An investigation of the impact of futility analysis in publicly funded trials
An investigation of the impact of futility analysis in publicly funded trials
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DOI：
10.1186/1745-6215-15-61
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发表时间：
2014-02-17
期刊：
影响因子：
2.5
通讯作者：
Nicholl, Jon
中科院分区：
文献类型：
--
作者：
Sully, Benjamin G. O.;Julious, Steven A.;Nicholl, Jon
背景：公共资助的试验经常无法招募目标样本量或发现显著的阳性结果。适应性临床试验，可能会部分调解对这些问题并不经常应用。在本文中，我们探讨了潜在的一种形式的适应在临床试验-徒劳的分析-看看它是否有潜力，以提高公共资助的trials.Methods：结果数据从两个英国机构资助的试验，卫生技术评估（HTA）计划和英国医学研究理事会（MRC），收集。然后使用这些数据模拟每项试验，在招募50%至90%的患者后，使用条件把握度进行单次无效性分析。2002年至2008年招募的33项试验符合纳入标准。停止边界的条件功率的20%，30%和40%被认为是和结果包括试验成功停止的数量和患者数量saved.Results：纳入无效分析后，75%的患者已被招募可能会导致10项试验，这继续有负面的结果，正确地停止无效使用30%的停止边界。使用这些无效参数，所有试验中共有807例患者可能得到挽救。研究成功招募的比例也将从45%增加到64%。结论：在公共资助的试验中，无效性评估有可能提高效率，节省患者和降低成本。虽然在进行无效性评估时存在后勤问题，但我们建议研究者应尽可能在其试验设计中纳入无效性分析。
Background: Publicly funded trials regularly fail to recruit their target sample size or find a significant positive result. Adaptive clinical trials which may partly mediate against the problems are not often applied. In this paper we investigate the potential of a form of adaption in a clinical trial - a futility analysis - to see if it has potential to improve publicly funded trials.Methods: Outcome data from trials funded by two UK bodies, the Health Technology Assessment (HTA) programme and the UK Medical Research Council (MRC), were collected. These data were then used to simulate each trial with a single futility analysis using conditional power, undertaken after 50% to 90% of the patients had been recruited. Thirty-three trials recruiting between 2002 and 2008 met the inclusion criteria. Stopping boundaries of conditional powers of 20%, 30% and 40% were considered and outcomes included the number of trials successfully stopped and number of patients saved.Results: Inclusion of a futility analysis after 75% of the patients had been recruited would have potentially resulted in 10 trials, which went on to have negative results, correctly stopping for futility using a stopping boundary of 30%. A total of 807 patients across all the trials would potentially have been saved using these futility parameters. The proportion of studies successfully recruiting would also have increased from 45% to 64%.Conclusions: A futility assessment has the potential to increase efficiency, save patients and decrease costs in publicly funded trials. While there are logistical issues in undertaking futility assessments we recommend that investigators should aim to include a futility analysis in their trial design wherever possible.