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作 者:王鸣岐 贾玉龙 王雨宁 李玲[1,2,3] 王雯 任燕[1,2,3] 姚明宏 孙鑫[1,2,3] WANG Mingqi;JIA Yulong;WANG Yuning;LI Ling;WANG Wen;REN Yan;YAO Minghong;SUN Xin(Chinese Evidence-based Medicine Center,West China Hospital,Sichuan University,Chengdu 610041,P.R.China;NMPA Key Laboratory for Real World Data Research and Evaluation in Hainan,Chengdu 610041,P.R.China;Sichuan Center of Technology Innovation for Real World Data,Chengdu 610041,P.R.China)
机构地区:[1]四川大学华西医院中国循证医学中心,成都610041 [2]国家药品监督管理局海南真实世界数据研究与评价重点实验室,成都610041 [3]四川省真实世界数据技术创新中心,成都610041
出 处:《中国循证医学杂志》2024年第5期605-611,共7页Chinese Journal of Evidence-based Medicine
基 金:国家自然科学基金项目(编号:82225049、72204173、82274368、71904134);四川省中央引导地方科技发展专项(编号:2022ZYD0127);中央级公益性科研院所基本科研业务费专项(编号:2020YJSZX-3)。
摘 要:高质量随机对照临床试验是评价药械有效性和安全性的金标准,但常需要花费大量的资源,难以为监管部门和医疗决策者提供即时证据,尤其是面对新发或突发的重大疾病。与此同时,随机对照试验因严格的设计限制,结果的外部效度较弱,难以提供药械在更广泛人群的临床疗效评价证据。相比之下,大规模简单临床试验(large simple trials,LST)可以缩短研究流程,降低研究花费,提供较好的外推性和可靠性证据。本文基于国内外有关LST的文献和监管部门的指导原则,介绍LST的发展、特点以及其与传统随机对照试验的区别,还有在进行LST时的特殊考虑。此外,本文还探讨了真实世界数据支持开展LST的前景,以期为相关研究者开展LST提供参考和借鉴。High-quality randomized controlled trials(RCTs)are regarded as the gold standard for assessing the efficiency and safety of drugs.However,conducting RCTs is expensive and time consumed,and providing timely evidence by RCTs for regulatory agencies and medical decision-makers can be challenging,particularly for new or emerging serious diseases.Additionally,the strict design of RCTs often results in a weakly external validity,making it difficult to provide the evidence of the clinical efficacy and safety of drugs in a broader population.In contrast,large simple clinical trials(LSTs)can expedite the research process and provide better extrapolation and reliable evidence at a lower cost.This article presents the development,features,and distinctions between LSTs and RCTs,as well as special considerations when conducting LSTs,in accordance with literature and guidance principles from regulatory agencies both from China and other countries.Furthermore,this paper assesses the potential of real-world data to bolster the development of LSTs,offering relevant researchers’insight and guidance on how to conduct LSTs.
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