集群随机对照试验的实际设计考虑:社区肿瘤学研究的经验教训。

Emily V Dressler, Stephanie L Pugh, Heather J Gunn, Joseph M Unger, David M Zahrieh, Anna C Snavely
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引用次数: 0

摘要

在国家癌症研究所(NCI)社区肿瘤学研究计划(NCORP)中进行的癌症护理交付研究试验通常在实践或提供者层面实施干预措施,需要使用集群随机对照试验(crct)。干预交付需要集群水平的随机化,而不是参与者水平的随机化,这影响了样本大小的计算和统计分析,以纳入实践中参与者之间的相关性。由于独特的试验网络基础设施,这些crct的实施存在实际挑战,包括参与者累计总数和比率不平等的可能性,以及分组错开的研究启动,随机分组之间可能存在差异。cRCT设计的执行可能是复杂的,例如,如果某些聚类没有累积参与者,则会发生意外的聚类水平交叉,如何最好地确定适当的聚类水平分层,随机化的时间和多水平资格标准考虑。本文分享了从3个NCORP crct中获得的潜在缓解策略的经验教训。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Practical design considerations for cluster randomized controlled trials: lessons learned in community oncology research.

Cancer care delivery research trials conducted within the National Cancer Institute (NCI) Community Oncology Research Program (NCORP) routinely implement interventions at the practice or provider level, necessitating the use of cluster randomized controlled trials (cRCTs). The intervention delivery requires cluster-level randomization instead of participant-level, affecting sample size calculation and statistical analyses to incorporate correlation between participants within a practice. Practical challenges exist in the conduct of these cRCTs due to unique trial network infrastructures, including the possibility of unequal participant accrual totals and rates and staggered study initiation by clusters, potentially with differences between randomized arms. Execution of cRCT designs can be complex, ie, if some clusters do not accrue participants, unintended cluster-level crossover occurs, how best to identify appropriate cluster-level stratification, timing of randomization, and multilevel eligibility criteria considerations. This article shares lessons learned with potential mitigation strategies from 3 NCORP cRCTs.

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