How To Extract Quantitative Data For Systematic Review And Meta-Analysis  - Pubrica
                     HOW TO EXTRACT  
QUANTITATIVE DATA FOR 
 SYSTEMATIC REVIEW 
AND  META-ANALYSIS
An Academic presentation by
Dr. Nancy Agnes, Head, Technical Operations, Pubrica 
 Group: www.pubrica.com
Email: [email protected]
Today's Discussion
Outline
Introduction
Process Involved in the Data Extraction for Meta-
Analysis  and Systematic Review
Tools for Data 
Extraction  
Conclusion
Introduction
The data extraction is the essential and  
primary protocol for conducting a systematic  
review and meta-analysis.
In order to help, this blog post will introduce 
 you to the process involved in the data  
extraction for conducting a systematic review  
and meta-analysis.
Contd...
A meta-analysis often accompanies systematic review.
It involves using statistical methods and techniques to pool the data from
many  studies on a particular topic to generate single quantitative data.
This generates an estimate which is more potent than conventional hypothesis testing. 
 It generates inferences that are more reliable than reported by individual studies.
A quantitative, formal, epidemiological study design will be followed for performing a 
 meta-analysis.
Process Involved in the 
Data  Extraction for Meta-
Analysis  and Systematic 
Review
PROCESS FLOW:
Define the review question and establish criteria for 
 including studies in the review
Search for studies that answer the review question 
 Choose studies that meet the review criteria
Contd...
Extract data from included studies
Assess the possibility of bias in included studies by objectively evaluating them 
 Evaluate the included data by conducting meta-analyses where applicable
Address reporting biases
SEARCH STRATEGY:
Various databases are available for the articles screening for the Systematic Review 
 and Meta-Analysis, including MEDLINE, PubMed, Scopus and Cochrane 
databases.
Contd...
Each database is having a different search strategy procedure for article screening.
The most commonly used search strategy was Medical Subject Headings (MeSH) 
 terms (Appendix 2).
Below we have provided the example of the articles screening process for
the  systematic review and Meta-Analysis.
EXAMPLE:
Question: How to extract the data for the management of Superior
Mesenteric  Artery Syndrome (SMAS)?
Contd...
Different combinations of keywords will be used for the search strategies and 
 medical subject headings (MeSH) to generate two subsets of citations: one for  
SMAS, using the MeSH and terms like “SMAS”, “SMA syndrome”, “superior  
mesenteric artery syndrome” and the other for its management using terms and  
MeSH like surgery, resection, bypass etc.
To search other databases, the keywords were changed according to each  
database’s searching protocol, including management of SMAS “Superior  
mesenteric artery syndrome”, “Wilkie syndrome”, “Cast syndrome”, “mesenteric 
 duodenal compression syndrome”, “chronic duodenal ileus”. Bibliographic sources  
will be screened.
Contd...
After that read sample papers related to SMAS management to identify
the  variables.
Freeze template using the variables for SMAS methodology,
characteristics,  therapeutics,etc.
Contd...
DATA
EXTRACTION  
TEMPLATE:
Contd...
RISK OF BIAS (QUALITY) ASSESSMENT)
Quality assessment will be performed as part of the data extraction process.
Two independent reviewers will critically appraise included studies to assess
the  risk of bias using the Quality of Health Economic Studies (QHES) 
tool.
Tools for Data 
Extraction
Contd...
Contd...
EXAMPLE OF A PRISMA DIAGRAM USED FOR DATA EXTRACTION
PRISMA focuses on how authors can ensure that systematic reviews and
meta-  analyses are transparent and complete.
It does not discuss the conductofsystematicreviews explicitly or in-depth,
but  there are other resources available.
Pubrica develops the PRISMA statement and this explanatory document to
help  authors report a wide array of systematic reviews to assess the benefits and 
harms.
Contd...
When reporting systematic reviews of non-randomized trials evaluating the benefits  
and harms of interventions, we consider several of the checklist items significant.
We recognize that authors who answer concerns about aetiology, diagnosis, or 
 prognosis and who review epidemiological or diagnostic accuracy research, for  
example, will need to change or include additional items in their systematic reviews.
Contd...

Conclusion
In future, to obtain the solution for a problem  
statement, the hurdles of analytics can be minimized  
by Data extraction.
Without data extraction, systematic reviews and meta-  
analysis proposals threw many human errors in  
manipulation and calculations in earlier days.
The evolution of Data extraction scrutinizes and  
maintaining the reliability of data in the existing studies.
Contact Us
UNITED KINGDOM
+44- 7424810299
INDIA
+91-9884350006
EMAIL
[email protected]