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6 Searching forand selecting studies
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plan to minimize the risk of missing potentially relevant studies for Cochrane Reviews
of diagnostic test accuracy. Further evidence is needed on the impact on accuracy
estimates of extensive compared to restrictive searching for studies of test accuracy.
Most of the main subject- specific databases are only available on a subscription or
‘pay- as- you- go’ basis. Access may therefore be limited to those databases that are
available through review authors’ institutions or medical libraries. Some of the main
subject- specific databases are listed in the online technical supplement of the Cochrane
Handbook for Systematic Reviews of Interventions and an extensive list is given in the
supplementary appendix of resources (Lefebvre 2021). Some subject- specific databases with relevant studies for syntheses of test accuracy are accessible to search for
free.For physiotherapists, there is a subject- specific database of primary studies and
systematic reviews of test accuracy related to physiotherapy practice (DiTA; www.dita.
org.au) (Kaizik 2019, Kaizik 2020).
During the COVID-
19 pandemic other sources such as online COVID- 19data sets or
research repositories emerged as potentially useful sources of studies relevant to
syntheses of test accuracy being conducted in response to COVID- 19. Examples
include the Cochrane COVID- 19 Study Register (www.covid- 19.cochrane.org), the
WHO database of global literature on COVID- 19 (search.bvsalud.org/global-literatureon-novel-coronavirus-2019-ncov/), the Epistemonikos Foundation COVID- 19 Living
Overview of Evidence (L- OVE; www.app.iloveevidence.com/topics) and the COVID- 19
Living Evidence database (www.ispmbern.github.io/covid- 19/living- review) from the
University of Bern.
6.3.1.4 Dissertations andtheses databases
Some studies have found that dissertations and theses are more likely to be published
in a journal article if the results are positive (Smart1964, Vogel 2000, Zimpel 2000) and
that, on average, dissertations that remain unpublished have lower effect sizes than the
published literature (Smith1980). It is not yet known whether dissertations about test
accuracy research follow a similar publication pattern, but to minimize possible effects
of publication bias, review authors should consider searching for dissertations and theses. Specific databases for theses and dissertations include Open Access Theses and
Dissertations (OATD; www.oatd.org), ProQuest Dissertations and Theses Global (PQDT;
www.about.proquest.com/en/products- services/pqdtglobal) and DART- Europe (www.
dart- europe.eu/basic- search.php). Some subject- specific databases, including CINAHL
and PsycINFO, also index dissertations relevant to their respective fields (Lefebvre
2021). A list of selected dissertations and theses can be found in Section1.1.5 of the
online technical supplement of the Cochrane Handbook for Systematic Reviews of
Interventions (Lefebvre 2021).
6.3.2 Additional sources tosearch
Even a very sensitive search strategy may miss a proportion of relevant studies indexed
in general biomedical databases. Studies may not have been indexed correctly, may not
have an informative title and abstract (Cohen 2019) or may not (yet) be formally
published at all. Additional methods to identify studies, such as checking references
(see Section6.3.2.1), handsearching (see Section 6.3.2.2), forward citation searching
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and co- citation searches (see Section6.3.2.3), web search engines (see Section6.3.2.4),
grey literature databases and preprint servers (see Section 6.3.2.5), trial registries
(see Section 6.3.2.6) and more informal sources (see Section6.3.2.7) may therefore
need to be considered.
6.3.2.1 Related reviews, guidelines andreference lists assources ofstudies
Checking the reference lists of primary studies (particularly those identified for inclusion in the review) and of existing reviews and meta- analyses can be an effective
method of identifying additional studies (Greenhalgh 2005, Bayliss 2007, Horsley 2011).
Whiting (2008) found that the majority of relevant test accuracy studies not found from
database searches were identified by checking reference lists. Preston (2015) found
that in a convenience sample of nine Health Technology Assessment systematic reviews
of test accuracy, of the 46 (15%) included studies not retrieved by the published searches
of MEDLINE and Embase, 24 (8%) could be found by checking the reference lists of the
included studies. Reference lists also point to reviews and discussion articles on the
subject or closely related topics (Devillé 2002a, Devillé 2002b). It may also be helpful to
update and rerun the electronic search if additional search terms are identified from
studies discovered from these other sources.
Guidelines or other guidance assessing diagnostic tests, such as Health Technology
Assessments, may also prove useful as sources of studies, for example the Diagnostics
Guidance produced by the UK National Institute for Health and Care Excellence (www.
nice.org.uk/guidance/published?ngt=Diagnostics%20guidance&ndt=Guidance).
