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LS1 HaDPop > L11 - Reviewing the evidence > Flashcards

L11 - Reviewing the evidence Flashcards

1
Q

What is a meta-analysis?

A

A quantitative synthesis of the results of two or more primary studies that addressed the same hypothesis in the same way

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2
Q

Describe the limitations of using evidence from single studies

A

a

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3
Q

What is the purpose of a systematic review?

A

A systematic review summarises the results of available carefully designed healthcare studies (controlled trials) and provides a high level of evidence on the effectiveness of healthcare interventions. Judgments may be made about the evidence and inform recommendations for healthcare.

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4
Q

Under what circumstances should a systematic review be undertaken?

A

It should have:

  1. Clearly focused question
  2. Explicit statements about:
    (i) types of study
    (ii) types of participants
    (iii) types of interventions
    (iv) types of outcome measures
  3. Systematic literature search
  4. Selection of the material
  5. Appraisal
  6. Synthesis (possibly including a meta-analysis)
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5
Q

What is a systematic review?

A

An overview of primary studies that used explicit and reproducible methods.

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6
Q

What is a ‘forest-plot’?

A

A graphical representation of a meta-analysis which plots a measure of study size against a measure of effect (e.g. Odds Ratio)

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7
Q

What are the common difficulties in systematic reviews?

A

a

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8
Q

What are the common difficulties in meta-analyses?

A
  1. Heterogeneity between studies
    (i) modelling for variation: fixed vs random effects model
    (ii) analysing the variation: sub-group analysis
  2. Variable quality of the studies
  3. Publication bias in the studies
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9
Q

What is publication bias?

A

When studies with statistically significant or ‘favourable’ results are more likely to be published than those studies with non-statistically significant or ‘unfavourable’ results - this particularly applies to smaller studies.

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10
Q

What effect does publication bias have?

A

Publication bias leads to a biased selection of studies towards the demonstration of effect

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11
Q

List three types of observational study: one descriptive and two association studies

A

Descriptive (proportion) - prevalence study

Association (ratio) - cohort and case-control studies

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12
Q

Name an experimental study type

A

Randomised controlled trials (RCTs) (comparison - ratio)

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13
Q

What is the difference in the analysed ratios of cohort/case-control studies and randomised controlled trials?

A

Cohort/case-control studies is a ratio of association

RCTs is a ratio of comparison

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14
Q

Name three types of broad classification or studies

A
  1. Primary research studies
  2. Literature reviews: narrative, systematic
  3. Decision analyses
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15
Q

What is the purpose of a decision analysis study?

A

Harms and benefits

Cost-effectiveness

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16
Q

Describe the features of a narrative review

A

Implicit assumptions, opaque methodology, not reproducible -> biased and subjective

17
Q

Describe the feature of a systematic review

A

Explicit assumptions, transparent methodology, reproducible -> unbiased and objective

18
Q

List some type of primary research studies

A

RCTs
Cohort studies
Case-control studies

19
Q

What are the purposes of a meta-analysis?

A
  1. To facilitate the synthesis of a large number of study results
  2. To systematically collate study results
  3. To reduce problems in interpretation due to variations in sampling
  4. TO QUANTIFY EFFECT SIZES AND THEIR UNCERTAINTY AS A POOLED ESTIMATE
20
Q

What are the quality criteria for a meta-analysis?

A

They should have a formal protocol specifiying:

  1. Compilation of complete set of studies
  2. Identification of common variable or category definition
  3. Standardised data extraction
  4. Analysis for sources of variation
21
Q

Why would a systematic review not necessarily include a meta-analysis?

A

If e.g. clinical heterogeneity was too great.

22
Q

How does a meta-analysis analyse all the studies?

A
  1. ORs and % CIs calculated for all studies
  2. Pooled estimate OR
  3. Studies weighted due to their size and the uncertainty of their OR (smaller EF, greater weight to result)
23
Q

How do you interpret a forest plot?

A 
ORs are represented by squares
95% CIs by libes
Size of square proportional to weight given to the study
Diamond=pooled estimate
Diamond centre (dotted line) = pooled OR
Diamond width= pooled 95% CI
Solid line = null hypothesis OR
24
Q

What are the assumptions of the fixed effect model for calculating the pooled estimate odds ratio and 95% CI?

A

That the studies are estimating exactly the same effect size

25
Q

What are the assumptions of the random effects model for calculating the pooled estimate odds ratio and 95% CI?

A

Assumes that studies are estimating similar, not the same, effect sizes

26
Q

Random effects modelling can only be used for modelling variation (accounting for it), what can be used to explain variation?

A

Sub-group analysis can help explain heterogeneity which may provide further insight into the effect of a treatment or exposure

27
Q

What are the two types of sub-group analysis?

A
  1. Stratification by study characteristics e.g. length of follow-up
  2. Stratification by participant profile e.g. age group, sex (however data is often unavailable)
28
Q

Studies are of variable quality. List from easier to assess to harder to assess the following causes of poor quality studies:
Poor protocol implementation
poor study design
poor design protocol

A

poor study design
poor design protocol
poor protocol implementation

29
Q 
List the following studies from least prone to bias and confounding to most prone:
randomised controlled trials
cohort studies
non-randomised controlled trials
case-control studies
A

randomised controlled trials
non-randomised controlled trials
cohort studies
case-control studies

30
Q

What are the two approaches for assessing the quality of studies that are included in meta-analyses

A
  1. Define a basic standard that studies must meet to be included e.g. Cochrane studies used to only include RCTs
  2. Score each study for its quality and then:
    (i) incoportate the quality store into the weighting allocated to each study
    (ii) use sub-group analyses to explore differences
    (iii) meta-regression analyses - i.e. weighted linear regression of effect size against quality
31
Q

What components of e.g. RCTs need to be considered when assesing their quality?

A

allocation methods e.g. randomisation
blinding and outcome assessment
patient attrition - intention-to-treat
appropiate statistical analysis

32
Q

How can you check for publication bias in the selection of studies?

A
  1. Check meta-analysis protocol for how they searched for and identified unpublished studies
  2. Plot identified studies against a measure of their size - A FUNNEL PLOT
  3. Use a statistical test for publication bias (tend to be weak statistical tests)
33
Q

What does a ‘funnel plot’ plot?

A

A measure of study size (y-axis) against a measure of effect (x-axis) (e.g. Odds ratio)

34
Q

How would you analyse a funnel plot for publication bias?

A

Smaller studies can be expected to vary further from the central effect size.
Publication bias is likely to exist if there are few small studies with results indication small or ‘negative’ measure of effect

35
Q

What is the p-value of tests for (statisical) heterogeneity if the differences in individual trial results are not consistent with heterogenity (e.g. systematic heterogeneity between trial results is likely)?

A

p=

36
Q

If heterogeneity test results for a meta-analysis were below 0.05 why would that raise concerns about the analysis?

A

It would raise concerns as to whether the individual trial results should be pooled. A statistical solution would be to use a different statistical analysis based on a ‘random effects’ model rather than a ‘fixed effects’ model, giving wider confidence intervals

37
Q

Give an example of a critical appraisal tool that can be used for systematic reviews

A

CASP

LS1 HaDPop (6 decks)

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