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GRADE INTRODUCTION
Holger Schünemann, MD, PhDProfessorMcMaster University, Hamilton, Canada
Madrid, SpainNovember 26, 2008
1
Content
Background and rationale for revisiting guideline methodology
GRADE approach Quality of evidence Strength of recommendations
Content
Background and rationale for revisiting guideline methodology
GRADE approach Quality of evidence Strength of recommendations
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
STUDY DESIGN Randomized Controlled
Trials Cohort Studies and
Case Control Studies Case Reports and Case
Series, Non-systematic observations
BIAS
Expert Opinion
Exp
ert O
pin
ion
Expert Opinion
Can you explain the following? Concealment of randomization Blinding (who is blinded in a double
blinded trial?) Intention to treat analysis and its correct
application Why trials stopped early for benefit
overestimate treatment effects? P-values and confidence intervals
Hierarchy of evidence
STUDY DESIGN Randomized Controlled
Trials Cohort Studies and
Case Control Studies Case Reports and Case
Series, Non-systematic observations
BIAS Exp
ert O
pin
ion
Reasons for grading evidence? People draw conclusions about the
quality of evidence and strength of recommendations
Systematic and explicit approaches can help protect against errors, resolve disagreements communicate information and fulfil needs
Change practitioner behavior However, wide variation in approaches
GRADE working group. BMJ. 2004 & 2008
Which grading system?
Evidence Recommendation B Class I A 1 IV C
Organization AHA ACCP SIGN
Recommendation for use of oral anticoagulation in patients with atrial fibrillation and rheumatic mitral valve disease
10
A COPD guidelines
11
Another COPD guidelines
12
And another COPD guideline
13
What to do?
14
Content
Background and rationale for revisiting guideline methodology
GRADE approach Quality of evidence Strength of recommendations
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
GRADE WORKING GROUP
Grades of Recommendation Assessment,
Development and Evaluation
CMAJ 2003, BMJ 2004, BMC 2004, BMC 2005, AJRCCM 2006, Chest 2006, BMJ 2008
GRADE Working GroupDavid 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 ProfessorGillian 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, UKHelena 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, USAc) Centers for Disease Control and Prevention, USAd) University of Newcastle upon Tyne, UKe) German Cochrane Centre, Germanyf) Norwegian Centre for Health Services, Norwayg) McMaster University, Canadah) Scottish Intercollegiate Guidelines Network, UKi) Fédération Nationale des Centres de Lutte Contre le Cancer, Francej) University of Newcastle, Australiak) McMaster University, Canadal) National Institute for Clinical Excellence, UKm) Università di Modena e Reggio Emilia, Italyn) Centro per la Valutazione della Efficacia della Assistenza Sanitaria, Italyo) Australasian Cochrane Centre, Australia p) Polish Institute for Evidence Based Medicine, Polandq) The Cancer Council, Australiar) Centre for Evidence-based Medicine, UKs) National Cancer Institute, Italyt) World Health Organisation, Switzerland u) Finnish Medical Society Duodecim, Finland v) Duke University Medical Center, USA w) Centers for Disease Control and Prevention, USAx) University of London, UKY) BMJ Clinical Evidence, UK
GRADE Uptake
World Health Organization Allergic Rhinitis in Asthma Guidelines (ARIA) American Thoracic Society British Medical Journal Infectious Disease Society of America American College of Chest Physicians UpToDate American College of Physicians Cochrane Collaboration National Institute Clinical Excellence (NICE) Infectious Disease Society of America European Society of Thoracic Surgeons Clinical Evidence Agency for Health Care Research and Quality (AHRQ) Over 20 major organizations
The GRADE approach
Clear separation of 2 issues:1) 4 categories of quality of evidence: very
low, low, moderate, or high quality? methodological quality of evidence likelihood of systematic deviation from
truth by outcome
2) Recommendation: 2 grades - weak or strong (for or against)? Quality of evidence only one factor
*www.GradeWorking-Group.org
GRADE Quality of Evidence
“Extent to which confidence in estimate of effect adequate to support decision”
high: considerable confidence in estimate of effect.
moderate: further research likely to have impact on confidence in estimate, may change estimate.
low: further research is very likely to impact on confidence, likely to change the estimate.