Sources of reviews, guidelines and other guidance are listed in the online technical
supplement of the Cochrane Handbook for Systematic Reviews of Interventions and
added to in the supplementary appendix of resources (Lefebvre 2021).
Handsearching
6.3.2.2
Handsearching is the systematic screening of the contents of every issue of a relevant
journal published within a defined time period. Evidence from one study suggests that
handsearching for systematic reviews of test accuracy with well- constructed search
strategies may not identify additional studies if the index test is well defined and study
records are consistently assigned a database indexing term (Glanville 2012). The
expected benefits from handsearching must be offset against the time and resources
required to do it well. Handsearching may be best justified in cases where a key journal
likely to be of interest is not indexed in the major bibliographic databases.
6.3.2.3 Forward citation searching andco- citation searching
Forward citation searching or ‘forward snowballing’ looks for studies that have cited
one or more key articles of interest to a review question. Forward citation searching can
provide a means of identifying additional relevant studies or, like the “See All Similar
Articles” option in PubMed and the “Find Similar” option in Ovid, can be a useful tool
when building a set of relevant articles to help design and test a search strategy. A number of online resources allow forward citation searching, including Web of Science and
Scopus (both of which require a paid subscription) and Google Scholar (which is available free of charge). Evidence on the added value of these search strategies in systematic reviews of test accuracy is currently lacking.
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Co- citation is a method designed to find articles that might be of interest because
they are frequently cited together in reference lists of other articles. It is different from
forward citation searching. For example, an eligible study A is cited by studies C, D and
E. Another study B is also cited by studies C, D and E. Study A and B have a co- citation
relationship. Some studies are co- cited more frequently than others and can be ranked
accordingly. For example, CoCites (www.cocites.com) is a novel interface for searching
within PubMed that not only retrieves the 100most recent citations of an article of
interest, but also extracts all other titles in their respective reference lists, counting how
often each title appears and ranking results by frequency (Janssens 2020). It has been
noted that some types of studies, particularly grey literature such as conference proceedings and studies in progress, cannot reliably be identified using citation analysis
methods. This may be because authors rarely cite them or the citation databases do not
index them, making these methods susceptible to publication bias (Belter 2016).
Citation analysis methods should not be used to replace database searching for test
accuracy studies. It is not known whether citation analysis methods, when used as an
adjunct to database searching, may identify additional test accuracy studies for
Cochrane systematic reviews.
Web searching
6.3.2.4
Searching the web in a systematic way for test accuracy studies is challenging. It is likely
to involve using general search engines, such as Google Search, and accessing selected
websites likely to cover relevant topics, such as those belonging to charitable organizations, research funders, diagnostic test manufacturers or regulatory agencies, health
technology assessment agencies, test accuracy research groups and other professional
societies. These resources are usually not designed to enable advanced search techniques for retrieving potentially relevant studies from within their wide range of content
and so are problematic to search efficiently. There is, however, some evidence that eligible and even ‘unique’ studies, not identified by other search methods, can be found
by web searching (Eysenbach 2001, Ogilvie 2005, Stansfield 2014, Godin 2015, Bramer
2017). When using search engines, review authors need to be aware that search results
can be personalized, for example when logged in to Google, and efforts should be made
to ensure that searches are as reproducible as possible by ‘logging out’ prior to carrying
out searches.
Google Scholar, a specialized version of Google Search, offers a way of searching the
scholarly literature on the web, including published and grey literature. It can be a useful tool to use alongside bibliographic database searching, not just for citation searching but also for the option to search the full text of studies, an advantage in tracking
down studies not indexed in, or not retrieved by searches of, bibliographic databases.
Some evidence indicates that using Google Scholar can identify unique studies using
similar or the same search terms as used in bibliographic databases (Bramer 2017). At
the same time, empirical work has particularly highlighted Google Scholar for the lack
of reproducibility of searches that could not be explained by ‘natural’ database growth
(Gusenbauer 2020). Although web searching has its challenges, as already outlined, it
has potential usefulness as a supplement to the other types of searching, but should
not be used as the single source for a systematic review of test accuracy. More detail on
web searching methods and a list of search engines can be found in Section1.3.5 of the
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online technical supplement of the Cochrane Handbook for Systematic Reviews of
Interventions (Lefebvre 2021).
