Critical Appraisal Skills Programme

Report
Evidence Based Medicine
&
Basic Critical Appraisal
David Erskine
London & SE
Medicines Information Service
Why do we need evidence?



Resources should be allocated to things
that are EFFECTIVE
The only way of judging effectiveness is
EVIDENCE
“In God we trust – all others bring data”
Why do we need evidence?

Move towards:
EVIDENCE-BASED MEDICINE

Move away from:
EMINENCE- BASED MEDICINE
What we really, really want is
EVIDENCE-INFORMED MEDICINE
Evidence-based medicine
5 steps



Converting information needs into
answerable questions
Finding the best evidence with which to
answer question
Critically appraising evidence for validity
and usefulness

Applying the results in clinical practice

Evaluating performance
What is an answerable question?
- step 1

Should contain the following components:



The intervention you are interested in
The population you are interested in
The outcomes you are interested in
Finding evidence - step 2
Workshop



What are ‘good’ sources of evidence?
Think about sources of evidence that
you have used – were they useful?
What makes a ‘good’ source of
evidence?
Finding evidence - step 2

Can search many of these sources
simultaneously using:



TRIP (via NLH)
OSRS (via NeLM)
NKS single search engine(via NLH)?????
Search Strategy
Tertiary
Secondary
Primary
Need to be systematic vs. time & resources
Start from scratch vs. build on previous work
Appraising evidence - step 3


Validity - closeness to the truth, i.e. do
we believe it?
Usefulness - clinical applicability, i.e. is
it important?
Using efficacy data from clinical trials to estimate
Clinical Effectiveness
Assessing validity

Results of a trial affected by:
Chance 
Bias 
Effect of intervention

Judge validity by:

Extent to which bias is eliminated
(Randomisation, type of analysis, blinding)
Must also account for chance
Assessed by using questions 1-7 on
checklist
Chance, bias, confounding
variables
.
S TU D Y
C O F F E E D R IN K IN G
L U N G CAN C E R
S M O K IN G
C O N F O U N D IN G VAR IAB L E
Cohort study
Exposed
Population
Sample
Outcome
Time
Not exposed
Outcome
Case control study
Study
Exposed
Cases
Not exposed
Population
Exposed
Controls
Not exposed
Time
Randomised, controlled trial
Randomisation
Experimental
intervention
Population
Outcome
Sample
Control
intervention
Time
Outcome
Are the results of the trial
valid?

Did the trial address a clearly focused
issue?




Define the population studied
The intervention given
The outcomes considered
Is an RCT an appropriate method to
answer this question?
How were patients assigned
to treatment groups?

What is randomisation?

Why is it important?

What are acceptable methods of randomisation?

What methods of randomisation are considered dubious?

Where to find out details of the randomisation process used?
Note CONSORT statement- recommend that RCTs should report how the allocation
sequence was generated and concealed until the patient was randomised
How were patients assigned
to treatment groups?

Could differences between groups have
altered the outcome?

Are any differences reported?

Where do you check for yourself?

Was any method used to balance
randomisation (stratification)?
Were patients, health workers
and study personnel “blind” to
treatment?



Why is this important?
When is it less important?
How is it done?
Want to minimise likelihood of
observer bias and Hawthorne effects
Were all the patients who
entered the trial properly
accounted for at its conclusion?


Was follow-up complete?- if not how was
missing data handled?
Were patients analysed in the groups to
which they were randomised?
Intention to treat analysis vs.
Per protocol or completer analysis
Aside from the experimental
investigation, were the two
groups treated in the same way?

Usually not such an important issue in
placebo-controlled or comparative drug
trials but assessing for possible bias
introduced by differing intensity of follow
up
Did the study have enough
participants to minimise the play
of chance?


Look for a power calculation
Do you agree with their definition of
“important”
How are the results
presented


What is being described: proportions of people, a
measurement (mean or median differences), a survival
curve?
How was it expressed?
With proportions see terms like Relative risk
reduction, absolute risk reduction, number needed to
treat

Do you understand what is being expressed?

