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Protocol: a systematic review of studies developing and/or evaluating search strategies to identify prognosis studies

Corp, Nadia; Jordan, Joanne L.; Hayden, Jill A.; Irvin, Emma; Parker, Robin; Smith, Andrea; van der Windt, Danielle A.

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Jill A. Hayden

Emma Irvin

Robin Parker

Andrea Smith


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.

Journal Article Type Other
Acceptance Date Apr 10, 2017
Online Publication Date Apr 20, 2017
Publication Date 2017-12
Publicly Available Date May 26, 2023
Journal Systematic Reviews
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 6
Article Number 88
Keywords prognosis, search filter, performance, systematic review
Publisher URL


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