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首页> 外文期刊>Trials >Statistical design and analysis plan for an impact evaluation of an HIV treatment and prevention intervention for female sex workers in Zimbabwe: a study protocol for a cluster randomised controlled trial
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Statistical design and analysis plan for an impact evaluation of an HIV treatment and prevention intervention for female sex workers in Zimbabwe: a study protocol for a cluster randomised controlled trial

机译:统计设计和分析计划,对津巴布韦女性性工作者的艾滋病治疗和预防干预措施的影响评估:一项整群随机对照试验的研究方案

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Background Pragmatic cluster-randomised trials should seek to make unbiased estimates of effect and be reported according to CONSORT principles, and the study population should be representative of the target population. This is challenging when conducting trials amongst ‘hidden’ populations without a sample frame. We describe a pair-matched cluster-randomised trial of a combination HIV-prevention intervention to reduce the proportion of female sex workers (FSW) with a detectable HIV viral load in Zimbabwe, recruiting via respondent driven sampling (RDS). Methods We will cross-sectionally survey approximately 200 FSW at baseline and at endline to characterise each of 14 sites. RDS is a variant of chain referral sampling and has been adapted to approximate random sampling. Primary analysis will use the ‘RDS-2’ method to estimate cluster summaries and will adapt Hayes and Moulton’s ‘2-step’ method to adjust effect estimates for individual-level confounders and further adjust for cluster baseline prevalence. We will adapt CONSORT to accommodate RDS. In the absence of observable refusal rates, we will compare the recruitment process between matched pairs. We will need to investigate whether cluster-specific recruitment or the intervention itself affects the accuracy of the RDS estimation process, potentially causing differential biases. To do this, we will calculate RDS-diagnostic statistics for each cluster at each time point and compare these statistics within matched pairs and time points. Sensitivity analyses will assess the impact of potential biases arising from assumptions made by the RDS-2 estimation. Discussion We are not aware of any other completed pragmatic cluster RCTs that are recruiting participants using RDS. Our statistical design and analysis approach seeks to transparently document participant recruitment and allow an assessment of the representativeness of the study to the target population, a key aspect of pragmatic trials. The challenges we have faced in the design of this trial are likely to be shared in other contexts aiming to serve the needs of legally and/or socially marginalised populations for which no sampling frame exists and especially when the social networks of participants are both the target of intervention and the means of recruitment. The trial was registered at Pan African Clinical Trials Registry (PACTR201312000722390) on 9 December 2013.
机译:背景实用性整群随机试验应力求对疗效进行公正的估计,并根据CONSORT原则进行报告,并且研究人群应代表目标人群。在没有样本框架的“隐藏”人群中进行试验时,这具有挑战性。我们描述了一项联合艾滋病毒预防干预措施的配对配对整群随机试验,旨在通过在响应者驱动的抽样(RDS)中招募来减少津巴布韦具有可检测到的HIV病毒载量的女性性工作者(FSW)的比例。方法我们将在基线和终点对200个FSW进行横断面调查,以表征14个站点的每个站点。 RDS是链引用采样的一种变体,已被修改为近似随机采样。初步分析将使用“ RDS-2”方法来估计聚类汇总,并将采用Hayes和Moulton的“两步法”来调整各个级别混杂因素的影响估计,并进一步调整聚类基线患病率。我们将调整CONSORT以适应RDS。在没有可观察到的拒绝率的情况下,我们将比较匹配对之间的招聘过程。我们将需要调查特定集群的招聘或干预本身是否会影响RDS估算过程的准确性,从而可能导致差异性偏差。为此,我们将在每个时间点为每个群集计算RDS诊断统计信息,并在匹配的对和时间点内比较这些统计信息。敏感性分析将评估由RDS-2估算得出的假设所产生的潜在偏差的影响。讨论我们不知道有任何其他完整的实用集群RCT正在使用RDS招募参与者。我们的统计设计和分析方法旨在透明地记录参与者的招募情况,并允许评估研究对目标人群的代表性,这是实用试验的关键方面。我们在设计该试验时面临的挑战可能会在其他情况下共同解决,这些问题旨在满足没有抽样框架的法律和/或社会边缘化人群的需求,尤其是当参与者的社交网络都是目标人群时干预和招募手段。该试验已于2013年12月9日在泛非临床试验注册中心(PACTR201312000722390)注册。

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