very low: any estimate of effect is very uncertain
Determinants of quality
RCTs start high
observational studies start low
5 factors lower the quality of evidence limitations in detailed design and execution inconsistency indirectness reporting bias imprecision
3 factors can increase the quality of evidence
Quality assessment criteria Quality of evidence
Study design Lower if Higher if
High Randomised trial Study quality: Serious limitations Very serious limitations I mportant inconsistency Directness: Some uncertainty Major uncertainty Sparse or imprecise data High probability of reporting bias
Strong association: Strong, no plausible confounders Very strong, no major threats to validity Evidence of a Dose response gradient All plausible confounders would have reduced the eff ect
Moderate
Low Observational study
Very low
Example: Design and Execution
limitations inappropriate randomization lack of concealment intention to treat principle violated inadequate blinding loss to follow-up early stopping for benefit
Design and Execution From Cates , CDSR 2008
CDSR 2008
Design and Execution
Overall judgment required
What can raise quality?3 Factors large magnitude can upgrade one level
very large two levels common criteria
everyone used to do badly almost everyone does well
Epinephrin in allergic shock dose response relation
(higher INR – increased bleeding) Residual confounding likely to reduce
(increase) observed (lack of) effect
From Evidence to Recommendation
28
The clinical scenario
A 68 year old male long-term patient of yours. He suffers from COPD but is unable to stop smoking after over 30 years of tobacco use. He has been taking beta-carotene supplements for several months because someone in the “healthy food” store recommended it to prevent cancer. He wants to know whether this will prevent him from getting cancer and whether he should use beta-carotene.
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.”
Desirable and undesirable effects
Desirable effects Mortality 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
Determinants of the strength of recommendation
Factors that can strengthen a recommendation
Comment
Quality of the evidence The higher the quality of evidence, the more likely is a strong recommendation.
Balance between desirable and undesirable effects
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 weak recommendation warranted.
Values and preferences The greater the variability in values and preferences, or uncertainty in values and preferences, the more likely weak recommendation warranted.
Costs (resource allocation) 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
Exercise!
36
A COPD guidelines
37
Another COPD guidelines
38
And another COPD guideline
39
The clinical question
Population: In smokers with COPDIntervention: does beta-carotene supplComparison: compared to no suppl.Outcomes: reduce the risk of COPD
symptoms, lung cancer
and death and improve PFTs?
Two trials
1) The Alpha-Tocopherol Beta-Carotene (ATBC) trial randomly assigned 29,133 people to receive beta carotene, tocopherol, both, or placebo. Study participants averaged 57.2 years of age, 20.4 cigarettes per day, and 35.9 years of smoking. They were followed up for 5 to 8 years.
RR for lung cancer = 1.16 (95% CI 1.02-1.33)
Albanes et al, JNCI, 1996
Two trials
2) The Beta-Carotene and Retinol Efficacy Trial (CARET) evaluated high-risk current and former smokers with a 20–pack-year history of smoking (n = 14,254), ~ 60 years old. The participants were randomly assigned to receive either a combination of beta carotene and vitamin A or placebo. Mean length of follow up: 4 years.
RR for lung cancer = 1.28 (95% CI 1.04-1.57)
Determinants of the strength of recommendation
Factors that can strengthen a recommendation
Comment
Quality of the evidence The higher the quality of evidence, the more likely is a strong recommendation.
Balance between desirable and undesirable effects
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 weak recommendation warranted.
Values and preferences The greater the variability in values and preferences, or uncertainty in values and preferences, the more likely weak recommendation warranted.
Costs (resource allocation) The higher the costs of an intervention – that is, the more resources consumed – the less likely is a strong recommendation warranted
Determinants of the strength of recommendation
Factors that can strengthen a recommendation
Comment
Quality of the evidence High
Balance between desirable and undesirable effects
Clear balance towards harm
Values and preferences Little variability
Costs (resource allocation) Lowering use of supplements will reduce resource use
Determinants of the strength of recommendation
Factors that can weaken the strength of a recommendation. Example:
Decision Explanation
Lower quality evidence □ Yes□ No
Uncertainty about the balance of benefits versus harms and burdens
□ Yes□ No
Uncertainty or differences in values □ Yes□ No
Uncertainty about whether the net benefits are worth the costs
□ Yes□ No
Table. Decisions about the strength of a recommendationFrequent “yes” answers will increase the likelihood of a weak recommendation
Your recommendation
Team up in pairs of two or three or four and formulate your recommendation for the guideline on COPD
I will collect your answers
Your recommendation
Our recommendation
In patients with COPD who continue to smoke, we recommend stopping beta-carotene supplementation.
