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Clinical Trials > Systematic reviews > Flashcards

Systematic reviews Flashcards

1
Q

Why do we need to review research?

A

So many articles, we need a good summary

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2
Q

What is a review?

A

Summary of what is known, often prepared by an expert and can be on any topic

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3
Q

What are the advantages of a traditional review? 3

A

Summarise everything Give flavor of a subject Might point us towards original research

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4
Q

What are the problems with a traditional review?4+

A

Messy Not clear Only sees part of the picture Unscientific- not standardised, no clear purpose, presents impressions of one individual

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5
Q

What do systemic reviews do?

A

Allow us to objectively review all available evidence Attempt to collate all evidence to answer a specific question using systemic ways More reliable

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6
Q

What do systemic reviews mostly look at?

A

effects of a treatment on a disease

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7
Q

Where does the best evidence for systemic reviews come from?

A

Randomised controlled trials

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8
Q

What type of data do most systemic reviews use?

A

Summary/aggregate data

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9
Q

What does a protocol for a systemic review need to have?6

A

Clear question with objectives set out search strategy to identify all trials consistent data collection across all trials Assessment of trial quality Synthesis of results Structured presentation of results

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10
Q

5 things systemic reviews should specify

A

PICOS Population Intervention Comparison Outcomes Study design

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11
Q

How to ensure the studies are similar

A

Set up good eligibility criteria Include trials with sim questions Some difference eg dosage expected

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12
Q

Where do you find studies: how

A

Rely on bibliographic data bases, build a structured search strategy and use index terms and free text terms

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13
Q

Biases involved with finding studies?

A

Studies with more dramatic results are more likely to be published, quicker and in better journals Publication bias, time lag bias, language bias –> reporting biases

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14
Q

How to avoid reporting biases?

A

All relevant trials published and unpublished checked

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15
Q

other than bibliographic data bases, where to look? 5

A

Grey literature Conference abstracts and proceedings Trial registers References for relevant articles Ask experts in fields

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16
Q

Which studies do you exclude?

A

Ineligible populations, interventions, comparisons and study types

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17
Q

How to collate data?

A

Using a predefined form

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18
Q

3 other challenges with obtaining enough data: what to do

A

Trial authors might not report results for some outcomes Not give detailed report of methods Not state exclusions –> ask for missing data

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19
Q

Why do you need to assess study quality?

A

Trials with poor design, conduct or analysis may over or underestimate effect of treatments

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20
Q

How to assess quality of studies?

A

Need to extract info to judge (methods of randomisation, analysis methods, outcomes)

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21
Q

A good systematic review will: 3

A

Provide a comprehensive objective and unbiased summary of all evidence Overcome problems with traditional reviews Results can be presented narratively as it will have a meta analysis

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22
Q

What is a meta analysis?

A

Quantitatively combining results of related trials to get an overall average effect of treatment

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23
Q

Why use meta analysis?3

A

To detect smaller effects reliably (they might still be very imp) Provides more patients than any one trial so greater power to detect difference between treatment and control and greater confidence that estimate of effects represent the truth

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24
Q

why do you need a systematic review with the meta analysis?

A

To prevent biased results

25
Q

2 stages of meta analysis

A

Extract or calculate estimate of effects of each trial combine these to get overall estimate of effect

26
Q

Formula for meta analysis

A

Meta analysis effect = Sum of (trial effects x weight)/ sum of weights

27
Q

How is meta analysis results presented?

A

Forest plot

28
Q

What are time to event outcomes?

A

Whether things do or dont happen over a period of time

29
Q

How are time to event outcome events usually measured?

A

Hazard Ratio

30
Q

What does hazard ratio

A

Benefit

31
Q

How do you get relative effect of treatment in a time to event outcome?

A

1-HR

32
Q

What is a continuous outcome?

A

Whether a disease or participant measure changes

33
Q

How are continuous outcomes measured?

A

Mean difference or standard mean difference

34
Q

Mean difference

A

benefit

35
Q

Why would you get heterogeneity between trials?

A

Dif populations, treatments, trial designs…

36
Q

When do you call it a statistical heterogeneity?

A

Difference is > expected by chance

37
Q

How to test for heterogeneity?

A

Heterogeneity Chi2 I2 Stat

38
Q

With heterogeneity chi2, what results could mean heterogeneity?

A

P

39
Q

What unit does I2 stat work with?

A

Percentages

40
Q

I2 stat results range show:

A

Low - low heterogeneity high - high heterogeneity

41
Q

Difference between fixed effect model and random effects model:

A

Fixed assumes same effect in each trial and weights by trial size Random assumes normal distribution of effect around mean and weights by trial size and heterogeneity

42
Q

When do people use random effects?

A

They use it to allow for any heterogeneity,

43
Q

What does random effects do if moderate heterogeneity?

A

Small trials have more weight, the random effects confidence interval is wider, fixed and random effects may differ - explore how and why results vary

44
Q

If no heterogeneity, what does random effects do?

A

if none, big trials have more weight and both fixed and random give same results

45
Q

If there is substantial heterogeneity what do you get for chi2 and I2?

A

Very small chi 2 p value and I2 close to 100%

46
Q

Fixed vs random effects if substantial heterogeneity?

A

Results vary loads

47
Q

Problem if substantial heterogeneity:

A

Is meta analysis justified?

48
Q

What questions should you ask when exploring heterogeneity of effects?

A

Do they vary by treatment or other trial characteristics? Do they vary by participant characteristics?

49
Q

How to find out what the studies vary by?

A

Trial subgroup analysis or sensitivity analusis

50
Q

How to figure out if the trials vary by participant characteristics:

A

Need data on each patient - IPD

51
Q

How do we do a sensitivity analysis?example

A

Do meta analysis of all trials, then do meta analysis after excluding the two largest trials - how similar are the results?

52
Q

How to do a trial subgroup analysis?

A

Group them by ie chemo regimen DO mini meta analysis for each subgroup Compare results

53
Q

What types of data can meta analysis be based on?

A

Aggregate and individual participant data (IPD) - raw data

54
Q

Aggregate data explain:

A

Often limited to published trials data common and quick

55
Q

IPD explain:

A

Get raw data, validate and reanalyse Gold standard take longer and more resource intensive

56
Q

How do you plan an analysis:

A

Analysis shouldn’t be driven by results: need a protocol including outcome measures, meta analysis models and how an effect varies by trial

57
Q

When is meta analysis not appropriate?3

A

Effects are v heterogeneous Data insufficient or very variable Trials are of poor quality

58
Q

What guidelines do you follow for systematic reviews?

A

PRISMA guidelines

59
Q

What do PRISMA guidelines aim to do?

A

Improve reporting of systematic reviews and meta analysis help users of published systematic reviews critically appraise them

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