Systematic reviews&

Meta-analysis

What is a systematic review?

• It is a structured review integrating statistical analysis of the results from a collection of individual studies.

Meta-analysis

A statistical analysis that combines or integrates

the results of several independent clinical trials

considered by the reviewer to be 'combinable'.

Significance of Meta-analysis Example

Mitchell JRA. Timolol after myocardial infarction: an answer or a new set of questions? BMJ 1981;282:1565-70:

"despite claims that they reduce arrhythmias, cardiac work, and infarct size, we still have no clear evidence that ß blockers improve long-term survival after infarction

despite almost 20 years of clinical trials".

Graphic Display:ß blockers in

secondary prevention after

myocardial infarction.

Cumulative Meta-analysis

Steps to do

• Well-Formulated Question• Efficient Search Strategies• Review Abstracts to Determine Eligibility• Apply Strict Inclusion/Exclusion Criteria• Extract the Data• Perform the Required Analyses (Meta-analysis)• Interpret the Results• Determine Implications for Health Care Policy and

Practice

Methodology• At least 3 reviewers• Trial design characteristics:

Method of randomisation Design (e.g. parallel or crossover) blinding power calculation Source of any funding Allocation concealment : adequate (A), unclear (B), or inadequate (C).

Description of studies

• Why included / excluded• Quality of included studies in details• Sample size of each

Standardization of measures of outcome

Odds and odds ratio

The odds is the number of patients who fulfill the criteria for a given endpoint divided by the number of patients who do not.

For example, the odds of diarrhoea during treatment with an antibiotic in a group of 10 patients may be 4 to 6 (4 with diarrhoea divided by 6 without, 0.66); in a control group the odds may be 1 to 9 (0.11). The odds ratio of treatment to control group would be 6 (0.66÷0.11).

Risk and relative risk

The risk is the number of patients who fulfil the criteria for a given end point divided by the total number of patients .

For example, the risk of diarrhoea during treatment with an antibiotic in a group of 10 patients may be 4 to 10; in the control group the risks may be 1 to 10. The relative risk of treatment to control group would be 4 (0.4÷0.1)

Some Controversies About Meta-Analysis

• Quality of Studies• Many Small Studies or One Big Study?• Publication Bias• Fixed- or Random-Effects Models?

Repeat the analysis

• Excluding the unpublished studies (if there were any)

• Excluding studies of the lowest quality• If there were one or more very large studies,

the analysis would be repeated excluding them to look at how much they dominate the results.

Publication Bias

Select your statistical model

• Fixed effects: Assumes that there is a single fixed treatment effect = no interaction between study and effect of intervention

• Random effects: Assumes different treatment effects of the intervention in different studies

Random-Effects Models

• the confidence interval will be wider =• less certainty in conclusions

• The Cochrane Library use Fixed effect model

Human Albumin Model

• The objective was to review the effectiveness of human albumin administration in prevention of severe ovarian hyperstimulation syndrome

Search strategy

• MEDLINE, • EMBASE, • The MDSG specialised register• Abstracts from conferences• handsearching of core journals • contact with authors of relevant papers.

• Selection criteria

• Only randomised controlled studies

R.R

NNT

• 2.2% in albumin group / 7.7% in control group

• absolute risk reduction was 5.5%• NNT = 1/ARR• For every 18 women at risk of severe

OHSS, albumin infusion will save one more case.

Caution

• Whether this NNT would justify the routine use of albumin infusion in cases at risk of severe OHSS needs to be judged by clinical decision makers.

Keep in mindEvidence may change with more trials

Thank You