Although internet searches are increasingly used as a resource for systematic reviews,
reporting standards are generally poor and a number of authors have provided guidance to improve the transparency and reproducibility of internet searches (e.g.
Briscoe2015). Options include saving a local electronic copy with details about any possibly relevant study found. Notetaking software such as Evernote or OneNote, or website logging software such as Zotero, should be used in preference to ‘bookmarking’ the
site in case the record of the study is removed or altered at a later stage. Briscoe (2015)
suggests that in addition to this type of record- keeping, a minimum set of information
should be recorded both for websites (name, URL, dates searched, search terms, including any specific sections searched and results) and for specific search engines (name,
dates searched, search terms, and how the results were selected).
Grey literature databases
6.3.2.5
Grey literature generally refers to documents that are not formally published in accessible sources such as books or journals. Examples may be conference abstracts, reports
by non- governmental organizations, policy briefs, national registries, etc. Grey literature has been shown to contribute about 10% of the studies referenced in Cochrane
systematic reviews of intervention (Mallett 2002). Grey literature is more likely to concern studies reporting non- significant results than are healthcare journal articles
(McAuley 2000, Hopewell 2005, Hopewell 2007). Thus, failure to include studies from
the grey literature may threaten the validity of a systematic review. More research is
needed across a range of diagnostic accuracy topic areas to determine whether studies of diagnostic accuracy exhibit similar publication biases (Brazzelli 2009, Wilson
2015, Korevaar 2016); there are some indications that this may be the case for imaging
studies (Brazzelli 2009).
Forms of grey literature that have become more accessible in recent years are preprints and open access archives. These reports are accessible through the websites and
preprint databases of commercial publishers (e.g. medRxiv, bioRxiv or SSRN), but also
through open access platforms, such as Zenodo and OpenScience framework (www.osf.
io). The status of these reports may vary, from first drafts with typos and mistakes to
peer- reviewed manuscripts almost ready to be formally published. Review authors
need to be aware of the level of rigour of the preprints that are retrieved and should
keep track of version numbers, as information is subject to change. It is advisable to
check the latest version and contact authors of any selected preprints deemed eligible
for inclusion in the review before submitting the review for publication.
6.3.2.6 Trial registries
Awareness of the existence of a possibly relevant ongoing study can affect decisions
about when to conduct or update a review. Information on research projects in progress, as well as completed project records that may contain study results or references
to publications, can be found in online registers maintained by professional associations or national governments. No single, central register of ongoing test accuracy evaluations currently exists, but such studies are increasingly being included in existing
trials registers (Hooft 2011) and regulatory agency data sets. A website listing some key
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registers and how to search them is available at sites.google.com/a/york.ac.uk/
yhectrialsregisters/home.
For Cochrane Reviews, information about possible relevant ongoing studies should
be included in the ‘Characteristics of ongoing studies’ table.
6.3.2.7 Contacting colleagues, study authors andmanufacturers
Colleagues can be an important source of information about unpublished studies and
informal channels of communication may be the only means of identifying unpublished
data. Authors of relevant studies or other experts in the field may know about completed but unpublished studies (Reveiz 2006). Conference reports on topics of interest
may be a source of potential authors and experts. One approach is to send a request for
information to the contact author of reports of included studies, together with a list of
relevant articles already identified and the eligibility criteria for the review, and ask
whether they know of additional studies (published, unpublished or ongoing) that
might be relevant. A similar request could be sent to test manufacturers.
6.4 Designing search strategies
Searches for test accuracy studies are often more challenging to design compared to
searches for randomized controlled trials of interventions. Not all databases have
subject headings for measures of accuracy or publication- type indexing for test accuracy studies. Where those are available, they may not always be applied consistently
or have been available for a long period of time (Gurung 2020). For example, the
methodological MeSH terms ‘Sensitivity and Specificity’, introduced to MEDLINE in
1991, may refer to test accuracy measures, but may also refer to the lowest concentration that can be measured of a certain compound (Wilczynski 1995). Authors also do
not consistently report measures of accuracy in article titles and abstracts, and older
studies are less likely to contain abstracts, which reduces the efficiency of indexing
and text word searching and can lead to missed studies (Doust 2005, Leeflang 2006,
Ritchie 2007).
Cases of incomplete reporting of test accuracy studies, a lack of relevant indexing
terms in some databases and variation in applying existing indexing terms may all contribute to low search recall (see Section6.4.7). Multi- stranded approaches to searching
may be needed, which in turn may lower precision. Search strategies may also pass
through many iterations as the information specialist tests out different approaches to
achieve the best balance between search recall and precision.
