Methodological search filters to identify prognosis studies: A systematic review of development and evaluation studies




Poster session 2 Thursday: Evidence synthesis - methods / improving conduct and reporting


Thursday 14 September 2017 - 12:30 to 14:00


All authors in correct order:

Corp N1, Jordan J1, Hayden J2, Irvin E3, Parker R4, Smith A5, van der Windt D1
1 Research Institute for Primary Care & Health Sciences, Keele University, UK
2 Department of Community Health & Epidemiology, Dalhousie University, Canada
3 Institute for Work & Health, Canada
4 W.K. Kellogg Health Sciences Library, Dalhousie University, Canada
5 Dalhousie University, Canada
Presenting author and contact person

Presenting author:

Joanne Jordan

Contact person:

Abstract text
Background: Research in prognosis is increasing as its importance is acknowledged in the context of a global rise in chronic health conditions and diseases. As literature on prognosis grows, there is increasing interest in prognostic systematic reviews to collate and synthesise research findings, especially to help inform effective clinical decision making and healthcare policy. A key element of any systematic review is a detailed, comprehensive search strategy. But, this is a challenge for prognosis research due to poor reporting and inconsistent use of existing indexing terms in electronic databases.
Objectives: A systematic review is being conducted to find and compare methodological search filters developed and evaluated to identify any of the 3 main types of prognosis studies: overall prognosis, prognostic factors, and prognostic [risk prediction] models.
Methods: Systematic review of primary studies that report the development and/or evaluation of methodological search filters designed to retrieve prognosis studies. Searches will be conducted of multiple electronic bibliographic databases, grey literature from relevant organisations and websites, contacting experts, citation tracking of key papers and checking reference lists of included papers. One reviewer will screen titles. Two reviewers will independently assess abstracts and full articles for inclusion and also conduct data extraction and quality assessment; any disagreements resolved by discussion or by a third reviewer if required. Filter characteristics and performance metrics reported in the included studies will be extracted and tabulated. To allow comparisons, filters will be grouped according to database, platform, type of prognosis study, and type of filter for which it was intended.
Results and Conclusion: Work on this systematic review will begin shortly. Details of all validated prognosis search filters and synthesised evidence on performance and applicability will be presented. These will inform the design of a search filter for different types of prognosis studies, and will support the work of Cochrane prognosis methods group in developing guidance for conducting prognosis reviews.