systematic review and meta analysis Flashcards
What is involved in a systematic review
review all info available concerning a clearly formulated question, use systematic and explicit methods to identify data, select relevant data, critically appraise research ie include/exclude, collect data from the studies, analyse data
range of qualities of reviews and evidence in literature - summarise and process which info is reliable. critical method for assessing this (critical appraisal)
Why conduct a systematic review
data quantity - number of citations in pubmed increases, because of more publications and more open access journals - you can produce as many articles as you like. Increase because of globalisation, internet and open access. new journal every day. Not feasible as a clinician to read them all
data quality: individual study/case report - unable to conclusively answer a business question, poor study design/small numbers - low power = false -ve results, difficult to generalises. Multiple studies: which source to trust when many are different/diverging, how to compare different studies using different protocols
How do you find systematic reviews
Cochrane - database of systematic reviews, about 8000, range of protocols. reviews updated on new evidence, active resource up to date
Stages in a systematic review
1 - planning review - critical, save time down the line
2a - identification of research
2b - selection of studies - assess volume and select ones interested in
2c - quality assessment
3a - data analysis
3b - data visualisation
3c - reporting and dissemination
planning the review
specify question to be addressed - eg should I recommend the flu jab
what was the focus of the review
find info I the summary
P opulation - all ages/one subgroup eg pregnant women and effect on new born
I ntervention/
C omparison - all methods of administration, there are different ways to give a vaccine and 3 different types
O utcomes - clinical - symptomatic infuenza and influenza like illness: number of cases side effects/days of work lost/specific outcome for pregnancy. Harms - serious systemic adverse effects eg nausea and fever. maternal outcomes -abortion, still birth, preterm birth, maternal death. neonatal - congenital malformations, death. secondary local adverse effects eg redness at site of injection
S tudy designs - RCT and quasi-RCT - compare placebo and vaccine, or different types of vaccine. comparative non-randomised study - efficacy in pregnancy or specific syndromes like Guillain-Barre
identification of research
need to decide in advance when stop getting information
if studies are missing it creates bias
remove duplicates
have inclusion and exclusion criteria
have 2 people doing it - minimise chance of subjectivity and error
quality
clearly defined search criteria - MeSH
search published medical literature - electronic database like Cochrane, Medline and EMBASE
search other sources - reference list citations, conference proceedings, contact researchers to get unpublished studies
Selection of studies
inclusion and exclusion criteria
extract data using data extraction form - methodological quality of studies: study design, description of setting, characteristics, description of vaccines, description of outcomes, publication status, date of study, location of study.
2 people
Study quality assessment
assessed by recognised/user defined criteria
assess biases in study design including selection bias, measurement bias, attrition bias/loss to follow up
preferably assessed before the study results are known
ideally with more than 1 assessor
traffic light rating for bias
Data analysis
odd ratio, relative risk and confidence interval
forest plot - bar show risk left favours vaccine, right risk of vaccine, diamond is the summary of all the evidence
confidence interval - smaller if there is a larger study
What is a meta- analysis
use of statistical techniques in a systematic review to integrate results of included studies
the studies are the primary units of analysis
sub part of review
larger study - has more weight it should have
software helps
generate forest plot
PRIMSA - example of guidelines
Reporting and dissemination
study details tabulated in a meaningful way
should include details of PICOS
includes summary of findings
limitations of systematic reviews and meta-analysis
depend on the amount of evidence that you can find
bias
inconsistency of results - heterogeneity
low study quality
incompleteness of review - ie not all studies included
low number of studies
lack of generalisability
publication bias
data might be in a different language - might not get all sources
give higher/lower odds ratio than expected
studies may not be representative of all valid studies
funnel plot - each study is a point, position determined by result, odds ratio and precision (sample size) no bias = symmetrical about mean, bias: asymmetric - miss lower R/L hand corner
Heterogeneity
inconsistency with study results
sub studies have smaller groups and so weaker evidence
studies differ with respect to: PICOS, clinical differences, methodology differences and unknown study characteristics
I squared give sense of heterogeneity 0= no, 25=low 50 = moderate, 75=high heterogeneity
can ask authors about bias
to explore heterogeneity look at subgroups to see if results differ, meta-regression, sensitivity analysis
Advantages of systematic reviews and meta analysis
pooled overall risk estimate
more reliable and precise estimate of effect
explore differences between studies
identify pub bias
