Mazumdar Madhu
Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, 307 E. 63rd St., 3rd floor, New York, NY 10021, USA.
Med Decis Making. 2004 Sep-Oct;24(5):525-33. doi: 10.1177/0272989X04269240.
Comparative diagnostic accuracy (CDA) studies are typically small retrospective studies supporting a higher accuracy for one modality over another for either staging a particular disease or assessing response to therapy, and they are used to generate hypotheses for larger prospective trials. The purpose of this article is to introduce the group sequential design (GSD) approach in planning these larger trials.
Methodology needed for using GSD in the CDA studies is recently developed. In this article, GSD with the O'Brien and Fleming (OBF) stopping rule is described and guidelines for sample size calculation are provided. Simulated data is used to demonstrate the application of GSD in the design/analysis of a clinical trial in the CDA study setting.
The expected sample size needed for planning a trial with GSD (under the OBF stopping rule) is slightly inflated but may ultimately result in greater savings of patient resources.
GSD is a specialized statistical method that is helpful in balancing the ethical and financial advantages of stopping a study early against the risk of an incorrect conclusion and should be adopted for planning CDA studies.
比较诊断准确性(CDA)研究通常是小型回顾性研究,旨在支持一种检查方式在对特定疾病进行分期或评估治疗反应方面比另一种方式具有更高的准确性,并且这些研究用于为更大规模的前瞻性试验生成假设。本文的目的是介绍在规划这些更大规模试验时的成组序贯设计(GSD)方法。
最近开发了在CDA研究中使用GSD所需的方法。本文描述了采用奥布赖恩和弗莱明(OBF)停止规则的GSD,并提供了样本量计算指南。使用模拟数据来证明GSD在CDA研究环境中临床试验的设计/分析中的应用。
采用GSD(在OBF停止规则下)规划试验所需的预期样本量略有增加,但最终可能会更大程度地节省患者资源。
GSD是一种专门的统计方法,有助于平衡提前终止研究的伦理和经济优势与得出错误结论的风险,在规划CDA研究时应采用该方法。