目的:临床试验数据库中的高质量数据输入对有用性至关重要,有效性,和研究结果的可复制性,因为它影响循证医学实践和未来的研究。我们的目标是评估试验注册中心自我报告数据的质量,并提出识别和评估数据质量的实用和系统的方法。
方法:我们检索了临床试验。政府在2000-2015年间进行介入性全膝关节置换术(TKA)试验。我们提取了必需的和可选的试验信息元素,并使用了CTG的变量定义。我们对框架的数据质量报告进行了文献综述,清单,以及医疗保健数据库中的违规行为概述。我们确定并评估了数据质量属性:一致性,准确度,完整性,和及时性。
结果:我们纳入了816项介入TKA试验。数据不规则性变化很大:0%到100%。不一致范围从0%到36%,最常见的非随机标记分配与"单组"分配试验设计相结合.不准确性范围从0%到100%。不完整性范围从0%到61%:61%完成的TKA试验没有报告其结果。关于及时性方面的违规行为:49%的试验是在开始日期后3个月以上注册的。
结论:我们发现注册的临床TKA试验的数据质量存在显著差异。审判赞助者应致力于确保他们提供的信息是可靠的,一致,最新的,透明和准确。CTG的用户在根据注册数据得出结论时需要至关重要。我们相信这种意识将增加有关已发表的文章和治疗方案的明智决定,包括复制和改进试验设计。
OBJECTIVE: High quality data entry in clinical trial databases is crucial to the usefulness, validity, and replicability of research findings, as it influences evidence-based medical practice and future research. Our aim is to assess the quality of self-reported data in trial registries and present practical and systematic methods for identifying and evaluating data quality.
METHODS: We searched ClinicalTrials.Gov for interventional total knee arthroplasty(TKA) trials between 2000-2015. We extracted required and optional trial information elements and used the CTG\'s variables\' definitions. We performed a literature review on data quality reporting on frameworks, checklists, and overviews of irregularities in healthcare databases. We identified and assessed data quality attributes: consistency, accuracy, completeness, and timeliness.
RESULTS: We included 816 interventional TKA trials. Data irregularities varied widely: 0% to 100%. Inconsistency ranged from 0% to 36%, most often non-randomized labeled allocation were combined with a \"single group\" assignment trial design. Inaccuracy ranged from 0% to 100%. Incompleteness ranged from 0% to 61%: 61% finished TKA trials did not report their outcome. As regard to irregularities in timeliness: 49% of the trials were registered more than 3 months after the start date.
CONCLUSIONS: We found significant variations in the data quality of registered clinical TKA trials. Trial sponsors should be committed to ensuring that the information they provide is reliable, consistent, up-to-date, transparent and accurate. CTG\'s users need to be critical when drawing conclusions based on the registered data. We believe this awareness will increase well-informed decisions about published articles and treatment protocols, including replicating and improving trial designs.