1. Critical Appraisal Level 2
Evaluating studies using the Critical Appraisal Skills Programme (CASP) Tools

2. What is Critical Appraisal?
Critical appraisal is the process of systematically examining research papers before using the evidence to form a decision
Critical appraisal allows us to make sense of research evidence and close the gap between research and practice

3. Why Critically Appraise?
In evidence based medicine the clinician should use the best available evidence to decide which treatment option is best for their patient
To determine the best treatment option we must have critical appraisal skills to assess the quality of research

4. Advantages of Critical Appraisal
Provides a systematic way of assessing the validity, results and usefulness of published research
Allows us to improve healthcare quality
Encourages objective assessment of the usefulness of all information/evidence
Critical appraisal skills are not difficult to develop – mostly common sense!

5. Disadvantages of Critical Appraisal
Can be time consuming
It may highlight that current practice is in fact ineffective
May highlight a lack of good evidence in an area of interest

6. Help with Critical Appraisal
It is difficult to remember all the issues which must be taken into account when reading research papers
To help with this the Public Health Resource Unit in Oxford have produced tools to evaluate most types of study as part of the Critical Appraisal Study Programme (CASP)
These are called CASP tools

7. CASP Tools CASP Tools have been developed to help us appraise:
Systematic Reviews
RCTs
Case-control studies
Cohort Studies
Tools for other types of study (e.g. qualitative research, economic evaluations and diagnostic studies) are also available

8. CASP Tools (2)
The tools break critical appraisal of each study type into manageable questions
The questions in each tool will vary slighty as study designs are different
They are available at:

9. Randomised Controlled Trials (RCTSs)
RCTs are the best type of research study to determine if a specific intervention produced the desired outcome in a specific population
e.g. The HOPE study: Does ramipril (the intervention) prevent myocardial infarction, stroke or death from cardiovascular causes (the outcomes) in patients who were at high risk for cardiovascular events but who did not have left ventricular dysfunction or heart disease (the population)

10. RCTs (continued)
RCTs should have a clearly defined research question in relation to the population, outcome and intervention
RCTs can minimise bias and use the most appropriate study design for investigating the effectiveness of a specific intervention or treatment
RCTs are, however, not automatically of good quality and should be appraised critically

11. Appraising RCTs
Three broad issues should be considered when examining a report of an RCT:
Validity
Results
Relevance
The CASP tool prompts us to ask questions which will assess each of these issues in more detail

12. Screening Questions in CASP tool
Questions 1 and 2 in the RCT CASP tool are screening questions to assess if:
The RCT asks a clearly focused study question (i.e. is population, intervention and outcome being investigated clearly stated?)
Whether an RCT is the most appropriate study design to ask this question
If the answer to either of these is “no” then it is probably not worth continuing with the rest of the questions

13. Validity
When assessing validity the methods used in the study are appraised
If the research methods are flawed then this may invalidate the results of the trial
To critically appraise the methodology of an RCT you will look at sample size, randomisation and baseline characteristics, blinding, follow-up, data collection and interventions. These elements are dealt with by questions 3-7 in the CASP tool for RCTs

14. Randomisation and Baseline Characteristics (Q3 in CASP Tool)
Randomisation reduces the possibility of bias
Method of randomisation should be robust and neither the participants or clinicians should be aware which group patients will be in before randomisation
Most robust methods are computer- generated numbers or tables of random numbers (gives 50:50 chance of being in either group)
Stratification can be used to ensure similar baseline characteristics in both groups

15. Randomisation and Baseline Characteristics (Q3 in CASP Tool)
The make-up of treatment and control groups should be very similar and the only difference should be the intervention under investigation in the study
This is so that we can be confident that the outcome is due to the intervention and not to any other confounding factors
Consider:
Is the sample large enough? (see also Q7)
Was the randomisation process robust?
Was there stratification?