OR:In patients with COPD who continue to
smoke, clinicians should stop beta-carotene supplementation.
Health Care Question
(PICO)Systematic reviews
Studies
Outcomes
Important outcomes
Rate the quality of evidence for each outcome, across studies RCTs start high, observational studies start low(-)Study limitationsImprecisionInconsistency of resultsIndirectness of evidencePublication bias likely
Final rating of quality for each outcome: high, moderate, low, or very low
(+)Large magnitude of effectDose responsePlausible confounders would ↓ effect when an effect is present or ↑ effect if effect is absent
Decide on the direction (for/against) and grade strength of the recommendation (strong/weak*) considering:
Quality of the evidenceBalance benefits/harmsValues and preferences
Decide if any revision of direction or strength is necessary considering:
Resource use
Rate overall quality of evidence (GRADE)(lowest quality among critical outcomes)
S1 S2 S3 S4
OC1 OC2 OC3 OC4
OC1 OC3 Critical outcomes
OC4
Reevaluate estimate of effect for each outcome
OC2
S5
*also labeled “conditional”
Guideline development processPrioritise Problems, establish panel
Systematic Review
Evidence Profile
Relative importance of outcomes
Overall quality of evidence
Benefit – downside evaluation
Strength of recommendation
Implementation and evaluation of guidelines
GRADE
Prioritise Problems, establish panel
Systematic Review
Evidence Profile
Relative importance of outcomes
Overall quality of evidence
Benefit – downside evaluation
Strength of recommendation
Implementation and evaluation of guidelines
GRADE
Summary of Findings
Guideline development process
GRADE Profiles
Summary of Findings Tables
Conclusions
GRADE is gaining acceptance as international standard
Criteria for evidence assessment across questions and outcomes
Criteria for moving from evidence to recommendations
Simple, transparent, systematic four categories of quality of evidence two grades for strength of recommendations
Transparency in decision making and judgments is key
55
Assessing the quality of evidence
56
1. Design and Execution
limitations lack of concealment intention to treat principle violated inadequate blinding loss to follow-up early stopping for benefit selective outcome reporting
Example: RCT suggests that danaparoid sodium is of benefit in treating HIT complicated by thrombosis Key outcome: clinicians’ assessment of when the
thromboembolism had resolved Not blinded – subjective judgement
2. Inconsistency of results(Heterogeneity)
if inconsistency, look for explanation patients, intervention, outcome, methods
unexplained inconsistency downgrade quality
Bleeding in thrombosis-prophylaxed hospitalized patients seven RCTs 4 lower, 3 higher risk
Example: Bleeding in the hospital
Dentali et al. Ann Int Med, 2007
Judgment variation in size of effect overlap in confidence intervals statistical significance of heterogeneity I2
Akl E, Barba M, Rohilla S, Terrenato I, Sperati F, Schünemann HJ. “Anticoagulation for the long term treatment of venous thromboembolism in patients with cancer”. Cochrane Database Syst Rev. 2008 Apr 16;(2):CD006650.
Heparin or vitamin K antagonists for survival in patients with cancer
Non-steroidal drug use and risk of pancreatic cancer
Capurso G, Schünemann HJ, Terrenato I, Moretti A, Koch M, Muti P, Capurso L, Delle Fave G. Meta-analysis: the use of non-steroidal anti-inflammatory drugs and pancreatic cancer risk for different exposure categories.
Aliment Pharmacol Ther. 2007 Oct 15;26(8):1089-99.
3. Directness of Evidence
differences in populations/patients (mild versus severe COPD,
older, sicker or more co-morbidity) interventions (all inhaled steroids, new vs. old) outcomes (important vs. surrogate; long-term
health-related quality of life, short –term functional capacity, laboratory exercise, spirometry)
indirect comparisons interested in A versus B have A versus C and B versus C formoterol versus salmeterol versus tiotropium
Alendronate
Risedronate
Placebo
Directness
interested in A versus B available data A vs C, B vs C
4. Publication Bias & Imprecision Publication bias
number of small studies
Egger M, Smith DS. BMJ 1995;310:752-54 66
I.V. Mg in acute myocardial infarctionPublication bias
Meta-analysisYusuf S.Circulation 1993
ISIS-4Lancet 1995
Egger M, Cochrane Colloquium Lyon 2001 67
Funnel plotS
tand
ard
Err
or
Odds ratio0.1 0.3 1 3
3
2
1
0
100.6
Symmetrical:No publication bias
Egger M, Cochrane Colloquium Lyon 2001 68
Funnel plotS
tand
ard
Err
or
Odds ratio0.1 0.3 1 3
3
2
1
0
100.6
Asymmetrical:Publication bias?
