Corp Nadia, Jordan Joanne L, Hayden Jill A, Irvin Emma, Parker Robin, Smith Andrea, van der Windt Danielle A
Arthritis Research UK Primary Care Centre, Research Institute of Primary Care and Health Sciences, Keele University, Keele, Staffordshire, ST5 5BG, UK.
Department of Community Health & Epidemiology, Dalhousie University, 5790 University Avenue, Room 403, Halifax, NS, B3H 1V7, Canada.
Syst Rev. 2017 Apr 20;6(1):88. doi: 10.1186/s13643-017-0482-y.
Prognosis research is on the rise, its importance recognised because chronic health conditions and diseases are increasingly common and costly. Prognosis systematic reviews are needed to collate and synthesise these research findings, especially to help inform effective clinical decision-making and healthcare policy. A detailed, comprehensive search strategy is central to any systematic review. However, within prognosis research, this is challenging due to poor reporting and inconsistent use of available indexing terms in electronic databases. Whilst many published search filters exist for finding clinical trials, this is not the case for prognosis studies. This systematic review aims to identify and compare existing methodological filters developed and evaluated to identify prognosis studies of any of the three main types: overall prognosis, prognostic factors, and prognostic [risk prediction] models.
Primary studies reporting the development and/or evaluation of methodological search filters to retrieve any type of prognosis study will be included in this systematic review. Multiple electronic bibliographic databases will be searched, grey literature will be sought from relevant organisations and websites, experts will be contacted, and citation tracking of key papers and reference list checking of all included papers will be undertaken. Titles will be screened by one person, and abstracts and full articles will be reviewed for inclusion independently by two reviewers. Data extraction and quality assessment will also be undertaken independently by two reviewers with disagreements resolved by discussion or by a third reviewer if necessary. Filters' characteristics and performance metrics reported in the included studies will be extracted and tabulated. To enable comparisons, filters will be grouped according to database, platform, type of prognosis study, and type of filter for which it was intended.
This systematic review will identify all existing validated prognosis search filters and synthesise evidence about their applicability and performance. These findings will identify if current filters provide a proficient means of searching electronic bibliographic databases or if further prognosis filters are needed and can feasibly be developed for systematic searches of prognosis studies.
预后研究正在兴起,其重要性得到认可,因为慢性健康状况和疾病越来越普遍且成本高昂。需要进行预后系统评价来整理和综合这些研究结果,特别是为有效的临床决策和医疗政策提供信息。详细、全面的检索策略是任何系统评价的核心。然而,在预后研究中,由于电子数据库中报告不佳和可用索引词使用不一致,这具有挑战性。虽然存在许多已发表的用于查找临床试验的检索过滤器,但预后研究并非如此。本系统评价旨在识别和比较已开发和评估的现有方法学过滤器,以识别三种主要类型中的任何一种预后研究:总体预后、预后因素和预后[风险预测]模型。
报告开发和/或评估用于检索任何类型预后研究的方法学检索过滤器的原始研究将纳入本系统评价。将搜索多个电子文献数据库,从相关组织和网站获取灰色文献,联系专家,并对关键论文进行引文跟踪以及对所有纳入论文的参考文献列表进行检查。标题将由一人筛选,摘要和全文将由两名评审员独立审查以确定是否纳入。数据提取和质量评估也将由两名评审员独立进行,如有分歧将通过讨论解决,必要时由第三名评审员解决。将提取纳入研究中报告的过滤器特征和性能指标并制成表格。为了进行比较,过滤器将根据数据库、平台、预后研究类型以及其预期的过滤器类型进行分组。
本系统评价将识别所有现有的经过验证的预后检索过滤器,并综合关于其适用性和性能的证据。这些结果将确定当前的过滤器是否提供了一种有效的手段来搜索电子文献数据库,或者是否需要进一步的预后过滤器,以及是否可以为预后研究的系统检索开发可行的过滤器。