Transcript Slide 1
RATING QUALITY OF EVIDENCE AND
STRENGTH OF RECOMMENDATIONS IN
HEPATOLOGY
USING THE GRADE FRAMEWORK
AASLD Practice Guidelines Committee Meeting, Chicago
1 May 2009
Yngve Falck-Ytter, M.D.
Case Western Reserve University
Disclosure
In the past 5 years, Dr. Falck-Ytter received no personal
payments for services from industry. His research group
received research grants from Three Rivers, Valeant and Roche
that were deposited into non-profit research accounts. He is a
member of the GRADE working group which has received
funding from various governmental entities in the US and
Europe. Some of the GRADE work he has done is supported in
part by grant # 1 R13 HS016880-01 from the Agency for
Healthcare Research and Quality (AHRQ).
Content
Part 1
Background and rationale for revisiting
guideline methodology
GRADE approach
Quality of evidence
Strength of recommendations
Content (continued)
Part 2 – practical consideration
Ideal vs. practical ad hoc approaches
Funding guideline work
Creating GRADE evidence profiles with
GRADEpro
GRADE and diagnostic tests
Reassessment of clinical
practice guidelines
Editorial by Shaneyfelt and Centor (JAMA 2009)
“Too many current guidelines have become
marketing and opinion-based pieces…”
“AHA CPG: 48% of recommendations are based on
level C = expert opinion…”
“…clinicians do not use CPG […] greater concern […]
some CPG are turned into performance measures…”
“Time has come for CPG development to again be
centralized, e.g., AHQR…”
Evidence based clinical
decisions
Clinical state and
circumstances
Patient values and
preferences
Expertise
Research evidence
Equal for all
Haynes et al. 2002
Confidence in evidence
There always is evidence
“When there is a question there is evidence”
Evidence alone is never sufficient to make a
clinical decision
Better research greater confidence in the
evidence and decisions
Hierarchy of evidence
Randomized Controlled
Trials
Cohort Studies and Case
Control Studies
Case Reports and Case
Series, Non-systematic
observations
Expert Opinion
BIAS
Expert Opinion
Expert Opinion
STUDY DESIGN
Reasons for grading evidence?
People draw conclusions about the
quality of evidence and strength of recommendations
Systematic and explicit approaches can help to
protect against errors, resolve disagreements
communicate information and fulfill needs
be transparent about the process
Change practitioner behavior
However, wide variation in approaches
GRADE working group. BMJ. 2004 & 2008
10
Which grading system?
P: In patients with acute hepatitis C …
I : Should anti-viral treatment be used …
C: Compared to no treatment …
O: To achieve viral clearance?
Evidence Recommendation
Organization
B
Class I
AASLD (2009)
II-1
-/-
VA (2006)
1+
A
SIGN (2006)
-/-
“Most authorities…” AGA (2006)
Scenario (2)
Should patients with risk factors for viral
hepatitis be screened with a hepatitis C
antibody (ELISA) test to identify patients with
past hepatitis C exposure?
Level of evidence in GI CPGs
AASLD
A
B
C
Multiple RCTs or
meta-analysis
Single randomized
trial, or nonrandomized studies
Only consensus
opinion of experts,
case studies, or
standard-of-care
AGA
ACG
Good
Consistent,
well-designed, well
conducted studies
[…]
1. Multiple published,
well-controlled (?)
randomized trials or a
well designed
systemic (?) metaanalysis
Fair
Limited by
the number, quality
or consistency of
individual studies
[…]
2. One qualitypublished (?) RCT,
published welldesigned cohort/
case-control studies
Poor
… important
flaws, gaps in chain
of evidence…
3. Consensus of
authoritative (?)
expert opinions based
on clinical evidence or
from well designed,
but uncontrolled or
non-rand. clin. trials
ASGE
A. RCTs
B. RCT with
important
limitations
C. Observational
studies
D. Expert
opinion
13
What to do?
