Review ArticleUse of methodological search filters to identify diagnostic accuracy studies can lead to the omission of relevant studies
Introduction
Systematic reviews, regarded as the cornerstones of evidence-based medicine, are intended to identify and evaluate all available evidence about a specific topic. A systematic and comprehensive search for relevant primary studies is one of the essential steps in conducting a systematic review, and one of the factors that distinguishes a systematic review from a traditional narrative review.
To identify diagnostic accuracy studies in an electronic database, such as Medline, several search strategies can be used. Many of these strategies rely on free or text words and MeSH headings directed to disease indicators in combination with search terms for the diagnostic test. To further limit the search results, a methodological filter can be used, consisting of text words and MeSH headings directed to general indicators of diagnostic studies. In contrast to their use with intervention studies, however, these general indicators are not widely and systematically used as keywords for diagnostic studies, and indexing of original diagnostic accuracy studies is not flawless [1], [2], [3]. Diagnostic studies show more variability in study design than intervention studies. It is therefore not unlikely that a considerable number of relevant studies will be missed when those filters are used in diagnostic reviews, and the reduction in number of studies to consider for inclusion is far from impressive.
A number of these methodological search filters for diagnostic accuracy studies have been validated. They are known to differ in sensitivity (percentage correctly identified studies) and specificity (percentage correctly nonidentified studies). Our objective was to assess the usefulness of these search filters by applying them to a reference set derived from published systematic reviews in a broad range of clinical fields. First, the fraction of relevant studies that did not pass each filter was calculated. Then we determined whether the diagnostic search filters focus the search strategy enough to be practical.
Section snippets
Methods
To identify articles reporting on the development of diagnostic search filters, we performed a computerized search using the databases Medline, EMBASE and the Cochrane Methodology Register of the Cochrane Library, with an end date of January 2004. The search terms used in Medline, interface PubMed, were: “Medline[MeSH] OR “Information Storage and Retrieval/methods”[MeSH]) AND diagnosis.” The search terms for EMBASE, interface OVID, were ((search adj strategy).mp. or (search adj strategies).mp.)
Results
Our search strategy for diagnostic search filters revealed a total number of 781 articles from three databases: Medline 605, EMBASE 95, and Cochrane Methodology Register 81. Eight articles were included [4], [5], [6], [7], [8], [9], [10], [11]. These articles described a total of 28 validated diagnostic search filters. Two studies described one accurate filter each [7], [8], and these filters were both selected as accurate filters. One study did not report sensitivity or specificity, nor
Discussion
Diagnostic reviews aim to identify and evaluate all available evidence about a specific index test or a comparison of tests. If the yield of the initial search based on index test and target condition is too large, a diagnostic search filter could be helpful in reducing this number. We compared the performance of 12 validated diagnostic search filters by applying them to a set of articles, selected from the reference lists of 27 published diagnostic systematic reviews. All filters studied may
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