Egger M, Smith DS. BMJ 1995;310:752-54 69
I.V. Mg in acute myocardial infarctionPublication bias
Meta-analysisYusuf S.Circulation 1993
ISIS-4Lancet 1995
Egger M, Smith DS. BMJ 1995;310:752-54 70
Meta-analysis confirmed by mega-trials
71
Publication bias (File Drawer Problem) Faster and multiple publication of
“positive” trials Fewer and slower publication of
“negative” trials
5. Imprecision
small sample size small number of events
wide confidence intervals uncertainty about magnitude of effect
how to decide if CI too wide? grade down one level? grade down two levels?
extent to which confidence in estimate of effect adequate to support decision
Example: Bleeding in the hospital
Dentali et al. Ann Int Med, 2007
Offer all effective treatments? atrial fib at risk of stroke
warfarin increases serious gi bleeding 3% per year
1,000 patients 1 less stroke 30 more bleeds for each stroke prevented
1,000 patients 100 less strokes 3 strokes prevented for each bleed
where is your threshold? how many strokes in 100 with 3% bleeding?
01.0%
01.0%
01.0%
01.0%
What can raise quality?1. large magnitude can upgrade (RRR 50%)
very large two levels (RRR 80%) common criteria
everyone used to do badly almost everyone does well
oral anticoagulation for mechanical heart valves insulin for diabetic ketoacidosis hip replacement for severe osteoarthritis
2. dose response relation
(higher INR – increased bleeding)
3. all plausible confounding may be working to reduce the demonstrated effect or increase the effect if no effect was observed
All plausible confounding
would result in an underestimate of the treatment effect Higher death rates in private for-
profit versus private not-for-profit hospitals patients in the not-for-profit hospitals
likely sicker than those in the for-profit hospitals
for-profit hospitals are likely to admit a larger proportion of well-insured patients than not-for-profit hospitals (and thus have more resources with a spill over effect)
All plausible biases would result in an overestimate of effect Hypoglycaemic drug phenformin
causes lactic acidosis The related agent metformin is under
suspicion for the same toxicity. Large observational studies have
failed to demonstrate an association Clinicians would be more alert to lactic
acidosis in the presence of the agent
82
Hands-on exercise Work in small groups
Select someone to report back to the whole group
Watch the time Read the following instructions
1. Familiarize yourself with the review that you have been given (if you are not yet familiar with it): read the abstract
2. Identify the clinical question in the PICO (Population, Intervention, Comparison, Outcome) format. Work in your small group.
83
Hands-on exercise cont’d3. Select up to 7 important outcomes
for this comparison (consider the suggestions)
transfer them to a blank evidence profile or use GRADEpro (see worksheet 3 on page 6 of this handout or go to ). Work in your small group or in pairs.
4. Assess the quality of evidence for an outcome according to the GRADE approach
5. Move from evidence to recommendations using the evidence profile
84
85
GRADE FROM EVIDENCE TO RECOMMENDATIONS
Holger Schünemann, MD, PhDProfessor
86
Evidence based clinical decisions
Research evidence
Patient valuesand preferences
Clinical state and circumstances
Expertise
Equal for allHaynes et al. 2002
The GRADE approach
Separation of 2 issues:1) 4 categories of quality of evidence:
very low, low, moderate, or high quality? methodological quality of evidence likelihood of bias by outcome and across outcomes
2) Recommendation: 2 grades - weak or strong (for or against)? Quality of evidence only one factor
www.GradeWorkingGroup.org
Grades of recommendation:Strength of recommendations
Strong recommendations high quality methods with large precise effect benefits much greater than downsides, or
downsides much greater than benefits we recommend Grade 1
Weak/conditional recommendations lower quality methods benefits not clearly greater or smaller than
downsides values and preferences uncertain or very variable we suggest Grade 2
Case scenario
A 13 year old girl who lives in rural Indonesia presented with flu symptoms and developed severe respiratory distress over the course of the last 2 days. She required intubation. The history reveals that she shares her living quarters with her parents and her three siblings. At night the family’s chicken stock shares this room too and several chicken had died unexpectedly a few days before the girl fell sick.
