在观察性数据库中衡量药物的有效性：前景与风险。
Measuring effectiveness of drugs in observational databanks: promises and perils.
作者信息
Krishnan Eswar, Fries James F
机构信息
Division of Immunology, Department of Medicine, Stanford University, Palo Alto, CA, USA.
出版信息
Arthritis Res Ther. 2004;6(2):41-4. doi: 10.1186/ar1151. Epub 2004 Feb 5.
Abstract
Observational databanks have inherent strengths and shortcomings. As in randomized controlled trials, poor design of these databanks can either exaggerate or reduce estimates of drug effectiveness and can limit generalizability. This commentary highlights selected aspects of study design, data collection and statistical analysis that can help overcome many of these inadequacies. An international metaRegister and a formal mechanism for standardizing and sharing drug data could help improve the utility of databanks. Medical journals have a vital role in enforcing a quality checklist that improves reporting.
摘要
观察性数据库有其固有的优点和缺点。与随机对照试验一样，这些数据库设计不佳可能会夸大或降低药物疗效的估计值，并可能限制其普遍性。本评论重点介绍了研究设计、数据收集和统计分析的某些方面，这些方面有助于克服其中许多不足之处。一个国际元注册库以及标准化和共享药物数据的正式机制有助于提高数据库的效用。医学期刊在执行提高报告质量的清单方面起着至关重要的作用。
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