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An introduction to systematic reviews and meta-analyses. Colin Josephson Assistant Professor of Neurology University of Calgary. Faculty/Presenter Disclosure. Faculty: Colin Josephson Relationships with commercial interests: Grants/Research Support: Nil Speakers Bureau/Honoraria: Nil
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An introduction to systematic reviews and meta-analyses Colin Josephson Assistant Professor of Neurology University of Calgary
Faculty/Presenter Disclosure • Faculty: Colin Josephson • Relationships with commercial interests: • Grants/Research Support: Nil • Speakers Bureau/Honoraria: Nil • Consulting fees: Nil • Other: Nil
Disclosure of Commercial Support • This program has received financial support from: Nil • This program has received in-kind support from: Nil • Potential conflict(s) of interest: • Nil
“That’s so meta…” • Greek: prefix for ‘after’ or ‘beyond’ • English: abstraction form a concept that is used to complete or add to said concept • Unfortunately now a ‘hipsterism’
A lot of work…but for what? • Traditional ‘narrative’ reviews are at high risk of bias • Systematic reviews address a specific question in a standardised, reproducible manner • If low heterogeneity (statistical inconsistency) then aggregating data is possible
What we want to avoid… Publication bias (selective reporting) Cochrane Handbook
The ideal result Cochrane Handbook
The ‘systematic’ approach PICOST JAMA Users Guide to the Medical Literature
Judge a man by his questions… • What was the question of the review? • Was it sensible, clinically relevant, and focused? • PICOST • A narrow, precise question diminishes the risk of heterogeneity, thus providing accurate conclusions
Examples • What is the effect of surgery on epilepsy outcomes (e.g. seizure-freedom and quality of life)? • What is the effect of resective surgery on seizure freedom? • In patients with TLE secondary to MTS (P), what is the effect of an ATL (I) compared to medical management (C) on seizure-freedom (O) in randomised controlled trials (S) measured at one-year (T)
The ‘systematic’ approach Statistical plan (PROSPERO) JAMA Users Guide to the Medical Literature
Heterogeneity • Clinical: • Population, intervention, outcome (systematic bias) • Methodology: • Study design (systematic bias) • Statistical • Variability in intervention effects (random error)
Means of addressing heterogeneity • Refrain from performing a meta-analysis • Explore heterogeneity through subgroup analyses or meta-regression • Pre-specify heterogeneity level (fixed-effects) • Perform a random-effects meta-analysis • Change the effect measure • Exclude studies after careful consideration
Fixed effects meta-analyses • Assumes one true treatment effect • Thus, differences across trials can only be due to one source of error (i.e. random error) e.g. TLE secondary to MTS Borenstein et al., 2007
Random effects meta-analyses • Assumes many treatment effects of which there is a ‘mean’ true effect e.g. epilepsy type
Random effects meta-analyses • Assumes many effects of which there is a ‘mean’ true effect • Two sources of error (random error around the true effect and random error around the mean of true effects) e.g. epilepsy type Borenstein et al., 2007
The ‘systematic’ approach Conducting the review JAMA Users Guide to the Medical Literature
Conducting the review • Comprehensive search strategy using multiple databases • Some argue that searching MEDLINE, EMBASE, and Cochrane Central is the bare minimum • Additional sources and grey literature: • Trial registries • Reference lists • Personal communications
‘Searching ain’t easy…’ Josephson et al., Cochrane Database of Systematic Reviews 2014
Databases…just a sampler • MEDLINE • PUBMED • EMBASE • Cochrane Central • TRIP • DARE • WHO ICTRP • Google Scholar
Publication bias Cochrane Handbook
Duplication,duplication • Involvement of two or more reviewers and abstractors ensures reproducibility of the process • Why? Because it is impossible to avoid some degree of subjectivity and, thus, error • The kappa statistic is highly informative (greater IRR suggests more confidence in the process)
Kappa Byrt, Epidemiology, 1996
The ‘systematic’ approach Performing the analyses JAMA Users Guide to the Medical Literature
See the forest for the trees Josephson et al., Neurology, 2013
Mantel-Haenszelfixed effect Contingency table M-H weighted average
Mantel-Haenszelfixed effect ssRR= 0.88 ssRR= 1.16 M-H weighted average: ((400*400) + (7*5))/(1000+20) 160035/1020 156.8 RR= 1 1 2 2 1 2 = = = 0.89 ((300*600) + (2*15))/(1000+20) 180030/1020 176.5
DerSimonian and Laird Contingency table DSL Estimate: v = within study variance t = between study variance
Was it correct to pool? Josephson et al., Neurology, 2013
Measuring heterogeneity – Cochran Q Nomenclature: wi = individual study’s weight (1/v) Ti = individual study’s effect size T-bar = mean effect size • Form of chi-square test • p-value of 0.1 is typically used for significance • Caveat: • Low power = insensitive • High power = too sensitive Cochrane Handbook
Measuring heterogeneity – I2 statistic • % variability in the effect estimate that is more than chance alone (i.e. due to heterogeneity rather than random error) • 0-40% = might not be important • 30-60% = may represent moderate heterogeneity • 50-90% = may represent substantial heterogeneity • 75-100% = considerable heterogeneity Cochrane Handbook
Confidence = ‘GRADE’ the results GRADE Type of evidence (RCT vs. observational) Quality (blinding, allocation, f/u, sparse data, methodology) Consistency of results (within or between studies) Directness (generalisability) Effect size (e.g. >5 or <0.2 for all studies)
Additional quality scales Jadad: RCTs Newcastle-Ottawa Scale: non-RCTs
Quality summary table(e.g. QUADAS scale) Josephson et al., Cochrane Database of Systematic Reviews 2014
Summary of findings table Cochrane Handbook
Required for all studies! • Checklist outlining all essential steps of the review to facilitate quality control • www.prisma-statement.org
Conclusions PICOST Statistical plan (PROSPERO) Performing the analyses JAMA Users Guide to the Medical Literature