Ten basic guidelines for conducting and publishing a meta-analysis

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TEN BASIC GUIDELINES FOR CONDUCTING AND
PUBLISHING A META-ANALYSIS
An Academic presentation by Dr. Nancy Agnes,
Head, Technical Operations, Pubrica Group 
www.pubrica.com Email sales_at_pubrica.com
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Introduction

• Meta-analysis is important in evidence-based
  medicine because it combines information from
  numerous sources and brings new insights.
• Meta-analysis research has grown in popularity
  as the amount of published scientific literature
  has increased. They are widely mentioned in
  biomedical sciences.
• Meta-analysis methodologies and criteria have
  developed throughout time. While there are
  several guidelines for certain types of
  meta-analysis, researchers interested in
  generating meta-analysis want a condensed piece
  containing general and up-to-date advice.
• This blog provides 10 straightforward guidelines
  for doing and publishing meta-analyses.
• To know more about Meta-Analysis Services, check
  our study guide. How to do a meta-analysis for a
  manuscript?

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Rule 1 Be specific about the meta-analysis's
topic and approach.

• A systematic review is crucial for meta-analysis,
  using the PICO model to formulate research
  questions.
• Verify that no published meta-analysis on the
  specific topic to avoid duplication.
• Meta-analysis can be conducted for multiple types
  of studies, including epidemiological variables,
  genetic association studies, gene expression
  studies, genome-wide association studies, and
  animal experimentsPreregister systematic review
  protocols at PROSPERO to avoid duplication of
  efforts.

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Rule 2 Adhere to the available instructions for
the various forms of meta-analysis.

• General guidelines for meta-analysis include the
  Quality of Reports of Meta-analyses of Randomized
  Controlled Trials (QUORUM) and the Meta-analysis
  of Observational Studies in Epidemiology (MOOSE)
  statements.
• The Preferred Reporting Items for Systematic
  Reviews and Meta-analysis (PRISMA) are widely
  used. Specific guidelines for clinical, genetic
  association, genome-wide expression, GWASs, and
  animal studies have been developed.

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Rule 3 Identify the essential variables and
establish the inclusion criterion

• Establish inclusion and exclusion criteria for
  studies, avoiding strict language or sample size
  criteria.
• Clearly define variables extracted from each
  article. Broad inclusion criteria increase
  heterogeneity, while narrow criteria can make it
  difficult to find studies.
• A compromise should be found, and prospective
  meta-analysis, typically conducted by
  international consortia, offers the advantage of
  including individual-level data.

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Rule 4 Conduct a systematic search across
several databases and extract important data.

• To systematically search published studies, use
  various bibliographic databases like PubMed,
  Embase, The Cochrane Central Register of
  Controlled Trials, Scopus, Web of Science, and
  Google Scholar.
• Specific databases like BIOSIS, CINAHL, PsycINFO,
  Sociological Abstracts, and EconLit can help
  identify additional articles and data.
• The Web of Science database can identify
  publications with key articles. Adequate
  extraction and recording of key data from primary
  articles is crucial for conducting a
  meta-analysis. Quality assessment of included
  studies, such as the Jadad scale for randomized
  clinical trials, the Newcastle-Ottawa scale for
  nonrandomized studies, and QUADAS-2 for
  diagnostic accuracy studies, is essential for
  determining inclusion criteria, sensitivity
  analysis, and differential weighting.
• However, quality assessment has been criticized
  for reducing studies to a single "quality" score.

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Rule 5 Request missing data from primary article
authors.

• Key data in primary articles is often
  unavailable, requiring authors to contact them
  for missing information.
• Standards like MIAME and STREGA promote primary
  data availability, but strict criteria and
  specialized permissions may be needed in certain
  areas, like genetics, where aggregated statistics
  can identify individuals.

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Rule 6 Choose the best statistical models for
your problem.

• Comprehensive meta-analysis are useful for
  analyzing high-quality primary data for
  quantitative summaries. However, analysts must be
  prepared for various transformations, such as
  extracting and transforming continuous variables,
  2 2 tables, or survival data.
• These analyses often use fixed-effects or
  random-effects statistical models, combining
  ranks or p-values, or multivariate methods.
  Additional statistical examinations include
  sensitivity analyses, metaregressions, subgroup
  analyses, and calculation of heterogeneity
  metrics.
• It is crucial to assess and explain possible
  sources of heterogeneity, identify sources of
  between-studies variation, and quantify their
  impact on effect size.
• Publication bias, such as the "Proteus
  phenomenon" or "winner's curse," is important in
  certain scientific fields, and cumulative
  meta-analysis is suggested to identify them.

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Rule 7 Use software that is readily available to
do meta statistics

• Meta-analyses are available in various programs,
  including Stata and R, which can handle complex
  analyses like network and gene expression
  studies.
• Stand-alone packages like OpenMetaAnalyst,
  NetworkAnalyst, JASP, MetaGenyo, Cochrane RevMan,
  EpiSheet, GWAR, GWAMA, and METAL are available
  for general applications or specific areas.
  However, some programs may present issues due to
  dependency on other packages.

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Rule 8 The study report and records must be
thorough and open.

• Meta-analyses should follow guidelines to ensure
  transparency and replicability.
• Data on search criteria, abstract screening, and
  included studies is useful, along with
  meta-analytical strategies.
• Assessment of study quality is also important. A
  spreadsheet with step records can create flow
  charts, improving the meta-analysis's quality.
• Records can be updated if needed, and stating
  limitations is crucial.

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Rule 9 Give your manuscript adequate data.

• A table with detailed information about included
  studies is useful in meta-analysis articles.
• It can be included in the main text or as a
  supplementary file.
• Reference software for meta-analyses and generate
  key graphs, including summary effect measures.
• Include plots from sensitivity analyses for
  positive findings. In complex analyses, include
  scripts used to generate results in supplementary
  files.

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Rule 10 Explain the context of your results and
recommend the next steps

• The Discussion section is crucial in a
  meta-analysis manuscript, as it helps authors
  discuss findings in relation to existing
  literature and knowledge.
• It provides an interpretation of findings,
  comments on individual studies, and suggests
  future primary studies based on available
  evidence.
• Check our Meta-Analysis Service sample work to
  know and learn more about, A meta-analysis of the
  relationship between Helicobacter Pylori
  infection and ABO blood groups.

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About Pubrica

• The team of researchers and writers at Pubrica
  creates scientific and medical research articles
  that may be a vital resource for practitioners
  and authors.
• By educating the reader about the flaws or gaps
  in the chosen study field, Pubrica medical
  writers assist you in writing and editing the
  introduction. Our specialists are familiar with
  the format that moves from a broad topic,
  problem, and background to a focused topic where
  the hypothesis is stated.

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