Development and evaluation of a search filter to identify prognostic factor studies in Ovid MEDLINE

Elena Stallings*, Andrea Gaetano-Gil, Noelia Alvarez-Diaz, Ivan Solà, Jesús López-Alcalde, Daniel Molano, Javier Zamora

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Background: Systematic reviews (SRs) are valuable resources as they address specific clinical questions by summarizing all existing relevant studies. However, finding all information to include in systematic reviews can be challenging. Methodological search filters have been developed to find articles related to specific clinical questions. To our knowledge, no filter exists for finding studies on the role of prognostic factor (PF). We aimed to develop and evaluate a search filter to identify PF studies in Ovid MEDLINE that has maximum sensitivity.

Methods: We followed current recommendations for the development of a search filter by first identifying a reference set of PF studies included in relevant systematic reviews on the topic, and by selecting search terms using a word frequency analysis complemented with an expert panel discussion. We evaluated filter performance using the relative recall methodology.

Results: We constructed a reference set of 73 studies included in six systematic reviews from a larger sample. After completing a word frequency analysis using the reference set studies, we compiled a list of 80 of the frequent methodological terms. This list of terms was evaluated by the Delphi panel for inclusion in the filter, resulting in a final set of 8 appropriate terms. The consecutive connection of these terms with the Boolean operator OR produced the filter. We then evaluated the filter using the relative recall method against the reference set, comparing the references included in the SRs with our new search using the filter. The overall sensitivity of the filter was calculated to be 95%, while the overall specificity was 41%. The precision of the filter varied considerably, ranging from 0.36 to 17%. The NNR (number needed to read) value varied largely from 6 to 278. The time saved by using the filter ranged from 13–70%.

Conclusions: We developed a search filter for OVID-Medline with acceptable performance that could be used in systematic reviews of PF studies. Using this filter could save as much as 40% of the title and abstract screening task. The specificity of the filter could be improved by defining additional terms to be included, although it is important to evaluate any modification to guarantee the filter is still highly sensitive.

Original languageEnglish
Article number107
Number of pages9
JournalBMC Medical Research Methodology
Volume22
Issue number1
Early online date10 Apr 2022
DOIs
Publication statusPublished - Dec 2022

Bibliographical note

Funding Information:
This work has been partially funded by the SEXCOMPLEX project (grant number PIE16/00050) and Biomarkers in sepsis project (grant PI19/00481) form the Instituto de Salud Carlos III (Plan Estatal de I + D + i 2013–2016) and co-financed by the European Development Regional Fund. "A way to achieve Europe" (ERDF). These funding sources had no role in the conception, design, execution or decision to submit this work.

Publisher Copyright:
© 2022, The Author(s).

Keywords

  • Prognostic factor
  • Search filter
  • Systematic review

ASJC Scopus subject areas

  • Epidemiology
  • Health Informatics

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