Systematic reviews and meta-analyses are essential to summarize evidence relating to efficacy and safety of health care interventions accurately and reliably. The clarity and transparency of these reports, however, is not optimal. Poor reporting of systematic reviews diminishes their value to clinicians, policy makers, and other users.

Since the development of the QUOROM (QUality Of Reporting Of Meta-analysis) Statement—a reporting guideline published in 1999—there have been several conceptual, methodological, and practical advances regarding the conduct and reporting of systematic reviews and meta-analyses. Also, reviews of published systematic reviews have found that key information about these studies is often poorly reported. Realizing these issues, an international group that included experienced authors and methodologists developed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) as an evolution of the original QUOROM guideline for systematic reviews and meta-analyses of evaluations of health care interventions.

The PRISMA Statement consists of a 27-item checklist and a four-phase flow diagram. The checklist includes items deemed essential for transparent reporting of a systematic review. In this Explanation and Elaboration document, we explain the meaning and rationale for each checklist item. For each item, we include an example of good reporting and, where possible, references to relevant empirical studies and methodological literature. The PRISMA Statement, this document, and the associated Web site (http://www.prisma-statement.org/) should be helpful resources to improve reporting of systematic reviews and meta-analyses.

/pdf/the-prisma-statement-for-reporting-systematic-reviews-and-3j53e5oe33.pdf

The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration

The Cochrane Handbook for Systematic Reviews of Interventions is the official document that describes in detail the process of preparing and maintaining Cochrane systematic reviews on the effects of healthcare interventions.

/pdf/cochrane-handbook-for-systematic-reviews-of-interventions-1xbdy6uvru.pdf

Cochrane Handbook for Systematic Reviews of Interventions

Systematic reviews and meta-analyses are essential to summarise evidence relating to efficacy and safety of healthcare interventions accurately and reliably. The clarity and transparency of these reports, however, are not optimal. Poor reporting of systematic reviews diminishes their value to clinicians, policy makers, and other users. Since the development of the QUOROM (quality of reporting of meta-analysis) statement—a reporting guideline published in 1999—there have been several conceptual, methodological, and practical advances regarding the conduct and reporting of systematic reviews and meta-analyses. Also, reviews of published systematic reviews have found that key information about these studies is often poorly reported. Realising these issues, an international group that included experienced authors and methodologists developed PRISMA (preferred reporting items for systematic reviews and meta-analyses) as an evolution of the original QUOROM guideline for systematic reviews and meta-analyses of evaluations of health care interventions. The PRISMA statement consists of a 27-item checklist and a four-phase flow diagram. The checklist includes items deemed essential for transparent reporting of a systematic review. In this explanation and elaboration document, we explain the meaning and rationale for each checklist item. For each item, we include an example of good reporting and, where possible, references to relevant empirical studies and methodological literature. The PRISMA statement, this document, and the associated website (www.prisma-statement.org/) should be helpful resources to improve reporting of systematic reviews and meta-analyses.