14
Limitations of existing systems
Confuse quality of evidence with strength of
recommendations
Lack well-articulated conceptual framework
Criteria not comprehensive or transparent
GRADE unique
breadth, intensity of development process
wide endorsement and use
conceptual framework
comprehensive, transparent criteria
Focus on all important outcomes related to a
specific question and overall quality
Grades of Recommendation
Assessment, Development and
Evaluation
GRADE Working Group
David Atkins, chief medical officera
Dana Best, assistant professorb
Martin Eccles, professord
Francoise Cluzeau, lecturerx
Yngve Falck-Ytter, associate directore
Signe Flottorp, researcherf
Gordon H Guyatt, professorg
Robin T Harbour, quality and information director h
Margaret C Haugh, methodologisti
David Henry, professorj
Suzanne Hill, senior lecturerj
Roman Jaeschke, clinical professork
Regina Kunx, Associate Professor
Gillian Leng, guidelines programme directorl
Alessandro Liberati, professorm
Nicola Magrini, directorn
James Mason, professord
Philippa Middleton, honorary research fellowo
Jacek Mrukowicz, executive directorp
Dianne O’Connell, senior epidemiologistq
Andrew D Oxman, directorf
Bob Phillips, associate fellowr
Holger J Schünemann, professorg,s
Tessa Tan-Torres Edejer, medical officert
David Tovey, Editory
Jane Thomas, Lecturer, UK
Helena Varonen, associate editoru
Gunn E Vist, researcherf
John W Williams Jr, professorv
Stephanie Zaza, project directorw
a) Agency for Healthcare Research and Quality, USA
b) Children's National Medical Center, USA
c) Centers for Disease Control and Prevention, USA
d) University of Newcastle upon Tyne, UK
e) German Cochrane Centre, Germany
f) Norwegian Centre for Health Services, Norway
g) McMaster University, Canada
h) Scottish Intercollegiate Guidelines Network, UK
i) Fédération Nationale des Centres de Lutte Contre le Cancer, France
j) University of Newcastle, Australia
k) McMaster University, Canada
l) National Institute for Clinical Excellence, UK
m) Università di Modena e Reggio Emilia, Italy
n) Centro per la Valutazione della Efficacia della Assistenza Sanitaria, Italy
o) Australasian Cochrane Centre, Australia
p) Polish Institute for Evidence Based Medicine, Poland
q) The Cancer Council, Australia
r) Centre for Evidence-based Medicine, UK
s) National Cancer Institute, Italy
t) World Health Organisation, Switzerland
u) Finnish Medical Society Duodecim, Finland
v) Duke University Medical Center, USA
w) Centers for Disease Control and Prevention, USA
x) University of London, UK
Y) BMJ Clinical Evidence, UK
GRADE uptake
Where GRADE fits in
Prioritize problems, establish panel
Systematic review
Searches, selection of studies, data collection and analysis
Prepare evidence profile:
Quality of evidence for each outcome and summary of findings
Assess overall quality of evidence
Decide direction and strength of recommendation
Draft guideline
Consult with stakeholders and / or external peer reviewer
Disseminate guideline
Implement the guideline and evaluate
GRADE
Assess the relative importance of outcomes
GRADE: Quality of evidence
The extent to which our confidence in an
estimate of the treatment effect is adequate to
support particular recommendation.
Although the degree of confidence is a
continuum, we suggest using four categories:
High
Moderate
Low
Very low
20
Quality of evidence across
studies
Outcome #1
Outcome #2
Outcome #3
Quality: High
Quality: Moderate
Quality: Low
III
V
II
IB
Determinants of quality
RCTs start high
Observational studies start low
What lowers quality of evidence? 5 factors:
Detailed design and execution
Inconsistency of results
Indirectness of evidence
Imprecision
Publication bias
What is the study design?
23
Types of studies
Did investigator assign exposure?
Yes
No
Experimental study
Observational study
Random allocation?
Comparison group?
Yes
RCT
No
CCT
Yes
Analytical study
No
Case-series
Direction?
Cohort study
Case-control study
Exposure
and outcome
at the same time
Cross-sectional study
Before and
after study
Variations:
cBAS
ITS
24
1. Design and execution
Study limitations (risk of bias)
For RCTs:
Lack of allocation concealment
No true intention to treat principle
Inadequate blinding
Loss to follow-up
Early stopping for benefit
For observational studies:
Selection
Comparability
Exposure/outcome
Tools: scales and checklists
Example: Jadad score
Was the study described as randomized?
