study is suggested. The sample size required is evaluated. In general, the required sample size for the bridging trials in the new region is inversely proportional to equivalence limits, variability of primary endpoints, and the number of patients of the trials conducted in the original region.
關聯 Biometrical Journal 44(8),969-981.
資料類型 article
DOI http://dx.doi.org/10.1002/bimj.200290008
dc.creator (作者) 薛慧敏;劉仁沛;Chen, J. J.zh_TW
dc.creator (作者) Liu, Jen-Pei;Hsueh, Hueymiin;James J. Chen-
dc.date (日期) 2002-12en_US
dc.date.accessioned 19-Dec-2008 14:51:07 (UTC+8)-
dc.date.available 19-Dec-2008 14:51:07 (UTC+8)-
dc.date.issued (上傳時間) 19-Dec-2008 14:51:07 (UTC+8)-
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/18150-
dc.description.abstract (摘要) This paper addresses issues concerning methodologies on the sample size required for statistical evaluation of bridging evidence for a registration of pharmaceutical products in a new region. The bridging data can be either in the Complete Clinical Data Package (CCDP) generated during clinical drug development for submission to the original region or from a bridging study conducted in the new region after the pharmaceutical product was approved in the original region. When the data are in the CCDP, the randomized parallel dose-response design stratified to the ethnic factors and region will generate internally valid data for evaluating similarity concurrently between the regions for assessment of the ability of extrapolation to the new region. Formula for sample size under this design is derived. The required sample size for evaluation of similarity between the regions can be at least four times as large as that needed for evaluation of treatment effects only. For a bridging study conducted in the new region in which the data of the foreign and new regions are not generated concurrently, a hierarchical model approach to incorporating the foreign bridging information into the data generated by the bridging study is suggested. The sample size required is evaluated. In general, the required sample size for the bridging trials in the new region is inversely proportional to equivalence limits, variability of primary endpoints, and the number of patients of the trials conducted in the original region.-
dc.format application/en_US
dc.language enen_US
dc.language en-USen_US
dc.language.iso en_US-
dc.relation (關聯) Biometrical Journal 44(8),969-981.en_US
dc.subject (關鍵詞) Extrapolation;Similarity;Equivalence limit;Hierarchical Model-
dc.title (題名) Sample size requirements for evaluation of bridging evidenceen_US
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1002/bimj.200290008en_US
dc.doi.uri (DOI) http://dx.doi.org/10.1002/bimj.200290008en_US