77 - Systematic Reviews and Meta-Analyses Flashcards
50 packet years
Equivalent of smoking a peck per day for 50 years
Definition of a systematic review
Literature review focussed on a single question
Identifies, appraises, selects and synthesises high-quality evidence relevant to question.
Narrow area of review
Meta-analysis
Statistical aspect of a systematic review
Analysis of combined data from multiple studies
Purposes of meta-analyses 1 2 3 4
1) Increase power
2) Resolve uncertainty
3) Improve estimates of effect size (precision)
4) Answer other questions
Highest level of evidence
Systematic review
How can studies for a systematic review be identified?
Use PICOT method (population, intervention, comparator, outcome, time)
MESH
Medical subject headings.
Tags on pieces of research
Data sources for systematic reviews
1
2
3
1) MEDLINE, EMBASE, CENTRAL, CINAHL, DARE, etc.
2) Reference lists of publications can be helpful
3) Grey literature - mightn’t be in mainstream literature, but might still be relevant (EG: negative findings, no statistically significant findings)
Inclusion/exclusion criteria
1
2
3
1) PICOT (population, intervention, comparator, outcome, time)
2) Other parameters (EG: only include studies over a certain sample size)
3) Need to be careful not to introduce selection bias
How are studies selected for systematic reviews? 1 2 3 4 5
1) At least two people independently select papers
2) Read all abstracts
3) Apply inclusion/exclusion criteria
4) Obtain full papers
5) Assess for quality
Example of consolidated standards for reporting trials
CONSORT guidelines for assessing trial quality
How can risk of bias be assessed?
Look at methods, see if methods are conducive to minimising bias
Example of statistical software
STATA
Key statistical issues in a meta-analysis
1
2
3
1) Outcome (weighted average effect size)
2) Weighting of individual studies
3) Heterogeneity (variability in effect sizes)
Examples of weighting of average effect size
Relative measure (RR, OR) Absolute measure (mean difference)