Adequate description of randomization?
Double blind?
1
1
1
Method of double blinding described?
Description of withdrawals and dropouts?
1
1
Max 5 points for quality
Jadad AR et al. Control Clin Trials 1996
26
Allocation concealment
250 RCTs out of 33 meta-analyses
Allocation concealment:
adequate
unclear
not adequate
Effect
(Ratio of OR)
1.00 (Ref.)
0.67 [0.60 – 0.75]
0.59 [0.48 – 0.73]
*
* significant
Schulz KF et al. JAMA 1995
27
5 vs 4 chemo-Rx cycles for AML
Studies stopped early because of
benefit
Cochrane Risk of bias graph in
RevMan 5
30
2. Consistency of results
Look for explanation for inconsistency
patients, intervention, comparator, outcome, methods
Judgment
variation in size of effect
overlap in confidence intervals
statistical significance of heterogeneity
I2
Heterogeneity
Pagliaro L et al. Ann Intern Med 1992;117:59-70
32
3. Directness of Evidence
Indirect comparisons
Interested in head-to-head comparison
Drug A versus drug B
Tenofovir versus entecavir in hepatitis B treatment
Differences in
patients (early cirrhosis vs end-stage cirrhosis)
interventions (CRC screening: flex. sig. vs colonoscopy)
comparator (e.g., differences in dose)
outcomes (non-steroidal safety: ulcer on endoscopy vs
symptomatic ulcer complications)
4. Imprecision
Small sample size
small number of events
wide confidence intervals
uncertainty about magnitude of effect
Imprecision
appreciable
benefit
RR
appreciable
harm
precise
imprecise
0.75
1.00
1.25
600
400
RRR=25%
300 events
200
RRR=30%
0
Total number of events required
RRR=20%
0.0
0.2
0.4
0.6
0.8
1.0
Control group event rate
36
5. Reporting Bias
(Publication Bias)
Reporting of studies
publication bias
number of small studies
Reporting of outcomes
Publication bias
ISIS-4
Lancet 1995
I.V. Mg in
acute
myocardial
infarction
Meta-analysis
Yusuf S.Circulation 1993
Egger M, Smith DS. BMJ 1995;310:752-54
38
Funnel plot
Standard Error
0
Symmetrical:
No reporting bias
1
2
3
0.1
0.3
0.6 1
3
10
Odds ratio
Egger M, Cochrane Colloquium Lyon 2001
39
Funnel plot
Standard Error
0
Asymmetrical:
Reporting bias?
1
2
3
0.1
0.3
0.6 1
3
10
Odds ratio
Egger M, Cochrane Colloquium Lyon 2001
40
I.V. Mg in
acute
myocardial
infarction
ISIS-4
Lancet 1995
Meta-analysis
Yusuf S.Circulation 1993
Reporting bias
Egger M, Smith DS. BMJ 1995;310:752-54
41
Quality assessment criteria
Quality of
evidence
Study
design
Lower if…
High (4)
Randomized
trial
Study limitations
(design and execution)
Moderate (3)
Low (2)
Very low (1)
Inconsistency
Observational
study
Indirectness
Imprecision
Higher if…
What can
raise the
quality of
evidence?
Publication bias
42
BMJ 2003;327:1459–61
43
Quality assessment criteria
Quality of
evidence
Study
design
Lower if…
Higher if…
High (4)
Randomized
trial
Study limitations
Large effect (e.g., RR 0.5)
Very large effect (e.g., RR 0.2)
Inconsistency
Evidence of dose-response
gradient
Indirectness
All plausible confounding
would reduce a
demonstrated effect
Moderate (3)
Low (2)
Very low (1)
Observational
study
Imprecision
Publication bias
44
Categories of quality
High
Further research is very unlikely to change our
confidence in the estimate of effect
Moderate
Further research is likely to have an important impact on
our confidence in the estimate of effect and may change
the estimate
Low
Further research is very likely to have an important
impact on our confidence in the estimate of effect and is
likely to change the estimate
Very low
Any estimate of effect is very uncertain
45
Judgments about the
overall quality of evidence
Most systems not explicit
Options:
Benefits
Primary outcome
Highest
Lowest
Beyond the scope of a systematic review
GRADE: Based on lowest of all the critical
outcomes
46
GRADE evidence profile
Going from evidence to
recommendations
Deliberate separation of quality of evidence
from strength of recommendation
No automatic one-to-one connection as in
other grading systems
Example: What if there is high quality
evidence, but the balance between benefit
and risks are finely balanced?