Relevant clinical question?Example from a not so common disease
Clinical question:
Population: Avian Flu/influenza A (H5N1) patients
Intervention: Oseltamivir (or Zanamivir)
Comparison: No pharmacological intervention
Outcomes: Mortality, hospitalizations, resource use, adverse
outcomes, antimicrobial resistanceSchunemann et al. The Lancet ID, 2007
Methods – WHO Rapid Advice Guidelines for management of Avian Flu Applied findings of a recent systematic evaluation
of guideline development for WHO/ACHR
Group composition (including panel of 13 voting members):
clinicians who treated influenza A(H5N1) patients infectious disease experts basic scientists public health officers methodologists
Independent scientific reviewers: Identified systematic reviews, recent RCTs, case series,
animal studies related to H5N1 infection
Evidence Profile
No of studies(Ref)
Design Limitations Consistency DirectnessOther
considerationsOseltamivir Placebo
Relative(95% CI )
Absolute(95% CI )
Mortality
0 - - - - - - - - - 9
5(TJ 06)
Randomised trial
No limitations One trial only Major uncertainty
(-2)1
Imprecise or sparse data (-1)
- - OR 0.22(0.02 to 2.16)
- Very low
6
0 - - - - - - - - - - 7
5(TJ 06)
Randomised trial
No limitations One trial only Major uncertainty
(-2)1
Imprecise or
sparse data (-1)2
2/982(0.2%)
9/662(1.4%)
RR 0.149(0.03 to 0.69)
- Very low
8
53
(TJ 06)(DT 03)
Randomised trials
No limitations4 Important inconsistency
(-1)5
Major uncertainty
(-2)1
- - - HR 1.303
(1.13 to 1.50)
- Very low
5
26
(TJ 06)
Randomised trials
No limitations -7 Major uncertainty
(-2)1
None - - - WMD -0.738
(-0.99 to -0.47)
Low
4
0 - - - - - - - - - - 4
0 - - - - - - - - - - 7
09 - - - - - - - - - - 7
311
(TJ 06)
Randomised trials
No limitations -12 Some uncertainty
(-1)13
Imprecise or
sparse data (-1)14
- - OR range15
(0.56 to 1.80)
- Low
0 - - - - - - - - - - 4
I mportance
Summary of findings
Cost of drugs
Outbreak control
Resistance
Serious adverse effects (Mention of significant or serious adverse effects)
Minor adverse effects 10 (number and seriousness of adverse effects)
Viral shedding (Mean nasal titre of excreted virus at 24h)
Duration of disease (Time to alleviation of symptoms/median time to resolution of symptoms – influenza cases only)
Duration of hospitalization
LRTI (Pneumonia - influenza cases only)
Healthy adults:
Hospitalisation (Hospitalisations from influenza – influenza cases only)
Quality assessmentNo of patients Effect
Quality
Oseltamivir for treatment of H5N1 infection:
-
-
Oseltamivir for Girl with Avian FluSummary of findings: No clinical trial of oseltamivir for treatment
of H5N1 patients. 4 systematic reviews and health technology
assessments (HTA) reporting on 5 studies of oseltamivir in seasonal influenza. Hospitalization: OR 0.22 (0.02 – 2.16) Pneumonia: OR 0.15 (0.03 - 0.69)
3 published case series. Many in vitro and animal studies. No alternative that is more promising at
present. Cost: ~ Euro 40$ per treatment course
Determinants of the strength of recommendation
Factors that can strengthen a recommendation
Comment
Quality of the evidence The higher the quality of evidence, the more likely is a strong recommendation.
Balance between desirable and undesirable effects
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 weak recommendation warranted.
Values and preferences The greater the variability in values and preferences, or uncertainty in values and preferences, the more likely weak recommendation warranted.
Costs (resource allocation) The higher the costs of an intervention – that is, the more resources consumed – the less likely is a strong recommendation warranted
Example: Oseltamivir for Avian Flu
Recommendation: In patients with confirmed or strongly suspected infection with avian influenza A (H5N1) virus, clinicians should administer oseltamivir treatment as soon as possible (????? recommendation, very low quality evidence).
Schunemann et al. The Lancet ID, 2007
Example: Oseltamivir for Avian Flu
Recommendation: In patients with confirmed or strongly suspected infection with avian influenza A (H5N1) virus, clinicians should administer oseltamivir treatment as soon as possible (strong recommendation, very low quality evidence). Values and PreferencesRemarks: This recommendation places a high value on the prevention of death in an illness with a high case fatality. It places relatively low values on adverse reactions, the development of resistance and costs of treatment.