Is it clinically significant?
Expressing results
Five years treatment with:
Intervention A
reduces cardiac events by 34%
Intervention B
causes an absolute reduction of cardiac
events of 1.4%
Intervention C
increases the rate of event free patients from
95.9% to 97.3%
Intervention D
71 patients need to be treated to avoid one
cardiac event
Intervention E
reduces cardiac events by 34% with a 6%
relative increase in mortality
(Lancet 1994; 343: 1209-1211)
Quantifying benefit
OUTCOME
Yes
No
Control intervention
a
b
Experimental intervention
c
d
Quantifying benefit
Relative risk reduction – RRR= CER – EER
CER
[a/a+b – c/c+d]
[ a/a+b]
Absolute risk reduction – ARR= CER – EER a/a+b – c/c+d
Number needed to treat – NNT
=
_1_
ARR
Relative risk – RR
=
EER
CER
Odds ratio – OR = odds of event in intervention group
odds of event in control group
c/c+d
a/a+b
c/d
a/b
RCT example - 4S study

Stable angina or myocardial infarction more than 6
months previously

Serum cholesterol > 6.2mmol/l

Excluded patients with arrhythmia's and heart failure

All patients given 8 weeks of dietary therapy

If cholesterol still raised (>5.5) randomised to receive
simvastatin (20mg > 40mg) or placebo

Outcome death or myocardial infarction (length of
treatment 5.4 years ) were the outcomes
Example – the 4S study
OUTCOME
Dead
Alive
Control group (placebo) n = 2223
256
1967
Experimental group (simvastatin) n = 2221
182
2039
Control event rate
= 256 =
2223
0.115 (11.5%)
Control odds of event
= 256 =
1967
0.130
Experimental event rate
= 182 =
2221
0.082 (8.2%)
Experimental odds of event
= 182 =
2039
0.089
Example – the 4S study
Relative risk reduction
RRR
CER – EER
CER
= 0.115 – 0.082 = 0.29 (29%)
0.115
Absolute risk reduction
ARR
CER – EER
= 0.115 – 0.082 = 0.033 (3.3%)
Number needed to treat
NNT
_1_
ARR
=
_1_
0.033
=
30.1
Relative risk
RR
EER
CER
=
0.082
0.115
=
0.71
Odds ratio =
OR
odds of event in experimental group
odds of event in control group
= 0.089 =
0.130
0.69
Workshop –revision

Assuming a treatment is beneficial and you
are trying to prevent an unpleasant endpoint.
Outline what type of values you would expect
for the following measures of efficacy:


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Relative risk reduction
Relative risk
Odds ratio
Absolute risk reduction
NNT
NNT EXAMPLES
Intervention
Outcome
NNT
Streptokinase + aspririn v.
placebo (ISIS 2)
tPA v. streptokinase
(GUSTO trial)
Simvastatin v. placebo in IHD
(4S study)
Treating hypertension in the
over-60s
Aspirin v. placebo in healthy
adults
prevent 1 death
at 5 weeks
save 1 life with
tPA usage
prevent 1
event in 5y
prevent 1 event
in 5y
prevent MI or
death in 1 year
20
100
15
18
500
How precise are the
results?


Limitations of the p-value- what does it
tell you?
Use of confidence intervals
•
•
•
What are confidence intervals?
What does upper and lower limits tell you?
Would your decision about whether to use
this treatment be the same at the upper and
lower confidence intervals?
How precise are the results?


CHANCE - p = 1 in 20 (0.05).
 > 1 in 20 (0.051) = not significant
 < 1 in 20 (0.049) = statistically significant
CONFIDENCE INTERVALS
 the range of values between which we could be
95% confidant that this result would lie if this trial
was carried out 100 times (taken as result for
general population)
Confidence Intervalhow to calculate in some
circumstances
The range of values which includes the true
population value 95% of the time
e.g. Confidence interval around ARR =
+/- 1.96
CER x (1 - CER)
N Control group
+
__EER x (1 - EER)__
N Experimental group
Can the results be applied to
the local population?

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Look at inclusion and exclusion criteriaare they similar
Are there differences which make this trial
irrelevant?
Be pragmatic!!
Were all the clinically important
outcomes considered?


Consider outcomes reported from a range of
perspectives- individual, family/ carers, policy
maker, healthcare professional, wider
community
Reports tend to concentrate on efficacy at the
expense of harms and quality of life measures
(participants and carers?)
Should policy or practice change
as a result of the evidence
contained in this trial?