48
Strength of recommendation
“The strength of a recommendation reflects the
extent to which we can, across the range of patients
for whom the recommendations are intended, be
confident that desirable effects of a management
strategy outweigh undesirable effects.”
Although the strength of recommendation is a
continuum, we suggest using two categories :
“Strong” and “Weak”
Desirable and undesirable effects
Desirable effects
Mortality reduction
Improvement in quality of life, fewer
hospitalizations/infections
Reduction in the burden of treatment
Reduced resource expenditure
Undesirable effects
Deleterious impact on morbidity, mortality or quality of
life, increased resource expenditure
4 determinants of the strength
of recommendation
Factors that can weaken the
strength of a recommendation
Explanation
Lower quality evidence
The higher the quality of evidence, the more
likely is a strong recommendation.
Uncertainty about the
balance of benefits versus
harms and burdens
The larger the difference between the desirable
and undesirable consequences, the more likely
a strong recommendation warranted. The
smaller the net benefit and the lower certainty
for that benefit, the more likely is a weak
recommendation warranted.
Uncertainty or differences
in values
The greater the variability in values and
preferences, or uncertainty in values and
preferences, the more likely weak
recommendation warranted.
Uncertainty about whether
the net benefits are worth
the costs
The higher the costs of an intervention – that is,
the more resources consumed – the less likely
is a strong recommendation warranted.
Developing recommendations
Implications of a
strong recommendation
Patients: Most people in this situation would want
the recommended course of action and only a small
proportion would not
Clinicians: Most patients should receive the
recommended course of action
Policy makers: The recommendation can be
adapted as a policy in most situations
Implications of a
weak recommendation
Patients: The majority of people in this situation
would want the recommended course of action,
but many would not
Clinicians: Be prepared to help patients to make a
decision that is consistent with their own
values/decision aids and shared decision making
Policy makers: There is a need for substantial
debate and involvement of stakeholders
6 main misconceptions
1.
2.
3.
4.
5.
6.
Isn’t GRADE expensive to realize?
Isn’t GRADE more complicated, takes longer and
requires more resources?
Isn’t GRADE eliminating the expert?
But what about prevalence/burden of disease,
diagnosis, cost?
But GRADE does not have an “insufficient evidence to
make recommendation” category! (or: the “optional”
category), no?
But we only “recommend” – we can’t possibly give
weak recommendations!
Critical
Outcome
Critical
Outcome
Important
Outcome
Not
High
Moderate
Low
Very low
Summary of findings
& estimate of effect
for each outcome
Systematic review
Grade down
P
I
C
O
Outcome
1.
2.
3.
4.
5.
Grade up
RCT start high,
obs. data start low
Risk of bias
Inconsistency
Indirectness
Imprecision
Publication
bias
1. Large effect
2. Dose
response
3. Confounders
Guideline development
Formulate recommendations:
• For or against (direction)
• Strong or weak (strength)
By considering:
Quality of evidence
Balance benefits/harms
Values and preferences
Revise if necessary by considering:
Resource use (cost)
Rate
overall quality of evidence
across outcomes based on
lowest quality
of critical outcomes
•
•
•
•
“We recommend using…”
“We suggest using…”
“We recommend against using…”
“We suggest against using…”
Conclusions
1. GRADE is gaining acceptance as international
2.
3.
4.
5.
standard
GRADE has criteria for evidence assessment across
questions (e.g., public health interventions) and
outcomes
Criteria for moving from evidence to
recommendations
Simple, transparent, systematic
Balance between simplicity and methodological rigor