Title: Critical Appraisal Level 2
1Critical Appraisal Level 2
- Evaluating studies using the Critical Appraisal
Skills Programme (CASP) Tools
2What 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
3Why 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
4Advantages 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!
5Disadvantages 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
6Help 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
7CASP 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
8CASP Tools (2)
- The tools break critical appraisal of each study
type into 10-12 manageable questions - The questions in each tool will vary slighty as
study designs are different - They are available at
- http//www.sph.nhs.uk/what-we-do/public-health-wor
kforce/resources/critical-appraisals-skills-progra
mme
9Randomised 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)
10RCTs (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
11Appraising 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
12Screening 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
13Validity
- 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
14Randomisation 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 5050
chance of being in either group) - Stratification can be used to ensure similar
baseline characteristics in both groups
15Randomisation 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?
16Blinding (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?)
17Follow-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
18Interventions (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?
19Interventions (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?
20Sample 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)
21Results
- 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
22Presentation 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
23Presentation 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
24Precision 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
25Confidence 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
26P-values
- P-values describe the probability that a result
has happened by chance - Plt0.05 is usually described as statistically
significant and means that the results are
unlikely to be due to chance
27Statistics 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
28Clinical 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)
29Relevance
- 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
30Relevance 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?
31Importance 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
32Risks 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?
33Other 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 patients perspective - Sponsorship sponsorship of the research or
author affiliations to drug to drug companies may
affect how the results are presented
34Look 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
35Sub-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
36Use 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
37Analysis 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
38Remember!
- 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
39Appraising 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
40Systematic 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
41Systematic 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.
42Observational 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
43Over 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