/pdf/the-prisma-statement-for-reporting-systematic-reviews-and-48ibbzju0k.pdf

The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration

abstracts can be used to eliminate clearly irrelevant reports, obviating the need to obtain the full text of those reports or to return to the bibliographic database at a later time. Accession number / unique identifier: it is advisable to allocate an unused field or fields to store the unique identifier(s) / accession number(s) of records downloaded, such as the PubMed ID number (PMID). This allows subsequent linkage to the full database record and also facilitates information management such as duplicate detection and removal (i.e. de-duplication). Copyright © 2019 The Cochrane Collaboration 75 Affiliation / address: may include the institutional affiliation and / or email address of the author / investigator. Article identifier / digital object identifier (DOI): can be used to cite and link to the full record. Author identifier: can be used to disambiguate authors with similar names. The identifier may be an ORCID (https://orcid.org/about/what-is-orcid/mission?lang=en_US), an International Standard Name Identifier (ISNI) http://www.isni.org/, or from the Virtual International Authority File (VIAF) http://viaf.org/. Clinical trial number: if the record contains a clinical trial number, such as those assigned by the ClinicalTrials.gov or ISRCTN schemes, or a number allocated by the sponsor of the trial, these should be downloaded to aid linking of trial reports to the original studies. In PubMed, the Secondary Source ID field [SI] contains information from secondary sources such as ClinicalTrials.gov and ISRCTN. Similarly, in Ovid MEDLINE, the Secondary Source Linking (SL) field contains the URL to ClinicalTrials.gov and ISRCTN resources where these are mentioned in MEDLINE records. In Embase, the Clinical Trial Number (CN) field contains clinical trial numbers associated with the record. Index terms / thesaurus terms / keywords: These help indicate why records were retrieved if the title and abstract lack detail. Investigator name: this field contains personal names of individuals (e.g. collaborators and investigators) who are not authors of the article but rather are listed in the article as members of a collective / corporate group that is an author of the article. Language: this is the language (or languages) of publication of the original document. Location identifier: this field may also contain a Digital Object Identifier (DOI). Original title: if the original title of the document is not in English and the original title is available, then both titles should be downloaded into separate database fields, to aid correct identification of the reference and de-duplication. See also Transliterated title below. Other term: this field contains largely non-MeSH subject terms (also referred to as Keywords) that describe the content of the article. Author-supplied keywords are included here in PubMed (since 2013). Registry Number / EC Number and Substance Name: these fields provide supplementary subject information regarding substances (chemicals, drugs and enzymes). Transliterated title: in PubMed, this field contains the original title (or, where available, the transliterated title) of each record originally published in a non-English language. This field can be useful for de-duplication. Copyright © 2019 The Cochrane Collaboration 76 Comments, corrections, errata, retractions and updates: It is mandatory, for Cochrane reviews of interventions, to examine any relevant retraction statements and errata for information (MECIR C48). All fields that relate to subsequently published comments, corrections, errata, retractions and updates should be selected for inclusion in the download, so that any impact of these subsequent publications can be taken into account. The MECIR standard specifies: “Care should be taken to ensure that this information is retrieved in all database searches by downloading the appropriate fields, together with the citation data”. For example, the most important fields to consider, in relation to comments, errata etc, together with their field labels in PubMed, are provided in Box 4.a. Box 4.a Important field labels in PubMed in relation to comments, retractions etc CIN: ‘Comment in’ CON: ‘Comment on’ CRI: ‘Corrected and republished in’ CRF: ‘Corrected and republished from’ EIN: ‘Erratum in’ EFR: ‘Erratum for’ ECI: Expression Of Concern In ECF: Expression Of Concern For RIN: ‘Retraction in’ ROF: ‘Retraction of’ RPI: ‘Republished in’ RPF: ‘Republished from’ UIN: ‘Update in’ UOF: ‘Update of’ See: https://www.nlm.nih.gov/bsd/mms/medlineelements.html The above list is provided as an example of the relevant fields in PubMed and as an indicator of the equivalent fields in other databases and service providers. Copyright © 2019 The Cochrane Collaboration 77 4.3 De-duplicating references Because searching to inform systematic reviews is intended to be extensive, thousands of records may be retrieved from multiple sources. References to the same article may be downloaded multiple times from different sources and duplicates can even be found within individual databases. The identification and elimination of duplicate records (de-duplication) reduces unnecessary work during the screening phase. Removing duplicate records from the pool of retrieved references is also necessary if the total number of records identified through database searching (in addition to the total number of additional records identified through other sources) is to be reported correctly in the PRISMA flow diagram together with the total number of records after the duplicates have been removed (Liberati et al 2009). Many Cochrane Information Specialists de-duplicate records so that review authors see only search results that have already been de-duplicated. Formatting of citation information often varies across sources, and automated identification of duplicate references from within reference management software may lead to false positives (removing non-duplicate records) and false negatives (retaining duplicate records). Meanwhile, de-duplication through visual examination of each record is time-consuming and often impractical. Several strategies have been developed to address these issues. Methods for modifying duplicate detection algorithms within reference management software have been developed and tested (Kwon et al 2015, Bramer et al 2016b). An online method to identify search results that are duplicates of PubMed citations has been reported (Sampson et al 2006). Open-source software programs for online duplicate detection have also been developed (Jiang et al 2014, Rathbone et al 2015). There is no consensus on the optimal method for duplicate detection, and the most appropriate method will most likely depend upon the size of the combined dataset, the number and output format of the resources searched, and the skill and comfort level of the operator. A combination of automated methods and visual inspection is often used. After de-duplication of search results, records may be screened for inclusion from within the reference management database. Alternatively, the records may be exported into dedicated screening software or into systematic review production software that includes screening capabilities. If screening is carried out within the reference management database, records for the included and excluded studies can be exported and uploaded into systematic review software such as RevMan. Instructions for importing references into RevMan can be found at: https://community.cochrane.org/help/tools-and-software/revman-5/support-revman5/revman-5-faq. The decision whether to screen within reference management software or within dedicated screening or review production software will most likely depend upon the number of retrieved references, access to various tools and review author preference. Copyright © 2019 The Cochrane Collaboration 78 4.4 Summary points • Cochrane review authors should seek advice from their Cochrane Information Specialist on managing references. • Authors of non-Cochrane reviews should seek advice from their medical / healthcare librarian or information specialist, with experience of managing references for systematic reviews. • Use of reference management software is recommended. • Ensure that all the necessary fields are downloaded. • Remove duplicate references before screening. • Either screen references within the reference management software and export references for the included and excluded studies into systematic review software, or export references to specialized screening software. 5 Supplement information Authors: Carol Lefebvre, Julie Glanville, Simon Briscoe, Anne Littlewood, Chris Marshall, MariaInti Metzendorf, Anna Noel-Storr, Tamara Rader, Farhad Shokraneh, James Thomas and L. Susan Wieland on behalf of the Cochrane Information Retrieval Methods Group

