systematic review and Meta Analysis by Umais Sohal.

1. Systematic review
and Meta-Analysis

3. What are they?
• A systematic review answers a defined research question
by collecting and summarizing all empirical evidence that
fits pre-specified eligibility criteria.
• A meta-analysis is the use of statistical methods to
summaries the results of these studies

5. Continue
A systematic review collects all possible studies related to a
given topic and design, and reviews and analyzes their results.
During the systematic review process, the quality of studies is
evaluated, and a statistical meta-analysis of the study results is
conducted on the basis of their quality. A meta-analysis is a
valid, objective, and scientific method of analyzing and
combining different results.

6. Reason to do Meta-analysis
When you looked at the individual studies, they may potentially
report differing effect from the treatment. "which one do I take".
In MA, you bring all different effect together and MA gives you
summarized effect from across all these different studies.
Each of the study by itself may have small sample size, result
may be questionable.

7. Continue…
Meta-analyses are conducted to assess the strength of
evidence present on a disease and treatment. One aim is to
determine whether an effect exists; another aim is to
determine whether the effect is positive or negative and,
ideally, to obtain a single summary estimate of the effect.

8. Relationship between SR and MA
• SR is the process of undertaking the reviews, and MA may be one
outcome.
• Not all systematic reviews include meta-analysis, but all meta-analysis
are found in systematic reviews.

9. Hierarchy of evidence

10. Results from Medline search using text
"meta-analysis"

11. Study planning
It is easy to confuse systematic reviews and meta-analyses. A systematic
review is an objective, reproducible method to find answers to a certain
research question, by collecting all available studies related to that question
and reviewing and analyzing their results. A meta-analysis differs from a
systematic review in that it uses statistical methods on estimates from two or
more different studies to form a pooled estimate. Following a systematic
review, if it is not possible to form a pooled estimate, it can be published as is
without progressing to a meta-analysis; however, if it is possible to form a
pooled estimate from the extracted data, a meta-analysis can be attempted.
Systematic reviews and meta-analyses usually proceed according to the
flowchart presented in Fig.

13. Define Research Question and Review
Literature
Meta-analyses begin with defining the research question. A
defined research question identifies the population affected by
the intervention and the potential outcome(s) of treatment.
For example, Are men who smoke for 10 or more years at
greater risks for lung cancer than men who have never smoke?
This question defines the population, and it identifies lung
cancer as the outcome of the intervention.

14. Literature search
Reviewing the literature for studies that answer your research
question comes after your question has been defined.
• MEDLINE
• EMBASE
• PUBMED
• Cochrane Collaboration
• GOOGLE SCHOLORS
• Gray literature

15. Select Appropriate Studies
• Selecting the appropriate studies is probably the most important
step of a meta-analysis. papers that are duplicates, that are written
in a language you can't understand, or that are not clinical studies,
can be eliminated.
• After eliminating papers that are clearly not useful, screen the rest
of the papers a bit more deeply for eligibility. Several elements
can be used to determine a paper's eligibility for the analysis, but
it is important that all of the studies you include have the
information that you need in order to do your analysis.

16. Extract Data
The next step in the process is extracting the data for analysis
and synthesis. The extracted data depends on the research
question, but it may include information such as sample size,
patient characteristics, length of study, and a statistical
measure, such as confidence interval, odds ratio, risks ratio,
mean difference, or hazard ratio.

18. Analyze data
• Once you have organized it, your next step is to analyze
the data using statistical software. A forest plot will allow
you to compare statistical differences between groups.

19. Dichotomous variables and continuous
variables
In data analysis, outcome variables can be considered broadly in
terms of dichotomous variables and continuous variables. When
combining data from continuous variables, the mean difference
(MD) and standardized mean difference (SMD) are used (Table 1)
MD = mean difference between the mean value in two groups
SMD =
difference in mean outcome between group
standard deviation of outcomeamong participants

20. Summary of Meta –analysis Methods available
in RevMan
Type of data Effect measure Fixed-effect model Random-effect
model
Dichotomous Odds ratio(OR) Mantel-Haenaszel
(M-H)
Mantel-Haenaszel
(M-H)
Inverse variance(IV) Inverse variance(IV)
Peto
Risk ratio(RR) Mantel-Haenaszel
(M-H)
Mantel-Haenaszel
(M-H)
Risk difference (RD) Inverse variance(IV) Inverse variance(IV)
Continuous Mean difference
(MD),Standardized
Difference
Mean(SDM)
Inverse variance(IV) Inverse variance(IV)

23. Forest plot representing homogeneous data

24. Publication bias Impact on meta-analysis
Meta-analyses and systematic reviews can account for
publication bias by including evidence from unpublished
studies and the grey literature. The presence of publication bias
can also be explored by constructing a funnel plot in which the
estimate of the reported effect size is plotted against a measure
of precision or sample size.

26. MEDCALC Software
MedCalc - "MedCalc is a complete statistical program for
Windows designed to closely match the requirements of
biomedical researchers. It is fast, very user-friendly and reliable”.
• more than 220 statistical tests, procedures and graphs
• reference software for ROC curve analysis...
• method comparison and method evaluation including Bland &
Altman plot, Passing & Bablok, and Deming regression, ...
• reference intervals
• meta-analysis

27. Advantages of systematic review
• The methods that scientists use to find and select studies reduce bias
and are more likely to produce reliable and accurate conclusions.
• A review summarizes findings from multiple studies. This makes the
information easier for the end user to read and understand.
• give an idea of how well findings might apply to everyday practice
• reduce bias when drawing conclusions, as it takes in a range of views
and findings
• Systematic reviews also offer practical advantages. They are less
costly to carry out than a new set of experiments, and they take less
time.
 .

28. Limitations in Systematic Reviews/Meta-
analysis
Even though systematic review and meta-analysis are
considered the best evidence for getting a definitive answer to
a research question, there are certain inherent flaws associated
with it, such as the location and selection of studies,
heterogeneity, loss of information on important outcomes,
inappropriate subgroup analyses and duplication of
publication.

29. The role of editors and peer reviewers
The decisions of journal editors and peer reviewers can also
lead to publication bias. Sometimes, results do not reach the
publication stage because there is funding for research, but this
does not cover the cost of analyzing and publishing the results.
This can limit the motivation to write up and submit any
negative or neutral findings for publication.

30. “If only we knew what we know!”
“Anything you can do ………. I can do Meta!”