Different sources of data used to extract for writing a systematic review - Pubrica
                     What are the Different Sources of Data Used 
to Extract for Writing a Systematic Review 
 
Dr. Nancy Agnes, Head, Technical Operations, Pubrica, [email protected] 
 
 
In-Brief 
 
3. Errata and letters will provide valuable 
Systematic reviews have studied rather than reports 
knowledge about experiments, such as critical 
as the unit of interest. So,many reports of the same 
flaws and retractions, and research reviewers can 
study need to be identified and linked together  
investigate them where they are found . 
before or after data extraction.Because of the 
 
growing abundance of data sources (e.g., studies 
4. Trials registers keep track of studies that have 
registers, regulatory records, and clinical research 
been designed or begun. They've become a 
reports), review authors can determine which 
valuable resource for locating experiments, 
sources can include the most relevant details for the 
matching reported outcomes and effects to those 
review and provide a strategy in place to address 
expected, and collecting feasibility and safety 
contradictions if evidence were inconsistent 
evidence that isn't readily accessible elsewhere. 
throughout sources. 
 
I. INTRODUCTION 5. Clinical research reports (CSRs) are 
 unabridged and concise accounts of the clinical 
Systematic analyses seek to find all important trials to challenge, nature, behaviour, and outcomes of 
their study issue and synthesise information about the clinical trials that meet the International 
design, risk of bias, and outcomes of those studies. As Conference on Harmonisation's format and 
a result, a systematic study is heavily dependent on content guidelines (ICH). Pharmaceutical firms 
interpreting and analysing evidence from these apply CSRs and other required documents to 
analyses. For systematic analyses, data collected regulatory authorities to secure marketing 
should be reliable, complete, and available for future clearance for medications and biologics for a 
updating and data sharing. The methods used to make particular indication. 
these choices must be straightforward, and they 
should be selected with prejudgments and human 
 
error in mind .We define data collection methods used 6. Regulatory reviews, such as those obtainable 
in systematic reviews, including data extraction from the US Food and Drug Administration or 
directly from journal articles and other case study the European Medicines Agency, may offer 
reports. invaluable information about drug, biologic, and 
 medical product trials applied for marketing 
II. DIFFERENT SOURCES OF DATA approval by manufacturers. These papers are 
 summaries of CSRs and associated documents 
1. Journal articles are the bulk of data in prepared by agency personnel as part of 
systematic reviews that comes from this source. authorising goods for sale after a reanalysis of 
It's worth noting that a thesis can be published in the initial trial results. 
many journal papers, each reporting on a 
different part of the research (e.g. design, main 7. Individual participant data (IPD) is normally 
results, and other results). requested directly from the study's researchers, 
or it can be found in open data repositories. 
2. Abstracts from conferences are widely Variables that reflect each participant's profile, 
accessible. On the other hand, conferencing intervention (or exposure) population, prognostic 
abstracts are extremely subjective in terms of factors, and outcome metrics are usually included 
efficiency, precision, and level of description. in these data. 
 
 
 
 
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III. DATA EXTRACTION TOOLS and systematic review." ISPRS Journal of 
 Photogrammetry and Remote Sensing 164 
i. Excel (2020): 152-170. 
Excel is the essential device for managing the 4. Büchter, Roland Brian, Alina Weise, and Dawid 
screening and information extraction phases of the Pieper. "Development, testing and use of data 
systematic review measure. We can design extraction forms in systematic reviews: a review 
customised workbooks and spreadsheets for of methodological guidance." BMC medical 
systematic review. A further developed way to utilise research methodology 20.1 (2020): 1-14. 
Excel for this object is the PIECES approach, planned 5. Hu, Ruiqi, Michelle Helena van Velthoven, and 
by a librarian at Texas A&M.  Edward Meinert. "Perspectives of people who 
ii. Covidence  are overweight and obese on using wearable 
Covidence is software built explicitly for dealing with technology for weight management: systematic 
each progression of a systematic review project, review." JMIR mHealth and uHealth 8.1 (2020): 
including data extraction.  e12651. 
iii. RevMan 6. Mengist, Wondimagegn, TeshomeSoromessa, 
RevMan is free software used to oversee Cochrane and GudinaLegese. "Method for conducting 
surveys. For more data on RevMan, including systematic literature review and meta-analysis 
clarifying how it could be utilised to extricate and for environmental science research." MethodsX 7 
examine information.  (2020): 100777. 
iv. SRDR   
SRDR (Systematic Review Data Repository) is a  
Web-based tool for extracting and managing data for 
systematic review. It is additionally an open and 
accessible document of a systematic review and their 
information. 
 
v. DistillerSR 
DistillerSR is a systematic review management 
program. It guides the reviewer in making project-
explicit structures, separating, and examining 
 
information
 
IV. CONCLUSION 
 
A systematic review article is not conceivable 
without a decent literature search. The writing search 
has its principles that, for the most part, apply to both 
unique and review examines. A detailed review 
includes a literature search method guided by keeping 
an accurate and straightforward record of the whole 
cycle. It is valuable to outline an Excel table where 
the choice measures will record references of studies. 
This will assist the reviewer with understanding the 
methodology, and the outcomes got. If any inquiries 
ought to emerge, this proof will make it simple to 
discredit and clarify any doubts about the cycle or the 
outcomes. 
 
REFERENCES 
 
1. Jackson, Tanya, et al. "Classification of aerosol-
generating procedures: a rapid systematic 
review." BMJ open respiratory research 7.1 
(2020): e000730. 
2. Spasic, Irena, and Goran Nenadic. "Clinical text 
data in machine learning: Systematic 
review." JMIR medical informatics 8.3 (2020): 
e17984. 
3. Tamiminia, Haifa, et al. "Google Earth Engine 
for geo-big data applications: A meta-analysis 
 
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