The initial set of search terms used to develop a draft search strategy will be informed
by discussions between the information specialist and other review authors with
clinical or topic expertise, and by the information specialist’s knowledge and expertise.
A number of other techniques can be used to build up a set of candidate search terms
(Lefebvre 2013, Lefebvre 2021). Putting together a set of known relevant studies is a
good starting point. Searching each database for this set of known studies can identify
relevant subject indexing and may be particularly useful when the test name is not
standardized or to capture all components of a composite test. Relevant studies
‘missed’ by the preliminary searches should be searched for using the author names,
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terms from the title or other bibliographic data. If a ‘missed’ study is found, its subject
headings and text words can be noted and any that are deemed potentially useful can
be incorporated into the search strategy.
Usually, a series of preliminary searches using a range of subject headings and text
words is conducted and records for retrieved studies are examined to identify relevant
text words and their variants (synonyms, abbreviations, spelling variants, common misspellings) as well as subject headings assigned by the database indexers. Some database search interfaces have a facility for mapping keyword searches to subject headings
(see Section6.3.1.1), and tools such as PubMed PubReMiner (www.hgserver2.amc.nl/
cgi- bin/miner/miner2.cgi) and the Yale MeSH Analyzer (www.mesh.med.yale.edu) can
also help to identify MeSH from known relevant records.
After adding terms, it may be necessary to test the search strategy to ensure it is
achieving an appropriate balance of recall and precision. The set of known relevant
studies that would be expected to be retrieved can be used to test the recall of the
search and to check how these studies have been indexed in different databases.
During these preliminary searches, it is important to note which topic concepts are
being described by the authors and captured by the database indexers so that the
structure of the search strategy can be designed to maximize retrieval of relevant
studies.
This iterative process can be followed to identify a wide range of search terms and the
key concepts of the research topic.
6.4.1 Structuring thesearch strategy
Chapter 5 outlines the essential components or ‘concepts’ of a review question.
Information specialists need to have a good understanding of these key concepts to
allow them to identify the most useful concepts to include in a search strategy. It is not
usually necessary to search on every aspect of the review question, as some concepts
may not appear in article titles or abstracts or may not be well indexed with subject
headings (van der Weijden 1997, Fielding 2002, Vincent 2003, Korevaar 2015). Depending
on the complexity of the topic(s) and/or the complexity of the ways in which the topic(s)
are described in records, one or more search strategies may be developed.
●
A single- stranded approach based on a single key concept– only suitable for index
tests that are well defined and consistently described. An example can be found in a
Cochrane Review of diagnostic test accuracy about the Informant Questionnaire on
Cognitive Decline in the Elderly (IQCODE) for the detection of dementia within com-
munity dwelling populations (Quinn 2021).
●
A single- stranded approach combining two key concepts, most commonly but not lim-
ited to (1) index test(s) AND (2) target condition(s) (e.g. a review of the use of ultra-
sound for confirmation of gastric tube placement combined terms related to
‘ultrasound’ with key terms related to ‘stomach tube’ (Tsujimoto 2017)).
●
A single- stranded approach involving three key concepts (e.g. (1) index test(s) AND
(2)target condition(s) AND (3) population)– only suitable if this can focus the search
without unduly compromising search recall. For example, clinical assessment for
diagnosing congenital heart disease in newborn infants with Down syndrome
(seeFigure6.4.a).
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Index test(s)
Clinical assessment; physical
examination; auscultation; palpation;
electrocardiography; pulse oximetry;
chest radiography; etc.
Clinical assessment
for detecting
congenital heart
disease.
Relevant
records
Traget condition
Congential heart disease;
atrioventricular septal
defects; ventricular septal
defects; etc.
Figure6.4.a Combining concepts as search sets in a simple structure. Example: Clinical assess-
ment for diagnosing congenital heart disease in newborn infants with Down syndrome
●
A multi- stranded approach whereby a number of different single- stranded approaches
Newborns with
Down syndrome
and congenital
heart disease.
Clinical assessment
of newborns with
Down syndrome.
