Flashcards in L13. Systematic Reviews and Meta-analyses Deck (26):
What is the Cochrane Collaboration and why does it exists?
A group formed to organise medical research information systemically to aid in evidence based medicine. They conduct systematic reviews of randomised controlled trials.
What is a Systematic Review? And what are the four main aims of the systematic review?
It is a literature review that focuses on answering a single question.
It aims to identify, appraise, select and synthesise high quality evidence to answer a question.
What is important to a systematic review?
A well-defined criteria for the review
What kind of data do systematic reviews analyse?
Both Clinical Trial (mainly) and Observational data
What kind of analysis gives the highest level of incidence? Is this always the case?
Systematic reviews often give the highest level of evidence of the study types.
However, a well conducted randomised controlled trail that is very rigorous may have the potential to have a higher level of evidence.
What is a meta-analysis?
The statistical aspect of a systematic review: analysis of the combined data from multiple studies
How is the meta-analysis data pooled?
Derived pooled into a weighted average based on the size of the effect of the findings.
What are the 4 purposes of a meta-analysis
1. Increase the power
2. Resolve uncertainty
3. Improve estimates of effect size (increase precision)
4. Answer other questions
How do we identify what studies to use?
Having a clear clinical or research question that you want to answer based on studies.
What are some data sources to use to find studies? 
Medline, embase, central and other databases
Reference lists of relevant papers
Others like 'grey literature' or websites
What important considerations must be made when searching through databases?
Using standard (MESH-medical subject headings) terms where possible, include all relevant spellings and types of terms, limits (eg. only including randomly controlled trials in the search).
What is 'grey literature' and why may some of the findings from these be important?
Studies conducted that are unpublished. These are important as they may be just as rigorous in nature as the published studies and may hold relevant information like negative results or null results which are just as important in a systemic review.
How do we decide on what to include and exclude from the systematic review? (what criteria)
Whether they are in line with the question being asked
Other parameters (like sample size)
It is important to not introduce bias when selecting for papers to include/exclude from systemic analyses. Give 2 examples where bias may be introduced
1. When screening for larger sample sizes in studies (these have higher power) you may be introducing selection bias as larger studies often com from larger centres with funding and aiming for a certain result. You may be discounting important information from smaller funded research.
2. Studies published in different languages are sometimes excluded for purposes of convenience but they may contain very important and relevant information
What are the steps  in selecting and appraising studies?
1. At least 2 people independently start the search
2. Reading all abstracts that are relevant (important to note that abstracts don't always reflect the quality of the study).
3. Apply the inclusion and exclusion criteria to abstracts
4. Obtain full papers
5. Asses the papers (particularly the methods) for quality
What are Consolidated Standards of Reporting Trails? What can the include?
Guidelines are available to help analyse the quality of a paper?
They often include checklists and flow charts
What is an important thing to asses in studies when conducting systematic reviews? What is the inherent risk in this.
The risk of bias and confounding: this in itself is a subjective measure
How do we undertake meta-analysis?
Statistical software and analysing how statistical analysis was undertaken in different studies.
What is the concept of a weighted average?
Weighted average, also called EFFECT SIZE results from the multiplication of each component by a factor reflecting its importance.
How do we achieve a weighted average in meta-analysis?
Studies are assessed and compared to according to the quality of data each study had. And then from this extrapolate how much of an effect or weight (% or proportion wise) that study will affect the meta-analysis. The higher the quality, the larger its weighting
What determines the weighting of individual studies?
Sample size and Inverse variance
What is inverse variance?
Variance is the deviation of the outcome of the study from the mean outcome of the combined study analysis. The greater the variance, the lower the weighting it will have in the overall meta analysis. Thus the weighting is inversely proportional to the variance.
What is meant by heterogeneity of the studies in meta-analysis? What is desired?
Heterogeneity is the variability in the effect sizes (weighted average) in terms of whether they similar to one another in nature to be pooled. The HIGHER the P value the less likely they are different so this is a good number (high similarity).
What is a forest plot? What kind of information does it include?
A quick way to record the information from a systematic review.
It includes a test for heterogeneity, the line of the null effect of each study and their confidence intervals (size of the square is the weighing of the study and the width indicates confidence interval), the pooled effect (shown by diamonds).
What are some considerations in deciding heterogeneity?
Statistical analysis: comparing effect sizes and variances
Non-statistical: PICOT (cannot be objectively assessed)