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Table of Contents   
EDITORIAL  
Year : 2022  |  Volume : 25  |  Issue : 1  |  Page : 1-2
The Systematic Review Meta-Analysis Conundrum


Department of Conservative Dentistry and Endodontics, Terna Dental College, Navi Mumbai, Maharashtra, India

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Date of Submission30-Mar-2022
Date of Acceptance30-Mar-2022
Date of Web Publication02-May-2022
 

How to cite this article:
Singh S. The Systematic Review Meta-Analysis Conundrum. J Conserv Dent 2022;25:1-2

How to cite this URL:
Singh S. The Systematic Review Meta-Analysis Conundrum. J Conserv Dent [serial online] 2022 [cited 2022 Jul 5];25:1-2. Available from: https://www.jcd.org.in/text.asp?2022/25/1/1/344511


It is interesting to see a large number of systematic reviews and meta-analyses being done and uploaded for publication. Unfortunately, this sudden surge in publications has made the reviewer's and editor's jobs more challenging when it comes to processing systematic reviews.

I feel that such a deluge of systematic reviews and meta-analyses has resulted in a compromise in quality as far as following the protocols is concerned with any combination or strategy being used and in turn undermining the research. This write-up brings out the do's and don'ts and a few suggestions that can help understand Systematic reviews and Meta-Analyses simply.

Most importantly, a Systematic review is different than a Meta-analysis and should nowhere be considered to be the same. Littell et al.[1] in their book have brought out this difference explicitly and explained in detail the steps for the same.

When it comes to research analysis, it is the evidence that plays a major role in deciding the quality.[2] Meta-Analysis is the top-ranked followed, by Systematic review, Randomized control trial, Cohort studies, Case–control studies, Case reports, and Animal research and laboratory studies in a descending order [Table 1].
Table 1: Evidence hierarchy

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Systematic reviews have a search question, are more detailed and involve a search strategy.[3] They require a lot of planning, are comprehensive, and reduce all risks of bias making the outcome more specific and sensitive to a particular topic. A narrative review, on the other hand, though descriptive and informative, can have an amount of selection bias. Most often, the systematic review has a meta-analysis component where the data are further processed, quantified, and summarized.

Muka et al.[4] have simplified the methodology to help synthesize the research data and publish the same successfully. [Table 2] outlines the steps one needs to follow carefully each step, which is further subdivided to simplify the researcher's work.
Table 2: Steps for a systematic review

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The National Institute for Health Research has an international database named PROSPERO where all the prospective systematic reviews need to be registered. Once the protocol is registered on PROSPERO, the researcher gets a unique id number with all the details for future reference. It is interesting to note that details of Cochrane protocols get automatically loaded on PROSPERO.

There are various guidelines available for reporting particular type of studies. Use of these checklists and tools is important for a successful outcome.[5]

  1. QUOROM: The Quality of Reporting of Meta-analysis[6]
  2. CONSORT: Consolidated Standards of Reporting Trials[7]
  3. PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses[8]
  4. PRISMA P: Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols[9]
  5. MOOSE: The Meta-analysis of Observational Studies in Epidemiology[10]
  6. ROBINS-I: Risk of Bias in Nonrandomized Studies of Interventions[11]
  7. ROB 2: COCHRANE: Risk of Bias tool for randomized control trials.[12]


We at the Journal of Conservative Dentistry urge the researchers to use the various tools available and improve the quality of their research. Adapting the various tools and adhering strictly to the criteria will only help bring out better and high-quality research papers.



 
   References Top

1.
Littell J, Corcoran J, Pillai V. Systematic Reviews and Meta-Analysis. Pocket Guides to Social Work Research Methods. Oxford University Press; 2008.  Back to cited text no. 1
    
2.
Haidich AB. Meta-analysis in medical research. Hippokratia 2010;14 Suppl 1:29-37.  Back to cited text no. 2
    
3.
Uman LS. Systematic reviews and meta-analyses. J Can Acad Child Adolesc Psychiatry 2011;20:57-9.  Back to cited text no. 3
    
4.
Muka T, Glisic M, Milic J, Verhoog S, Bohlius J, Bramer W, et al. A 24-step guide on how to design, conduct, and successfully publish a systematic review and meta-analysis in medical research. Eur J Epidemiol 2020;35:49-60.  Back to cited text no. 4
    
5.
Khan S. Meta-Analysis, Statistics for Biology and Health. Springer Nature Singapore Pte Ltd; 2020. p. 3. Available from: https://doi.org/10.1007/978-981-15-5032-4_1.  Back to cited text no. 5
    
6.
Moher D, Cook DJ, Eastwood S, Olkin I, Rennie D, Stroup DF. Improving the quality of reports of meta-analyses of randomised controlled trials: The QUOROM statement. Quality of Reporting of Meta-analyses. Lancet 1999;354:1896-900.  Back to cited text no. 6
    
7.
Moher D, Hopewell S, Schulz KF, Montori V, Gøtzsche PC, Devereaux PJ, et al. CONSORT 2010 explanation and elaboration: Updated guidelines for reporting parallel group randomised trials. Int J Surg 2012;10:28-55.  Back to cited text no. 7
    
8.
Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Ann Intern Med 2009;151:264-9, W64.  Back to cited text no. 8
    
9.
Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev 2015;4:1.  Back to cited text no. 9
    
10.
Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: A proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 2000;283:2008-12.  Back to cited text no. 10
    
11.
Sterne JA, Hernán MA, Reeves BC, Savović J, Berkman ND, Viswanathan M, et al. ROBINS-I: A tool for assessing risk of bias in non-randomised studies of interventions. BMJ 2016;355:i4919.  Back to cited text no. 11
    
12.
Sterne JA, Savović J, Page MJ, Elbers RG, Blencowe NS, Boutron I, et al. RoB 2: A revised tool for assessing risk of bias in randomised trials. BMJ 2019;366:l4898.  Back to cited text no. 12
    

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Correspondence Address:
Dr. Shishir Singh
05/306, St Annes Apartments, Off Palimala Road, Bandra, Mumbai, Maharashtra
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jcd.jcd_173_22

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