16. Blinding (Q4 in CASP Tool)
If the people involved in the study are not aware who is in the treatment or control group this reduces the possibility of bias i.e. ideally a study should be double-blind
Single-blind and open-label studies would be expected to have higher chance of producing biased results
To blind patients and clinicians the intervention and placebo must appear to be identical – this is not always possible
Consider – if every effort was made to achieve blinding
-if it matters in the study being reviewed (i.e. could there be observer bias in the results that are used?)

17. Follow-up (Q5 in CASP tool)
If a large number of participants withdraw from a trial before its conclusion their loss may distort the results
Crossover between groups can also distort the results as the effects of randomisation can be lost
In most cases intention-to-treat analysis should be used – i.e. the final results should be analysed according to the original randomisation

18. Interventions (Q6 in CASP tool)
It is important that, aside from the intervention under investigation, the groups are treated equally as this means the outcome of the study can be attributed to the intervention
Consider:
Were groups reviewed at the same time intervals?
Were any other treatments allowed in either group?

19. Interventions (Q6 in CASP tool)
Also consider:
If tests or measurement s were used were they conducted by appropriate personnel and established tests were used?
Were assessments frequent enough to show a pattern of response?
Is the duration of the study sufficient?

20. Sample Size (Q7 in CASP tool)
A study should include enough participants so that the researchers can be reasonably sure that there is a high chance of detecting a beneficial effect
A power calculation should be carried out before the participants are enrolled to estimate how many people need to be recruited to achieve a certain level of certainty (usually aim for 80-90%)

21. Results
The results of a RCT should be scrutinised in a similar way to the method
Broad considerations are:
What are the results?
How are the results presented?
How precise are the results?
This is dealt with by questions 8 and 9 in the CASP RCT tool

22. Presentation of Results (Q8 in CASP tool)
Results can be expressed as:
Relative Risk – if we hope that the intervention will lead to LESS outcomes (e.g. MI, stroke, death) we want a hazard ratio of less than 1
Absolute Risk – proportion of people experiencing an event in each group
Results may be reported as either of the above or as both

23. Presentation of Results (2)
The results presented should relate to the objectives set out in the original description of the study method
Relative or absolute measures may have little meaning in relation to clinical practice
Numbers needed to treat (NNT) may make measures more understandable
NNT is the number of people who must be treated to produce one additional successful outcome

24. Precision of Results (Q9 in CASP tool)
Statistical tests are used to establish whether the results of a trial are real or whether they occurred purely by chance
There will always be some doubt as the trial only looks at a sample of the population
Confidence intervals and p-values indicate the level of certainty around the results

25. Confidence Intervals (CI)
Inferences based on random samples are uncertain because different results would be obtained each time a study was repeated
CIs indicate the range of doubt around the results and represent the range of values within which the true value lies
Therefore, the narrower the range, the more convincing the results
If CIs overlap this indicates that the study has failed to demonstrate a difference

26. P-values
P-values describe the probability that a result has happened by chance
P<0.05 is usually described as statistically significant and means that the results are unlikely to be due to chance

27. Statistics Used
There should be adequate statistical analysis of the relevant results and the statistical analysis used should be appropriate to trial size and design
Statistical tests used should be adequately described and referenced
Consider whether a statistician is listed as one of the authors

28. Clinical vs. Statistical Significance
A statistically significant difference in favour of a drug does not always indicate a clinically significant difference
e.g. in a study of two antihypertensives a difference in BP of 1-2mmHg may be statistically significant but is this likely to confer significant clinical benefit?
Also consider surrogate markers versus clinical endpoints (e.g. an increase in bone mineral density versus a decrease in fracture rate)

29. Relevance
If the methodology and results are acceptable then the applicability of the results to the local population should be considered
Some broad issues include:
Relevance to the local population
Were the outcomes considered clinically important?
Risk versus benefit of treatment
Q10 in the CASP tool prompts us to consider the issues around the relevance of our study to our local population

30. Relevance to Local Population
It is important to consider if there are any differences between the participants in the trial and the local population that would make it impossible to apply the results locally. Think about:
Inclusion/exclusion criteria – e.g. age, ethnicity, co-morbidities, concomitant medication
Local healthcare provision – the setting may have been in a different healthcare system and it may not be possible to provide similar care locally
Control group – is the standard treatment used in the study better or worse than local standard? Are realistic comparative doses used?

