{"title":"具有剂量优化的自适应2/3期设计。","authors":"Cong Chen , Mo Huang , Xuekui Zhang","doi":"10.1016/j.cct.2025.108048","DOIUrl":null,"url":null,"abstract":"<div><div>FDA's Project Optimus initiative for oncology drug development emphasizes selecting a dose that optimizes both efficacy and safety. When an inferentially adaptive Phase 2/3 design with dose selection is implemented to comply with the initiative, the conventional inverse normal combination test is commonly used for Type I error control. However, indiscriminate application of this overly conservative test can lead to substantial increase in sample size and timeline delays, which undermines the appeal of the adaptive approach. This, in turn, frustrates drug developers regarding Project Optimus.</div><div>The inflation of Type I error depends on the probability of selecting a dose with better long-term efficacy outcome at end of the study based on limited follow-up data at dose selection. In this paper, we discuss the estimation of this probability and its impact on Type I error control in realistic settings. Incorporating it explicitly into the two methods we have proposed result in improved designs, potentially motivating drug developers to adhere more closely to an initiative that has the potential to revolutionize oncology drug development.</div></div>","PeriodicalId":10636,"journal":{"name":"Contemporary clinical trials","volume":"156 ","pages":"Article 108048"},"PeriodicalIF":1.9000,"publicationDate":"2025-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive phase 2/3 design with dose optimization\",\"authors\":\"Cong Chen , Mo Huang , Xuekui Zhang\",\"doi\":\"10.1016/j.cct.2025.108048\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>FDA's Project Optimus initiative for oncology drug development emphasizes selecting a dose that optimizes both efficacy and safety. When an inferentially adaptive Phase 2/3 design with dose selection is implemented to comply with the initiative, the conventional inverse normal combination test is commonly used for Type I error control. However, indiscriminate application of this overly conservative test can lead to substantial increase in sample size and timeline delays, which undermines the appeal of the adaptive approach. This, in turn, frustrates drug developers regarding Project Optimus.</div><div>The inflation of Type I error depends on the probability of selecting a dose with better long-term efficacy outcome at end of the study based on limited follow-up data at dose selection. In this paper, we discuss the estimation of this probability and its impact on Type I error control in realistic settings. Incorporating it explicitly into the two methods we have proposed result in improved designs, potentially motivating drug developers to adhere more closely to an initiative that has the potential to revolutionize oncology drug development.</div></div>\",\"PeriodicalId\":10636,\"journal\":{\"name\":\"Contemporary clinical trials\",\"volume\":\"156 \",\"pages\":\"Article 108048\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2025-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Contemporary clinical trials\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1551714425002423\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Contemporary clinical trials","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1551714425002423","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
FDA's Project Optimus initiative for oncology drug development emphasizes selecting a dose that optimizes both efficacy and safety. When an inferentially adaptive Phase 2/3 design with dose selection is implemented to comply with the initiative, the conventional inverse normal combination test is commonly used for Type I error control. However, indiscriminate application of this overly conservative test can lead to substantial increase in sample size and timeline delays, which undermines the appeal of the adaptive approach. This, in turn, frustrates drug developers regarding Project Optimus.
The inflation of Type I error depends on the probability of selecting a dose with better long-term efficacy outcome at end of the study based on limited follow-up data at dose selection. In this paper, we discuss the estimation of this probability and its impact on Type I error control in realistic settings. Incorporating it explicitly into the two methods we have proposed result in improved designs, potentially motivating drug developers to adhere more closely to an initiative that has the potential to revolutionize oncology drug development.
期刊介绍:
Contemporary Clinical Trials is an international peer reviewed journal that publishes manuscripts pertaining to all aspects of clinical trials, including, but not limited to, design, conduct, analysis, regulation and ethics. Manuscripts submitted should appeal to a readership drawn from disciplines including medicine, biostatistics, epidemiology, computer science, management science, behavioural science, pharmaceutical science, and bioethics. Full-length papers and short communications not exceeding 1,500 words, as well as systemic reviews of clinical trials and methodologies will be published. Perspectives/commentaries on current issues and the impact of clinical trials on the practice of medicine and health policy are also welcome.