How to do Meta Analysis - PowerPoint PPT Presentation

About This Presentation
Title:

How to do Meta Analysis

Description:

Quantitative approach for systematically combining results of previous research ... Embase. Cochrane Review/Trials Register. Other strategies you may adopt ... – PowerPoint PPT presentation

Number of Views:2023
Avg rating:3.0/5.0
Slides: 27
Provided by: biba8
Learn more at: http://www.bibalex.org
Category:
Tags: analysis | embase | meta

less

Transcript and Presenter's Notes

Title: How to do Meta Analysis


1
How to do Meta Analysis
  • Arindam Basu
  • Associate Director,
  • Fogarty International Training Program
  • Kolkata, India
  • February, 2005
  • arin.basu_at_gmail.com
  • phone 919830153666

2
What is meta analysis?
Quantitative approach for systematically
combining results of previous research to arrive
at conclusions about the body of research.
3
What does it mean?
  • Quantitative numbers
  • Systematic methodical
  • combining putting together
  • previous research what's already done
  • conclusions new knowledge

4
The popularity of meta analyses
Number of Meta Analysis publications are steadily
increasing since 1993. We graphed the counts of
journal articles included meta analysis as
publication type from Pubmed, from years 1993
through 2004
5
Four Steps of Meta Analysis
  • Identify your studies
  • Determine eligibility of studies
  • Inclusion which ones to keep
  • Exclusion which ones to throw out
  • Abstract Data from the studies
  • Analyze data in the studies statistically

6
Identify your studies
  • Be methodical plan first
  • List of popular databases to search
  • Pubmed/Medline
  • Embase
  • Cochrane Review/Trials Register
  • Other strategies you may adopt
  • Hand search (go to the library...)
  • Personal references, and emails
  • web, eg. Google (http//scholar.google.com)

7
How to Search for literature
  • Formulate your question appropriately
  • If you are searching pubmed
  • Use Medical Subject Headings (MeSH) 1
  • Lookup word in text word, abstract, title 2
  • Combine 1 with 2 using boolean logic
  • Set up proper filters
  • For Others, use text word, abstract

Huh?!, what is boolean logic??
8
Boolean Logic AND
this is AND zone, covering common area between
two ellipses
9
Boolean Logic OR
this is boolean OR, covering the two ellipses
10
Example Research Issue
  • Let's say we want to know whether streptokinase
    is protective for death from acute myocardial
    infarction. How should we set up a search
    strategy? We will search pubmed only

11
The Search
  • streptokinasetext word OR acute myocardial
    infarctiontext word produces ALL articles that
    contain EITHER streptokinase OR acute myocardial
    infarction anywhere in the text inclusive, many
  • streptokinase text word AND acute myocardial
    infarction text word will capture only those
    subsets that have BOTH streptokinase AND acute
    myocardial infarction anywhere in the text
    restrictive, few

Next, we shall look at the PUBMED Screen
12
Choose your DATABASE here
Remember to choose both PUBMED, and MESH for
formulating search. Choose PUBMED CENTRAL for
free articles!
13
Keep some, throw out others
  • Cannot include all studies
  • Keep the ones with
  • high levels of evidence
  • good quality
  • check with QUOROM guidelines
  • Usually, MA done with RCTs
  • Case series, and case reports definitely out
  • Selection problems are major problems
  • read the article I sent

MA Meta Analysis RCT Randomized Controlled
Trial
14
Plan of Action
ARE THE STUDIES ELIGIBLE FOR MA (STEP I)?
NO
DISCARD
YES
ABSTRACT THE DATA
ENTER INTO A SPECIFIED FORMAT
15
How to Abstract Data Guidelines
  • Create a spreadsheet (Excel, or OpenOffice Calc)
  • For each study, create the following columns
  • name of the study
  • name of the author, year published
  • number of participants who received intervention
  • number of participants who were in control arm
  • number who developed outcomes in intervention
  • number who developed outcomes in control arm