Cochrane handbook for systematic reviews of interventions. Version 5.1.0 [updated March 2011]. The Cochrane Collaboration

Protocols of systematic reviews and meta-analyses allow for planning and documentation of review methods, act as a guard against arbitrary decision making during review conduct, enable readers to assess for the presence of selective reporting against completed reviews, and, when made publicly available, reduce duplication of efforts and potentially prompt collaboration. Evidence documenting the existence of selective reporting and excessive duplication of reviews on the same or similar topics is accumulating and many calls have been made in support of the documentation and public availability of review protocols. Several efforts have emerged in recent years to rectify these problems, including development of an international register for prospective reviews (PROSPERO) and launch of the first open access journal dedicated to the exclusive publication of systematic review products, including protocols (BioMed Central's Systematic Reviews). Furthering these efforts and building on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines, an international group of experts has created a guideline to improve the transparency, accuracy, completeness, and frequency of documented systematic review and meta-analysis protocols--PRISMA-P (for protocols) 2015. The PRISMA-P checklist contains 17 items considered to be essential and minimum components of a systematic review or meta-analysis protocol.This PRISMA-P 2015 Explanation and Elaboration paper provides readers with a full understanding of and evidence about the necessity of each item as well as a model example from an existing published protocol. This paper should be read together with the PRISMA-P 2015 statement. Systematic review authors and assessors are strongly encouraged to make use of PRISMA-P when drafting and appraising review protocols.

/pdf/preferred-reporting-items-for-systematic-review-and-meta-mgb1uy0yle.pdf

Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation.

BACKGROUND: The inclusion of grey literature (i.e. literature that has not been formally published) in systematic reviews may help to overcome some of the problems of publication bias, which can arise due to the selective availability of data. OBJECTIVES: To review systematically research studies, which have investigated the impact of grey literature in meta-analyses of randomized trials of health care interventions. SEARCH STRATEGY: We searched the Cochrane Methodology Register (The Cochrane Library Issue 3, 2005), MEDLINE (1966 to 20 May 2005), the Science Citation Index (June 2005) and contacted researchers who may have carried out relevant studies. SELECTION CRITERIA: A study was considered eligible for this review if it compared the effect of the inclusion and exclusion of grey literature on the results of a cohort of meta-analyses of randomized trials. DATA COLLECTION AND ANALYSIS: Data were extracted from each report independently by two reviewers. The main outcome measure was an estimate of the impact of trials from the grey literature on the pooled effect estimates of the meta-analyses. Information was also collected on the area of health care, the number of meta-analyses, the number of trials, the number of trial participants, the year of publication of the trials, the language and country of publication of the trials, the number and type of grey and published literature, and methodological quality. MAIN RESULTS: Five studies met the inclusion criteria. All five studies showed that published trials showed an overall greater treatment effect than grey trials. This difference was statistically significant in one of the five studies. Data could be combined for three of the five studies. This showed that, on average, published trials showed a 9% greater treatment effect than grey trials (ratio of odds ratios for grey versus published trials 1.09; 95% CI 1.03-1.16). Overall there were more published trials included in the meta-analyses than grey trials (median 224 (IQR 108-365) versus 45(IQR 40-102)). Published trials had more participants on average. The most common types of grey literature were abstracts (55%) and unpublished data (30%). There is limited evidence to show whether grey trials are of poorer methodological quality than published trials. AUTHORS' CONCLUSIONS: This review shows that published trials tend to be larger and show an overall greater treatment effect than grey trials. This has important implications for reviewers who need to ensure they identify grey trials, in order to minimise the risk of introducing bias into their review.

Grey literature in meta‐analyses of randomized trials of health care interventions

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Mathias M Egger

Author Tools

Chat about Author

Papers

Grey literature in meta‐analyses of randomized trials of health care interventions