Cautionary note on regional consistency evaluation in multiregional clinical trials with binary outcomes

IF 1.3 4区 医学 Q4 PHARMACOLOGY & PHARMACY Pharmaceutical Statistics Pub Date : 2023-12-20 DOI:10.1002/pst.2358
Gosuke Homma
{"title":"Cautionary note on regional consistency evaluation in multiregional clinical trials with binary outcomes","authors":"Gosuke Homma","doi":"10.1002/pst.2358","DOIUrl":null,"url":null,"abstract":"Multiregional clinical trials (MRCTs) have become increasingly common during the development of new drugs to obtain simultaneous drug approvals worldwide. When planning MRCTs, a major statistical challenge is determination of the regional sample size. In general, the regional sample size must be determined as the sample size such that the regional consistency probability, defined as the probability of meeting the regional consistency criterion, is greater than a prespecified value. The Japanese Ministry of Health, Labour and Welfare proposed two criteria for regional consistency. Moreover, many researchers have proposed corresponding closed-form formulas for calculating regional consistency probabilities when the primary outcome is continuous. Although some researchers have argued that those formulas are also applicable to cases with binary outcomes, it remains questionable whether such an argument can be true. Based on simulation results, we demonstrate that the existing formulas are inappropriate for binary cases, even when the regional sample size is sufficiently large. To address this issue, we develop alternative formulas and use simulation to show that they provide accurate regional consistency probabilities. Furthermore, we present an application of our proposed formulas for an MRCT of advanced or metastatic clear-cell renal cell carcinoma.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pharmaceutical Statistics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/pst.2358","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0

Abstract

Multiregional clinical trials (MRCTs) have become increasingly common during the development of new drugs to obtain simultaneous drug approvals worldwide. When planning MRCTs, a major statistical challenge is determination of the regional sample size. In general, the regional sample size must be determined as the sample size such that the regional consistency probability, defined as the probability of meeting the regional consistency criterion, is greater than a prespecified value. The Japanese Ministry of Health, Labour and Welfare proposed two criteria for regional consistency. Moreover, many researchers have proposed corresponding closed-form formulas for calculating regional consistency probabilities when the primary outcome is continuous. Although some researchers have argued that those formulas are also applicable to cases with binary outcomes, it remains questionable whether such an argument can be true. Based on simulation results, we demonstrate that the existing formulas are inappropriate for binary cases, even when the regional sample size is sufficiently large. To address this issue, we develop alternative formulas and use simulation to show that they provide accurate regional consistency probabilities. Furthermore, we present an application of our proposed formulas for an MRCT of advanced or metastatic clear-cell renal cell carcinoma.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
二元结果多区域临床试验中区域一致性评价的注意事项
多区域临床试验(MRCT)在新药研发过程中越来越常见,目的是使新药在全球范围内同时获得批准。在规划多区域临床试验时,确定区域样本量是一项重大的统计挑战。一般来说,区域样本量必须确定为使区域一致性概率(定义为符合区域一致性标准的概率)大于预设值的样本量。日本厚生劳动省提出了两个地区一致性标准。此外,许多研究人员还提出了相应的封闭式公式,用于计算主要结果连续时的区域一致性概率。虽然有些研究者认为这些公式也适用于二元结果的情况,但这种说法是否成立仍值得商榷。根据模拟结果,我们证明现有公式不适合二元案例,即使区域样本量足够大。为了解决这个问题,我们开发了替代公式,并通过模拟证明它们能提供准确的地区一致性概率。此外,我们还介绍了我们提出的公式在晚期或转移性透明细胞肾细胞癌 MRCT 中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Pharmaceutical Statistics
Pharmaceutical Statistics 医学-统计学与概率论
CiteScore
2.70
自引率
6.70%
发文量
90
审稿时长
6-12 weeks
期刊介绍: Pharmaceutical Statistics is an industry-led initiative, tackling real problems in statistical applications. The Journal publishes papers that share experiences in the practical application of statistics within the pharmaceutical industry. It covers all aspects of pharmaceutical statistical applications from discovery, through pre-clinical development, clinical development, post-marketing surveillance, consumer health, production, epidemiology, and health economics. The Journal is both international and multidisciplinary. It includes high quality practical papers, case studies and review papers.
期刊最新文献
On Some Modeling Issues in Estimating Vaccine Efficacy Propensity Score Analysis With Baseline and Follow-Up Measurements of the Outcome Variable. Generalizing Treatment Effect to a Target Population Without Individual Patient Data in a Real-World Setting. Comparative Analyses of Bioequivalence Assessment Methods for In Vitro Permeation Test Data. Simultaneous Inference Using Multiple Marginal Models.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1