31. Importance of outcomes
Were all clinically important outcomes considered? A single RCT is unlikely to address all the clinically important outcomes but consider if the original question has been answered and if any other important outcomes have been missed out.
Think about outcomes form the point of view of:
The patient and their family/carers
The clinician using the treatment
Policymakers
The wider community

32. Risks versus Benefits Risks:
Safety – the risk of serious side effects may outweigh the benefits of treatment (can calculate NNT vs. NNH)
Tolerability – what was the drop-out rate in the study compared to withdrawal rates on the current standard treatment?
Is the benefit of the treatment large enough to outweigh these risks?

33. Other Considerations
Cost implications – financial information is not normally included in a trial. Economic evaluations may be available
Simplicity of use – patient factors such as compliance, method of administration or complicated devices may limit the usefulness of a treatment in clinical practice
Quality of life data – gives more information from the patient’s perspective
Sponsorship – sponsorship of the research or author affiliations to drug to drug companies may affect how the results are presented

34. Look out for……..
A lot of work and funding goes into drug development and clinical trials and drug companies and researchers will want a positive result from their hard work
When apprasing RCTs beware of the negative aspects of the study being glossed over to make it appear positive. This can include:
Use of sub-group analysis
Use of composite end points
Analysis of secondary outcomes

35. Sub-group analysis
Sub-group analysis is when results are broken down into patient sub-groups e.g. elderly, patients with a history of stroke/diabetes
If the result of the overall trial is negative it may be positive in a specific sub-group
Trials may not be powered to detect differences in sub-groups containing small numbers of patients

36. Use of Composite Endpoints
Sometimes the desired outcome of a clinical trial is relatively rare e.g. fatal MI
To show a difference between intervention and control huge numbers of participants in very long term trials would be required
Composite end-points may be used instead e.g. risk of MI, stroke, death or hospital admission due to cardiac causes
Not all the individual components are always of equal importance to all patients

37. Analysis of Secondary Outcomes
The primary outcome is the most important outcome of an RCT
If no statistically significant increase in efficacy is observed with the new treatment then secondary outcomes which are significant may be quoted in the results
The number of patient enrolled in a trial is based on the primary outcome
It is poor practice to disregard the primary outcome and quote a secondary outcome as the main result

38. Remember!
Healthcare decisions are not usually made on the basis of one trial. Other factors and other evidence may also have to be considered when making a decision

39. Appraising other publications
In addition to RCTs other publications may be used to contribute to evidence-based decision making
In order of importance the usual hierarchy is:
Systematic reviews
RCTs
Observational studies e.g. cohort, case-control or cross-sectional studies
Case reports, case studies
Expert consensus

40. Systematic Reviews
Systematic reviews seek to bring the same level of rigour to reviewing research evidence as should be used in producing research evidence. They:
Identify relevant published and non-published evidence
Select studies for inclusion and assess the quality of each
Present a summary of the findings with due consideration

41. Systematic Reviews (2)
Meta-analysis is a statistical technique for combining the results of independent studies and is the technique normally used to combine the results of selected studies for systematic review.
Validity of meta-analysis depends on the quality of the systematic review on which it is based.
Like RCTs systematic reviews should not be considered to automatically be of good quality and should be critically appraised.

42. Observational Studies
Includes cohort studies, case-control studies and cross-sectional studies
These studies lack the controlled design of RCTs and the evidence which comes from this type of study is therefore considered less robust
In some cases observational studies provide the only evidence available (e.g. emerging safety issues) and therefore it is also important that we are able to critically appraise these

43. Over to you……
Now use what you have learned from this presentation and the tools available online to critically appraise a randomised controlled trial and a cohort study