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EPI-214: Lecture 1 Designing a Systematic Review (Meta-analysis)

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EPI-214: Lecture 1 Designing a Systematic Review (Meta-analysis) Dejana Braithwaite Assistant Professor UCSF Department of Epidemiology and Biostatistics – PowerPoint PPT presentation

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Title: EPI-214: Lecture 1 Designing a Systematic Review (Meta-analysis)


1
EPI-214 Lecture 1 Designing a Systematic Review
(Meta-analysis)
  • Dejana Braithwaite
  • Assistant Professor
  • UCSF Department of Epidemiology and Biostatistics

2
8 steps of a systematic review Bent et al. 2004
1 Formulate research question
Lecture 1
2 Develop review protocol
3 Initiate search strategy
4 Apply inclusion /exclusion criteria
5 Quality appraisal
6 Data abstraction
7 Analysis
Lectures 1, 2 3
8 Interpret findings
3
Whats a Systematic Review?
  • A review of the evidence on a clearly formulated
    question that uses systematic and explicit
    methods to identify, select and critically
    appraise relevant primary research, and to
    extract and analyze data from the studies that
    are included in the review.
  • Cochrane Collaboration

4
and meta-analysis?
  • Statistical combination of gt 2 studies to
    produce single estimate of effect of exposure

5
Rapid growth
  • Pubmed search
  • up to 3/29/2010
  • Systematic review gt1.5 million hits
  • Meta-analysis gt40,000 hits
  • up to 1/1/1990
  • Systematic review 300,994 hits
  • Meta-analysis 845

6
The Cochrane Collaboration International
systematic review initiative
  • Archie Cochranes vision led to the opening of
    the first Cochrane centre (in Oxford, UK) in 1992
    and the founding of the Cochrane Collaboration in
    1993

Source http//www.cochrane.org/cochrane/archieco.
htm
7
Meta-analysis in the NYT accessed 3/30/10
Sattar N, et al. Statins and risk of incident
diabetes a collaborative meta-analysis of
randomised statin trials. Lancet. 2010 Feb
27375(9716)735-42. Epub 2010 Feb 16.
8
Meta-analysis in the NYT February 2010
9
Systematic Review in context
Traditional review Systematic Review Meta-analysis
Author An individual A team A team
Search strategy Individual Based on a protocol Based on a protocol
Summary Conclusion Authors judgement Can be qualitative Summary statistical techniques
10
Narrative review
  • Uses informal, unsystematic and subjective
    methods
  • Searching quality and synthesis not described
  • Disadvantage
  • may have preconceived biases and may
    overestimate value of some studies

11
Systematic review
  • Driven by evidence-based medicine movement and
    Cochrane collaboration
  • Advantages
  • Reduces bias
  • Replicable
  • Resolves controversy between conflicting findings
  • Provides reliable basis for decision making

12
Use of meta-analysis as a prelude to clinical
trials
  • Define pre-trial expected effect sizes
  • sample size estimation
  • Determine effect estimates in key subgroups (e.g.
    based on gender, race/ethnicity or age)
  • Identify sources of heterogeneity in prior
    studies
  • Addressing these sources in design phase of new
    trial

13
Use of meta-analysis in study designs that are
not clinical trials
  • Observational studies
  • (e.g. case control, cohorts, cross-sectional
    prevalence studies, etc.)
  • Studies evaluating diagnostic tests (sensitivity,
    specificity, predictive value)
  • IPD individual patient data studies
  • Qualitative studies (meta-ethnography)

14
Meta-analyses
IPD
Systematic reviews
IPD individual participant data
15
Resources required for systematic reviewing
  • Can be time consuming
  • Team science (to reduce bias)
  • Bibliographic software (e.g. Endnote)
  • Statistical software (if appropriate)

16
Step 1 Formulate research question
17
FINER criteria for research question
Feasible Interesting Novel Ethical Relevant
Hulley S, et al. 2001 Designing Clinical Research
18
  • Patient
  • Disease or condition
  • Stage, severity
  • Demographic characteristics (age, gender, etc.)
  • Intervention (or Exposure)
  • Type of intervention or exposure
  • Dose, duration, timing, route, etc.
  • Comparison
  • Absence of risk or treatment
  • Placebo or alternative therapy

19
Outcome Risk or protective Dichotomous or
continuous Type mortality, morbidity, quality of
life, etc. Study designs RCTs Cohort Case-contro
l Cross-sectional All
20
Formulation of an etiology question
Exposure
Outcome
Is smoking a risk factor for lung cancer?
Exposure
Patient
Are people who smoke regularly at a greater risk
of developing lung cancer as compared to those
who do not smoke?
cohort case-control studies
Outcome
Comparison
21
Formulation of a diagnosis question
Test (intervention)
Outcome
Is MRI a good test for breast cancer?
Outcome
Test (intervention)
Is MRI a more sensitive and specific test in
diagnosing breast cancer as compared to
mammography?
Comparison
22
Step 2 Develop review protocol
23
Protocol
  • Background
  • Objectives
  • Pre-determined selection criteria
  • Planned search strategy
  • Planned data abstraction
  • Proposed method of synthesis of findings
  • Establishment of an advisory group

