罕见暴露的灵活两阶段研究:新变体的可行性、计划和效率问题。

Pascal Wild, Nadine Andrieu, Alisa M Goldstein, Walter Schill
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引用次数: 2

摘要

两阶段设计包括已知疾病状态和廉价协变量信息的初始(第一阶段)研究。在最初的研究中,选择一个子样本来收集详细的协变量数据。与标准病例对照设计相比,两阶段研究已被证明是有效的。然而,如果不能在最稀有的类别中保证最小的样本量,或者很难重新接触受试者,就会出现潜在的问题。在具有廉价代理的罕见暴露的情况下,作者提出了灵活的两阶段设计,其中有一个单一的接触时间,在此时间内,根据代理做出关于全协变量确定的决定。对受试者进行筛选,直到选定所需数量的病例和对照以收集全部数据。提出了优化设计成本/效率的策略和相应的软件。该设计应用于职业流行病学和遗传流行病学的两个例子。通过确保最罕见疾病-协变量组合的最小数量,我们比标准的两期研究获得了相当大的效率收益,并提高了实际可行性。灵活的两阶段设计可能是设计的选择,在有针对性的研究罕见暴露的影响与廉价的代理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Flexible Two-Phase studies for rare exposures: Feasibility, planning and efficiency issues of a new variant.

Flexible Two-Phase studies for rare exposures: Feasibility, planning and efficiency issues of a new variant.

The two-phase design consists of an initial (Phase One) study with known disease status and inexpensive covariate information. Within this initial study one selects a subsample on which to collect detailed covariate data. Two-phase studies have been shown to be efficient compared to standard case-control designs. However, potential problems arise if one cannot assure minimum sample sizes in the rarest categories or if recontact of subjects is difficult. In the case of a rare exposure with an inexpensive proxy, the authors propose the flexible two-phase design for which there is a single time of contact, at which a decision about full covariate ascertainment is made based on the proxy. Subjects are screened until the desired numbers of cases and controls have been selected for full data collection. Strategies for optimizing the cost/efficiency of this design and corresponding software are presented. The design is applied to two examples from occupational and genetic epidemiology. By ensuring minimum numbers for the rarest disease-covariate combination(s), we obtain considerable efficiency gains over standard two-phase studies with an improved practical feasibility. The flexible two-phase design may be the design of choice in the case of well targeted studies of the effect of rare exposures with an inexpensive proxy.

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