Bruhn Hanne, Treweek Shaun, Duncan Anne, Shearer Kirsty, Cameron Sarah, Campbell Karen, Innes Karen, McRae Dawn, Cotton Seonaidh C
Health Services Research Unit, University of Aberdeen, Health Sciences Building, Foresterhill, Aberdeen, UK.
CHaRT, University of Aberdeen, Health Sciences Building, Foresterhill, Aberdeen, UK.
Trials. 2019 Apr 3;20(1):192. doi: 10.1186/s13063-019-3287-6.
Multicentre randomised trials provide some of the key evidence underpinning healthcare practice around the world. They are also hard work and generally expensive. Some of this work and expense are devoted to sites that fail to recruit as many participants as expected. Methods to identify sites that will recruit to target would be helpful.
We asked trial managers at the Centre for Healthcare Randomised Trials (CHaRT), University of Aberdeen to predict whether a site would recruit to target. Predictions were made after a site initiation visit and were collected on a form comprising a simple 'Yes/No' prediction and a reason for the prediction. We did not provide guidance as to what trial managers might want to think about when making predictions. After a minimum of eight months of recruitment at each site for which a prediction had been made, all trial mangers in CHaRT were invited to a group discussion where predictions were presented together with sites' actual recruitment performance over that period. Individual trial managers reflected on their predictions and there was a general discussion about predicting site recruitment. The prediction reasons from the forms and the content of the group discussion were used to identify features linked to correct predictions of recruitment failure.
Ten trial managers made predictions for 56 site visits recruiting to eight trials. Trial managers' sensitivity was 82% and their specificity was 32%, correctly identifying 65% of sites that would hit their recruitment target and 54% of those that did not. Eight 'red flags' for recruitment failure were identified: previous poor site performance; slow approvals process; strong staff/patient preferences; the site recruitment target; the trial protocol and its implementation at the site; lack of staff engagement; lack of research experience among site staff; and busy site staff. We used these red flags to develop a guided prediction form.
Trial managers' unguided recruitment predictions were not bad but were not good enough for decision-making. We have developed a modified prediction form that includes eight flags to consider before making a prediction. We encourage anyone interested in contributing to its evaluation to contact us.
多中心随机试验提供了支撑全球医疗实践的一些关键证据。它们也是一项艰巨的工作，而且通常成本高昂。其中一些工作和成本投入到了那些未能招募到预期数量参与者的研究点。识别能够按目标招募参与者的研究点的方法会很有帮助。
我们请阿伯丁大学医疗保健随机试验中心（CHaRT）的试验管理者预测一个研究点是否会按目标招募。预测是在研究点启动访视后做出的，并记录在一份表格上，该表格包含一个简单的“是/否”预测以及预测的理由。我们没有就试验管理者在做预测时可能需要考虑的因素提供指导。在对每个做出预测的研究点进行至少八个月的招募后，CHaRT的所有试验管理者都被邀请参加一次小组讨论，在讨论中展示预测结果以及该时期各研究点的实际招募表现。每位试验管理者反思他们的预测，并且就预测研究点招募情况进行了一般性讨论。利用表格中的预测理由和小组讨论的内容来识别与正确预测招募失败相关的特征。
十位试验管理者对招募八项试验的56次研究点访视做出了预测。试验管理者的敏感度为82%，特异度为32%，正确识别出65%能达到招募目标的研究点以及54%未达目标的研究点。识别出了八个招募失败的“警示信号”：既往研究点表现不佳；审批流程缓慢；工作人员/患者偏好强烈；研究点招募目标；试验方案及其在研究点的实施情况；工作人员参与度不足；研究点工作人员缺乏研究经验；以及研究点工作人员繁忙。我们利用这些警示信号开发了一份有指导的预测表格。
试验管理者无指导的招募预测不算差，但对决策而言还不够好。我们开发了一种经过改进的预测表格，其中包括在做出预测前要考虑的八个警示信号。我们鼓励任何有兴趣参与其评估的人联系我们。