Patient description
Newborn infants; neonates;
babies; etc. – with Down
syndrome; trisomy 21.
are applied to optimize search recall. This approach might be taken where a diagnostic
question can be conceptualized in a number of different ways, or where the search
terms from relevant concepts are not always present in all records (so a permutation
of concepts is required). Multiple single- stranded approaches are developed, each
capturing a different way in which the relevant literature might be described by combining key concepts in different ways. The individual single-
stranded approaches are
then combined to create the final search strategy. For example, a review of physical
examination for low back pain ultimately combined four single- stranded searches,
each of which combined two or more sets of search terms related to either physical
examination, specific tests that could be included in a physical examination, low back
pain, the relevant causes of low back pain and diagnostic accuracy terms (van der
Windt 2010). Asimplified example of this type of complex search structure is provided
in Table6.4.a.
6.4.2 Controlled vocabulary andtext words
Several database producers index records using standard keywords or subject headings. Well- known examples of subject headings include MeSH for MEDLINE and EMTREE
for Embase. The indexing terms are a controlled vocabulary and are database specific,
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Table6.4.a Multi- stranded search tofind brief psychometric instruments toidentify depression
inprison or oender populations
Search
strand Concept 1 Concept 2 Concept 3
1 General screening
2 Specific terms for depression screening
3 Specific depression screening instruments for offender populations
4 General diagnostic
5
Within each of these search queries a range of search terms and search techniques will be used to
maximize retrieval of relevant studies and minimize retrieval of irrelevant studies.
Source: Adapted from Hewitt 2011.
instruments
Index tests (general) AND Target condition AND Population
instruments
Index test/Target condition concept merged AND Population
Index test/Target condition/Population concept merged
terms
Diagnostic filter
1 OR 2 OR 3 OR 4
AND Depression AND People who committed
a crime
AND People who committed
a crime
AND Depression AND People who committed
a crime
AND Target condition AND Population
i.e. the subject headings used are not identical across databases and the approach to
indexing may also differ. Embase records are often indexed in greater depth than
MEDLINE records and in recent years Elsevier has increased the number of subject
headings assigned to each Embase record. Searches of Embase may therefore retrieve
additional articles that were not retrieved by a MEDLINE search, even if the records
were present in both databases. Retrieving more records does not necessarily mean
retrieval of more relevant records, and it is important that search strategies are customized for each database searched (Falck- Ytter 2004).
Text word searches will automatically ‘map’ to relevant database subject headings
when using PubMed as an interface. The mapping should be checked to make sure the
mapping terms presented are appropriate for the search topic (they may be broader
or narrower than required). If mapping is not providing correct results, mapping in
PubMed can be prevented by careful use of field tags. Other interfaces, such as Embase.
com and Ovid, offer options to look up the subject heading based on entering an example, which provides the user with more control over the search strategy and the results
retrieved. Again, careful inspection of the headings available and the broader and narrower headings around a specific heading is important to ensure efficient searches and
to achieve a good balance of search recall and precision. Subject headings can also be
identified using other search tools provided with the database, such as the Permuted
Index under Search Tools in Ovid or the MeSH database (www.ncbi.nlm.nih.gov/mesh)
for PubMed. Database thesauri may offer the facility to ‘explode’ subject headings that
have more specific terms associated with them. For example, the MeSH term ‘Prenatal
Diagnosis’ has several lower- level terms covering more specific types of prenatal
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diagnosis such as‘Amniocentesis’ or ‘Chorionic Villi Sampling’. ‘Explosion’ of a higherlevel subject heading such as ‘Prenatal diagnosis’ captures all of these more specific
terms and so searches for several terms at once. If the review is about amniocentesis,
then articles on amniocentesis should only be indexed with the specific term
‘Amniocentesis’, and the search should include the heading ‘Amniocentesis’. However,
in practice some records may receive the more general term ‘Prenatal Diagnosis’ rather
than ‘Amniocentesis’, so if that is found to be the case, it would also be necessary to
search for ‘Prenatal Diagnosis’ unexploded. If the review is about all prenatal diagnosis
tests, then it would be best to search using the exploded heading ‘Prenatal Diagnosis’.
It is always important to check the impact of an explosion to ensure that precision does
not suffer. The information specialist should seek clarification from clinical and technical specialists about whether to include all of the terms grouped under the highestlevel term or only some ofthem.
Older publications are harder to identify than recent ones. For example, MEDLINE
does not generally include abstracts for articles published before 1976, so only text
word searches can be used on titles for this period. In addition, MEDLINE subject
headings relating to study design and methodology were not available before the
1990s, so text word searches are necessary to retrieve older records (Wilczynski 1995,
Vincent 2003).