Lets do that to our streptokinase myocardial
infarction study, next
16
Spreadsheet Data for Strepto Study
We got like 22 studies to do our meta analysis,
after all
  • We created seven columns
  • trial trial identity code
  • trialname name of trial
  • year year of the study
  • pop1 study population
  • deaths1 deaths in study
  • pop0 control population
  • deaths0 deaths in control

17
Analyze Data Statistically
  • Combine data to arrive at a summary, 3 measures
  • Effect Size (Odds Ratio)
  • Variance with 95 Confidence Interval
  • Test of heterogeneity
  • Two Graphs
  • Forest Plot
  • Funnel Plot
  • Examine why the studies are heterogeneous, if
    they are
  • Use Statistical Packages, several choices

Lets see what we got for streptokinase versus
deaths from AMI
18
Summary Estimates for Strepto Study
The pooled Odds Ratio shows that those receiving
streptokinase at AMI are about 77 at risk of
death (23 less likely to die)
  • Mantel Haenszel OR0.77
  • 95 Confidence Interval
  • 0.72, 0.83
  • Test of Heterogeneity
  • Chi-square (df21) 31.5
  • P-Value 0.07

That in 95 out of 100 such meta analyses, the
pooled Odds Ratio would lie between 0.72 and
0.83, indicating a statistically significant
protective effect
That these studies were not significantly
heterogeneous
19
Forest Plot
The dotted line passes across null, or 1.0 The
Risk Estimate of each study is lined up on each
side of the dotted line, with 95 CI spread as
the line The diamond in the below is the summary
estimate The two ends of the diamond indicate 95
CI
The size of the black square box indicates weight
of the study
They call it a forest plot so that you dont miss
the wood for the trees!
20
Funnel Plot what and how to read
Plots the effect size against the sample size of
the study To study a funnel plot, look at its
LOWER LEFT corner, thats where negative or null
studies are located If EMPTY, this indicates
PUBLICATION BIAS Note that here, the plot fits
in a funnel, and that the left corner is not all
that empty, but we cannot rule out publication
bias
21
Issues in meta analysis
  • Choosing a model
  • Fixed effects model or random effects?
  • Bias in meta analysis
  • poor quality of trials
  • publication bias
  • Quality control in meta analysis
  • QUOROM guidelines
  • Statistical Software for meta analysis

22
Fixed Effects or Random Effects Model?
Fixed Effects Model
Random Effects Model
  • conduct if it is reasonable to assume underlying
    Rx effect is SAME for all studies
  • Pooling Mantel Haenszel OR
  • Test test of heterogeneity
  • If significant, go for random effects model
  • short 95 CI for summary
  • smaller summary estimate
  • OR0.77 0.72,0.83
  • Conduct if test of heterogeneity is significant
    (shows heterogeneity)
  • Assume that TRUE log odds ratio comes from a
    normal distribution
  • Method DerSimonian Lairs method (DSL) of
    calculating Odds Ratio
  • OR0.78 0.69,0.88

23
Bias in Metaanalysis
  • Poor Quality of Trials
  • To avoid them, learn more at CONSORT statement
  • http//www.consort-statement.org
  • Publication Bias
  • study showing beneficial effects of new treatment
    more likely to be published than one showing no
    effect
  • negative trials assumed to contribute less never
    show up in the literature base
  • use several approaches to avoid this
  • Use Funnel Plots to examine the influence of
    publication bias

24
Quality Control in MAQUOROM Table
  • Detailed Guidelines
  • A Good Checklist
  • Use it for reporting
  • Meta Analysis
  • Systematic reviews

25
Statistical Software for Meta Analysis
  • Huge Checklist
  • http//faculty.ucmerced.edu/wshadish/
  • Free Software
  • EpiMeta from Epi Info
  • Revman from Cochrane Collaboration
  • meta package in R for statistical computing
  • Non-free
  • meta module in STATA

26
Summarizing...
  • Defined meta analysis
  • quantitative research synthesis
  • Outlined basic steps
  • Information retrieval
  • Data Abstraction
  • Data Analysis
  • Model Selection Fixed Effects or Random effects
  • Outlined some issues and listed software

Feel free to shoot questions at
arin.basu_at_gmail.com
Write a Comment
User Comments (0)
About PowerShow.com