{"title":"Patient-specific dose finding in seamless phase I/II clinical trials","authors":"M. Alam, Shantonu Islam Shanto","doi":"10.1080/07474946.2022.2105361","DOIUrl":null,"url":null,"abstract":"Abstract This article incorporates a covariate to determine the optimum dose in a seamless phase I/II clinical trial. A binary covariate and its interaction effect are assumed to keep the method simple. Each patient’s outcome is assumed to be trinomial, and the continuation ratio model is utilized to model the dose–response data. The Bayesian approach estimates parameters of the dose–response model. Eight plausible dose–response scenarios are investigated to check the proposed methodology. A simulation study shows that covariate consideration can enhance the identification of the optimum dose when it is appropriate to do.","PeriodicalId":48879,"journal":{"name":"Sequential Analysis-Design Methods and Applications","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sequential Analysis-Design Methods and Applications","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/07474946.2022.2105361","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
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Abstract
Abstract This article incorporates a covariate to determine the optimum dose in a seamless phase I/II clinical trial. A binary covariate and its interaction effect are assumed to keep the method simple. Each patient’s outcome is assumed to be trinomial, and the continuation ratio model is utilized to model the dose–response data. The Bayesian approach estimates parameters of the dose–response model. Eight plausible dose–response scenarios are investigated to check the proposed methodology. A simulation study shows that covariate consideration can enhance the identification of the optimum dose when it is appropriate to do.
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The purpose of Sequential Analysis is to contribute to theoretical and applied aspects of sequential methodologies in all areas of statistical science. Published papers highlight the development of new and important sequential approaches.
Interdisciplinary articles that emphasize the methodology of practical value to applied researchers and statistical consultants are highly encouraged. Papers that cover contemporary areas of applications including animal abundance, bioequivalence, communication science, computer simulations, data mining, directional data, disease mapping, environmental sampling, genome, imaging, microarrays, networking, parallel processing, pest management, sonar detection, spatial statistics, tracking, and engineering are deemed especially important. Of particular value are expository review articles that critically synthesize broad-based statistical issues. Papers on case-studies are also considered. All papers are refereed.
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