6.4.3 Text word or keyword searching
A sensitive search strategy includes a range of text words for each concept to be searched
and it is important to consider alternative ways of specifying the same concept, for
example via synonyms (e.g. ‘newborn’ or ‘neonate’), using related terms (e.g. ‘Down
Syndrome’ or ‘Downs syndrome’ or ‘trisomy 21’) and variant spellings (e.g. ‘paediatric’
or ‘pediatric’). Depending on the service provider and the search concept, some types
of variations can also be captured using truncation (e.g. electrocardiogra* for electrocardiogram, electrocardiograph, electrocardiography, etc.) or wildcards (e.g. wom?n
for woman or women). These features differ across database interfaces and can also
change over time, so database interface help files should be checked. It is crucial to
describe fully each concept deemed important to be searched to ensure that when all
these concepts are combined in a multi- stranded approach, the risk of missing studies
is kept to a minimum (see Figure6.4.a).
Once defined, search terms (including both subject headings and text words) are
combined using Boolean operators or ‘connecting words’, the basic ones being ‘AND’
and ‘OR’ (see Figure6.4.a). Terms within the same search concept (e.g. all the search
terms for the index test(s)) are usually combined using ‘OR’, while ‘AND’ is used to combine sets of search terms for two or more concepts (e.g. index test AND target
condition).
Some search interfaces allow the use of additional operators (known as proximity
operators) to specify how close to each other words must be (e.g. occurring within a
certain number of words of each other). Proximity operators, where available and in
suitable cases, can be very useful for improving the precision of searches.
The third Boolean operator, the ‘NOT’ operator, can be used to exclude records
indexed with certain terms (for example, to carefully exclude records related exclusively
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to research on animals). Extreme care should be taken when using the NOT operator to
avoid inadvertently removing relevant records from the search result. Further details
about use of Boolean operators can be found in the online technical supplement of the
Cochrane Handbook for Systematic Reviews of Interventions (Lefebvre 2021).
6.4.4 Search filters
The accuracy of a diagnostic test can be expressed in a number of ways: sensitivity and
specificity, positive and negative predictive values, positive and negative likelihood
ratios, diagnostic odds ratio, receiver operating characteristic (ROC) curve and area
under the curve (AUC). These terms can be included in a search string as words in the
title and abstract, and as standard index terms, such as the MeSH terms, for example
‘Sensitivity and Specificity’. A combination of these terms can be used as a methodological search filter to focus searches on the studies that are most likely to report test
accuracy data.
A number of filters have been developed and published, but none has sufficiently
high levels of reliability that would justify its use as a sound method to optimize precision without compromising search recall for Cochrane Reviews of diagnostic test accuracy. The filters have not attained the proven level of efficiency that the randomized
controlled trial filters have, for example.
A routine reliance on methodological search filters for systematic reviews of test
accuracy is therefore not recommended. Evaluations have shown that even the most
sensitive filters miss relevant studies, do not perform consistently across subject areas
and study designs (Doust 2005, Mitchell 2005, Leeflang 2006, Ritchie 2007, Beynon 2013)
and do not significantly reduce the number of studies that have to be screened (Leeflang
2006, Ritchie 2007). A methodological filter should only be used as part of a multistranded approach to searching (see Section6.4.1). Search filters can be identified from
the InterTASC Information Specialists’ Sub- Group (ISSG) Search Filter Resource (www.
sites.google.com/a/york.ac.uk/issg- search- filters- resource/home). Further evidencebased information on the performance of test accuracy search filters can be found
within the diagnostic accuracy section of the SuRe info portal (www.sites.google.com/
york.ac.uk/sureinfo/home/diagnostic- accuracy).
6.4.5 Language, date andtype ofdocument restrictions
Further research is needed to determine whether studies of test accuracy are at risk of
language and other reporting biases (see Section6.4.7). Although language restrictions
are not recommended, restricting the search to particular dates might be worthwhile if
the diagnostic test of interest was introduced from a particular date or has been substantially improved over time and the review focuses only on the most recent versions.
Excluding records based on document type is not recommended. Letters may report
test accuracy data from the correspondents’ own institution, and some journals publish
short reports of studies as a research letter. Letters and errata may also report clues to
additional studies or new information about a study that is not reported elsewhere.
Further research is needed to determine the importance of letters or other types of document, such as case reports, as a source of test accuracy data.
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