Hargreaves James R, Fearon Elizabeth, Davey Calum, Phillips Andrew, Cambiano Valentina, Cowan Frances M
Centre for Evaluation Department for Social and Environmental Health Research, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London, WC1H 9SH, UK.
Research Department of Infection and Population Health, Institute of Epidemiology and Health Care, Faculty of Population Health Sciences, University College London, Gower Street, London, WC1E 6BT, UK.
Trials. 2016 Jan 5;17:6. doi: 10.1186/s13063-015-1095-1.
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).
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.
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.
实用性整群随机试验应致力于做出无偏倚的效应估计,并按照CONSORT原则进行报告,且研究人群应代表目标人群。在没有抽样框架的“隐蔽”人群中进行试验时,这具有挑战性。我们描述了一项配对整群随机试验,该试验采用一种联合HIV预防干预措施,以降低津巴布韦女性性工作者(FSW)中可检测到HIV病毒载量的比例,通过应答者驱动抽样(RDS)进行招募。
我们将在基线和终线时对约200名FSW进行横断面调查,以描述14个地点中的每一个。RDS是链式推荐抽样的一种变体,已被调整以近似随机抽样。主要分析将使用“RDS-2”方法来估计整群汇总,并将采用海斯和莫尔顿的“两步”方法来调整个体水平混杂因素的效应估计,并进一步针对整群基线患病率进行调整。我们将对CONSORT进行调整以适应RDS。在没有可观察到的拒绝率的情况下,我们将比较配对组之间的招募过程。我们需要调查整群特异性招募或干预本身是否会影响RDS估计过程的准确性,从而可能导致差异偏倚。为此,我们将在每个时间点为每个整群计算RDS诊断统计量,并在配对组和时间点内比较这些统计量。敏感性分析将评估由RDS-2估计所做假设引起的潜在偏倚的影响。
我们不知道有任何其他已完成的实用性整群随机对照试验使用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招募情况,并允许评估该研究对目标人群的代表性,这是实用性试验的一个关键方面。我们在该试验设计中面临的挑战可能在其他旨在满足法律和/或社会边缘化人群需求的背景下也会出现,这些人群没有抽样框架,特别是当参与者的社会网络既是干预目标又是招募手段时。该试验于2013年12月9日在泛非临床试验注册中心(PACTR201312000722390)注册。