Suppr超能文献

对在涉及植入式心脏医疗设备的临床试验中实施的基于风险的监测方法的有效性评估。

An evaluation of the effectiveness of a risk-based monitoring approach implemented with clinical trials involving implantable cardiac medical devices.

作者信息

Diani Christopher A, Rock Angie, Moll Phil

机构信息

BIOTRONIK Inc., Lake Oswego, OR, USA.

出版信息

Clin Trials. 2017 Dec;14(6):575-583. doi: 10.1177/1740774517723589. Epub 2017 Aug 18.

Abstract

Background Risk-based monitoring is a concept endorsed by the Food and Drug Administration to improve clinical trial data quality by focusing monitoring efforts on critical data elements and higher risk investigator sites. BIOTRONIK approached this by implementing a comprehensive strategy that assesses risk and data quality through a combination of operational controls and data surveillance. This publication demonstrates the effectiveness of a data-driven risk assessment methodology when used in conjunction with a tailored monitoring plan. Methods We developed a data-driven risk assessment system to rank 133 investigator sites comprising 3442 subjects and identify those sites that pose a potential risk to the integrity of data collected in implantable cardiac device clinical trials. This included identification of specific risk factors and a weighted scoring mechanism. We conducted trend analyses for risk assessment data collected over 1 year to assess the overall impact of our data surveillance process combined with other operational monitoring efforts. Results Trending analyses of key risk factors revealed an improvement in the quality of data collected during the observation period. The three risk factors follow-up compliance rate, unavailability of critical data, and noncompliance rate correspond closely with Food and Drug Administration's risk-based monitoring guidance document. Among these three risk factors, 100% (12/12) of quantiles analyzed showed an increase in data quality. Of these, 67% (8/12) of the improving trends in worst performing quantiles had p-values less than 0.05, and 17% (2/12) had p-values between 0.05 and 0.06. Among the poorest performing site quantiles, there was a statistically significant decrease in subject follow-up noncompliance rates, protocol noncompliance rates, and incidence of missing critical data. Conclusion One year after implementation of a comprehensive strategy for risk-based monitoring, including a data-driven risk assessment methodology to target on-site monitoring visits, statistically significant improvement was seen in a majority of measurable risk factors at the worst performing site quantiles. For the three risk factors which are most critical to the overall compliance of cardiac rhythm management medical device studies: follow-up compliance rate, unavailability of critical data, and noncompliance rate, we measured significant improvement in data quality. Although the worst performing site quantiles improved but not significantly in some risk factors such as subject attrition, the data-driven risk assessment highlighted key areas on which to continue focusing both on-site and centralized monitoring efforts. Data-driven surveillance of clinical trial performance provides actionable observations that can improve site performance. Clinical trials utilizing risk-based monitoring by leveraging a data-driven quality assessment combined with specific operational procedures may lead to an improvement in data quality and resource efficiencies.

摘要

背景

基于风险的监测是美国食品药品监督管理局认可的一个概念,旨在通过将监测工作重点放在关键数据元素和高风险研究机构上,提高临床试验数据质量。百多力公司通过实施一项综合策略来实现这一目标,该策略通过运营控制和数据监测相结合的方式评估风险和数据质量。本出版物展示了数据驱动的风险评估方法与量身定制的监测计划结合使用时的有效性。

方法

我们开发了一个数据驱动的风险评估系统,对包括3442名受试者的133个研究机构进行排名,并识别那些对植入式心脏设备临床试验中收集的数据完整性构成潜在风险的机构。这包括识别特定风险因素和加权评分机制。我们对1年多来收集的风险评估数据进行趋势分析,以评估我们的数据监测过程与其他运营监测工作相结合的总体影响。

结果

对关键风险因素的趋势分析表明,观察期内收集的数据质量有所提高。三个风险因素——随访依从率、关键数据不可用率和不依从率,与美国食品药品监督管理局基于风险的监测指导文件密切相关。在这三个风险因素中,分析的100%(12/12)分位数显示数据质量有所提高。其中,表现最差的分位数中67%(8/12)的改善趋势的p值小于0.05,17%(2/12)的p值在0.05至0.06之间。在表现最差的机构分位数中,受试者随访不依从率、方案不依从率和关键数据缺失发生率有统计学意义的下降。

结论

在实施基于风险的监测综合策略(包括用于现场监测访视的数据驱动风险评估方法)一年后,在表现最差的机构分位数中,大多数可衡量的风险因素有统计学意义的改善。对于心律管理医疗器械研究整体合规性最关键的三个风险因素:随访依从率、关键数据不可用率和不依从率,我们测量到数据质量有显著改善。尽管在一些风险因素(如受试者损耗)方面,表现最差的机构分位数有所改善但不显著,但数据驱动的风险评估突出了现场和集中监测工作应继续关注的关键领域。对临床试验表现进行数据驱动的监测提供了可采取行动的观察结果,可改善机构表现。利用基于风险的监测,通过数据驱动的质量评估与特定运营程序相结合的临床试验,可能会提高数据质量和资源效率。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验