Medical Consultancy Department,German Federal Joint Committee,Department of Health Care Management,Berlin University of
Medical Consultancy Department,German Federal Joint Committee.
Int J Technol Assess Health Care. 2017 Jan;33(1):103-110. doi: 10.1017/S0266462317000265. Epub 2017 May 15.
The aim of this study was to assess the quality of reporting sample size calculation and underlying design assumptions in pivotal trials of high-risk medical devices (MDs) for neurological conditions.
Systematic review of research protocols for publicly registered randomized controlled trials (RCTs). In the absence of a published protocol, principal investigators were contacted for additional data. To be included, trials had to investigate a high-risk MD, registered between 2005 and 2015, with indications stroke, headache disorders, and epilepsy as case samples within central nervous system diseases. Extraction of key methodological parameters for sample size calculation was performed independently and peer-reviewed.
In a final sample of seventy-one eligible trials, we collected data from thirty-one trials. Eighteen protocols were obtained from the public domain or principal investigators. Data availability decreased during the extraction process, with almost all data available for stroke-related trials. Of the thirty-one trials with sample size information available, twenty-six reported a predefined calculation and underlying assumptions. Justification was given in twenty and evidence for parameter estimation in sixteen trials. Estimates were most often based on previous research, including RCTs and observational data. Observational data were predominantly represented by retrospective designs. Other references for parameter estimation indicated a lower level of evidence.
Our systematic review of trials on high-risk MDs confirms previous research, which has documented deficiencies regarding data availability and a lack of reporting on sample size calculation. More effort is needed to ensure both relevant sources, that is, original research protocols, to be publicly available and reporting requirements to be standardized.
本研究旨在评估高风险医疗器械（MDs）用于神经系统疾病的关键试验中报告样本量计算和潜在设计假设的质量。
对已注册的随机对照试验（RCT）研究方案进行系统评价。在没有发表的方案的情况下，联系主要研究者以获取额外的数据。纳入标准为：研究高风险 MD，于 2005 年至 2015 年期间注册，以中风、头痛障碍和癫痫为中枢神经系统疾病的病例样本；独立提取关键方法学参数进行样本量计算，并进行同行评审。
在最终纳入的 71 项合格试验中，我们从 31 项试验中收集了数据。从公共领域或主要研究者处获得了 18 个方案。在提取过程中数据可用性下降，几乎所有中风相关试验的数据都可用。在有样本量信息的 31 项试验中，26 项报告了预先定义的计算和潜在假设。20 项提供了合理性依据，16 项提供了参数估计的证据。估计值最常基于先前的研究，包括 RCT 和观察性数据。观察性数据主要代表回顾性设计。其他参数估计的参考文献表明证据水平较低。
我们对高风险 MD 试验的系统评价证实了先前的研究，该研究记录了数据可用性和样本量计算报告方面的缺陷。需要做出更多努力，以确保原始研究方案等相关来源能够公开，并使报告要求标准化。