24
Step 3 Initiate search strategy
25
Where to locate studies
  • Pubmed
  • CINAHL
  • Web of Science
  • EMBASE
  • PsychINFO

26
Additional sources to identify studies for
systematic reviews
  • Reference lists of retrieved articles
  • Manual searching of relevant publications
  • Experts in the field
  • Corresponding or first authors of published
  • studies identified for the systematic review

27
Issues to consider
  • Publication bias
  • Search bias

28
Pubmed citation example
  • Title Interaction between 5-HTTLPR genotype,
    stressful life events and depression
  • Search terms
  • Life stress
  • Life event
  • Depression
  • Depress
  • Serotonin transporter
  • 5-HTTLPR
  • Interaction
  • Moderation

Risch et al. JAMA 2010
29
Step 4 Apply inclusion /exclusion criteria
30
Inclusion/exclusion criteria
  • P - Population
  • I - Intervention
  • C - Comparison (if necessary)
  • O - Outcome
  • T - Type of study (if necessary)
  • Subject headings OR Textwords
  • To find studies using all of the PICO
    elements
  • P and I and C and O (and T)

31
Exclusion criteria
  • Keep log of excluded studies
  • Note reasons for exclusion
  • Have eligibility checked by more than one
    reviewer
  • Develop strategy to resolve disagreements

32
Search strategy example
Risch et al. JAMA 2010
33
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34
Step 5 Quality appraisal
35
Principles of quality appraisal
  • Quantitative studies
  • Internal Validity
  • allocation bias, confounding, attrition,
    statistical
  • analysis, intervention integrity, withdrawals and
  • dropouts
  • External Validity (generalizability or
    applicability)

36
Are there quality appraisal tools?
37
QUORUM for trials
  • Moher et al. Improving the quality of reports of
    meta-analyses of randomized controlled trials
    The QUORUM statement. Lancet 19993541896-1900

38
MOOSE for observational designs
  • Stroup et al. Meta-analysis of observational
    studies in epidemiology. JAMA 20002832008-12

39
Qualitative research
  • Checklists available to assess the quality of
    qualitative research. E.g. CASP appraisal tool
    for qualitative research (http//www.phru.nhs.uk/c
    asp/qualitat.htm)

40
Recruit participants
SELECTION BIAS
ALLOCATION BIAS
Allocate to intervention and control groups
Intervention group
Control group
CONFOUNDING
INTEGRITY OF INTERVENTION
Implement intervention
Implement intervention
INTENTION-TO-TREAT
Follow-up participants
Follow-up participants
WITHDRAWALS/ DROP OUTS
Measure outcomes
Measure outcomes
BLINDING OUTCOME ASSESSORS
DATA COLLECTION METHODS
Analyze outcomes
Analyze outcomes
STATISTICAL ANALYSIS
41
Step 6 Data abstraction
42
Data abstraction
  • Design and pilot data abstraction form
  • Consider gt1 reviewer
  • Consider blinding of observers to authors,
    institutions and journals

43
Data abstraction elements
publication details study design population
details (n, characteristics) intervention
details setting outcomes and findings
44
Summary of study characteristics - example
Risch et al. JAMA 2009
45
Data abstraction examples
  • http//www.cochrane.org

46
Step 7 Analysis
47
Synthesizing the Evidence
  • NARRATIVE SYNTHESIS
  • primary studies explained qualitatively and
    summarized
  • META-ANALYSIS
  • findings summarized and then combined
    statistically

48
Is there heterogeneity?
No
Yes
Meta-analysis
Narrative synthesis
Deal with heterogeneity? (e.g. subgroup
analysis)
49
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50
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51
Guidelines for narrative synthesis
  • Not available yet

52
Step 8 Interpret findings
53
Interpretation of results
  • Strength of the evidence
  • Explanations of effectiveness
  • Applicability
  • Trade-offs between benefits and harms
  • Implications for practice

54
Strength of the evidence
  • Describe the overall strength of the evidence
  • The quality of the evidence
  • The size and consistency of the results
    (particularly important in population based
    studies where a small effect at the community
    level may have much significance than the effect
    of comparable size at the individual level)
  • Describe biases and limitations of the review
    process (e.g. difficulties in locating articles,
    inability to translate non-English articles)

55
8 steps of a systematic review Bent et al. 2004
1 Formulate research question
Lecture 1
2 Develop review protocol
3 Initiate search strategy
4 Apply inclusion /exclusion criteria
5 Quality appraisal
6 Data abstraction
7 Analysis
Lectures 1,2 3
8 Interpret findings
56
Section 1 Assignment Developing a Protocol for a
Systematic Review
  • Homework
  • Write a 1-2 page protocol to address the clinical
    problem described in the assignment.
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