Are the likely benefits worth the potential harms
and costs?

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Have you got all the data you need to make this
assessment
Can you access any missing data you need
How does this intervention compare with other
interventions-and the results of related RCTs (if any)
Also need to consider service implications
Applying results to local practice
- step 4

Local policies

Guideline development

Implementing clinical effectiveness and
clinical governance agendas
Evaluating performance step 5

Clinical audit!
Evidence based medicine
Formulate question
Efficiently track
Down best
Available
Evidence
Critically review the
Validity and usefulness
Of the evidence
Evaluate
Performance
Implement
Changes
In clinical
Practice
Hierarchy of evidence
)
(used in NICE Guidelines)
Ia
Evidence from systematic review of meta-analysis of
randomised controlled trials
Ib
Evidence from at least one randomised controlled trial
IIa
Evidence from at least one well-designed controlled study
without randomisation
IIb
Evidence from at least one other type of well-designed quasiexperimental study
III
Evidence from well-designed non-experimental descriptive
studies such as comparative studies, or case studies
IV
Evidence from expert committee reports or opinions and/or
clinical experiences of respected authorities
Strength of recommendations
used in NICE Guidelines
Grade A
At least one randomised controlled trial as part of a body of
literature of overall good quality and consistency
addressing the specific recommendation (evidence levels
1a and 1b)
Grade B
Well conducted clinical studies but no randomised clinical
trials on the topic of the recommendation (evidence levels
Iia, IIb, III)
Grade C
Expert committee reports or opinions and/or clinical
experience of respected authorities. This grading indicates
that directly applicable clinical studies are absent (evidence
level IV)
Good practice point: recommended good practice based on
the clinical experience of the Guideline Development Group
Recommendations from the
BHS Guideline 1999

Drug therapy should be started in all patients with
sustained systolic BP >/= 160mmHg or sustained
diastolic BP >/= 100mmHg despite nonpharmacological measures (A)

To reduce overall cardiovascular risk patients should
stop smoking (B)

At least two BP measurements should be made at
each visit and 4 visits to determine blood pressure
(C)
Criticisms of evidence-based
medicine

Effective therapies might be rejected on the basis
of “absence of evidence” of efficacy rather than
“evidence of absence” of efficacy.

“Cook book” medicine

Can take a long time to gather the evidence

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When is it appropriate to generalise across
populations?
Use of surrogate markers, class effects
Additional criteria in assessing
trials claiming therapeutic
equivalence

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Was the active control previously shown to be
effective?
Were study patients and outcome variables similar to
those in the original trials that established the
efficacy of the active control?
Were both regimens applied in optimal fashion?
Was the appropriate null hypothesis tested?
Was the equivalence margin specified before the
study?
Was the trial large enough?
Was analysis by intention to treat AND on-treatment?
PLUS usual assessment of size and precision of
treatment effect!
REFERENCES

CASP Tool
www.phru.nhs.uk/casp/resourcescasp.htm

Additional Reading

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Montori V et al Users’ guide to detecting misleading claims in clinical
research reports BMJ 2004; 329: 1093-1096
Greenhalgh T. How to read a paper: Getting your bearings (deciding
what a paper is about). BMJ 1997; 315: 243-246
Greenhalgh T. How to read a paper: Assessing the methodological
quality of published papers. BMJ 1997; 315: 305-308
Guyatt GH, et al. Users’ Guides to the Medical Literature: II. How to
use an article about therapy or prevention. A. Are the results of the
study valid? JAMA 1993; 270: 2598-2601
Guyatt GH, et al. Users’ Guides to the Medical Literature: II. How to
use an article about therapy or prevention. B. What are the results and
will they help me in caring for my patients? JAMA 1994; 271: 59-63
REFERENCES cont.
Statistics for the non-statistician
I: Different types of data need different statistical tests
Greenhalgh T BMJ 1997; 315: 364-6
II: “Significant” relations and their pitfalls
Greenhalgh T BMJ 1997; 315: 422-5
Statistics in small doses- a series of articles available
on UKMI web-site
(http://www.ukmi.nhs.uk/activities/Research/default.asp?pageRef=27)

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