Schunemann et al. The Lancet ID, 2007
Other explanations
Remarks: Despite the lack of controlled treatment data for H5N1, this is a strong recommendation, in part, because there is a lack of known effective alternative pharmacological interventions at this time.
The panel voted on whether this recommendation should be strong or weak and there was one abstention and one dissenting vote.
ACCP: Acute coronary syndromeWould a recommendation ignoring V & P be possible?
For all patients presenting with NSTE ACS, without a clear allergy to aspirin, we recommend immediate aspirin, 75 to 325 mg po, and then daily, 75 to 162 mg po (strong recommendation, high quality evidence).
Value sensitive recommendation
Idiopathic deep venous thrombosis (DVT) is potentially life threatening condition
Patients usually receive blood thinners for one year Continuing therapy will reduce a patients absolute
risk for recurrent DVT by 7% per year for several years
The burdens include: taking a blood thinner daily keeping dietary intake of vitamin K constant blood tests to monitor the intensity of anticoagulation living with increased risk of minor and major bleeding
Value sensitive recommendations→ Patients who are very averse to a recurrent DVT would consider the benefits of avoiding DVT worth the downsides of taking warfarin. Other patients are likely to consider the benefit not worth the harms and burden.
For patients with idiopathic DVT, without elevated bleeding risk, we suggest long term warfarin therapy (weak recommendation, high quality evidence).
Values and preferences: this recommendation ascribes a low value to bleeding complications and burden from therapy and a high value to avoiding DVTs
Quality assessment criteria Quality of evidence
Study design Lower if Higher if
High Randomised trial Study quality: Serious limitations Very serious limitations I mportant inconsistency Directness: Some uncertainty Major uncertainty Sparse or imprecise data High probability of reporting bias
Strong association: Strong, no plausible confounders Very strong, no major threats to validity Evidence of a Dose response gradient All plausible confounders would have reduced the eff ect
Moderate
Low Observational study
Very low Any other evidence
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.”
Strong or weak
Quality of evidence & strength of recommendation Linked but no automatism Other factors beyond the quality of
evidence influence our confidence that adherence to a recommendation causes more benefit than harm
Systems/approaches failed to make this explicit
GRADE separates quality of evidence from strength of recommendation
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
Evaluating desirable and undesirable effects
Desirable << Undesirable Effects Desirable ?< Undesirable Effects Desirable ?> Undesirable Effects Desirable >> Undesirable Effects
Formulating a recommendation
Against For
Strong
1
Weak ? 2
Weak ? 2
Strong
1
Respiratory disease guidelines ?
Factors determining strength of recommendation
Factors that can strengthen a recommendation
Comment
Quality of the evidence The higher the quality of evidence, the more likely is a strong recommendation.
Balance between desirable and undesirable effects
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 the certainty for that benefit, the more likely is a weak recommendation.
Values and preferences The greater the variability in values and preferences, or uncertainty in values and preferences, the more likely weak recommendation warranted.
Costs (resource allocation) The higher the costs of an intervention – that is, the more resources consumed – the less likely is a strong recommendation warranted
Values & Preferences
Patients’ perspectives, beliefs, expectations, and goals for health and life.
Underlying processes used in considering the benefits, harms, costs, and inconveniences patients will experience with each management option and the resulting preferences for each option.
Guideline panels should be explicit about the relative value they place on the range of relevant patient-important outcomes. If values and preferences vary widely, a strong recommendation becomes less likely
Example: Patients vary widely in their view of how aversive they find the risk of a stroke versus the risk of a gastrointestinal bleed when deciding about oral anticoagulation for atrial fibrillation.
Relative importance of outcomes and management approaches
Desirable and undesirable effects desirable effects
Mortality improvement in quality of life, fewer
hospitalizations reduction in the burden of treatment reduced resource expenditure
undesirable consequences deleterious impact on morbidity, mortality
or quality of life, increased resource expenditure
Conclusion
clinicians, policy makers need summaries quality of evidence strength of recommendations
explicit rules transparent, informative
GRADE four categories of quality of evidence two grades for strength of recommendations transparent, systematic by and across outcomes applicable to diagnosis wide adoption
113
Questions for you
Are systematic reviews for every recommendation in your guidelines a reality/possibility?
What about cost – how do you deal with cost and how should we deal with it?
Content
Study design – bias Levels/quality of evidence - GRADE
Guidelines/Recommendations
Content
Study design – bias Levels/quality of evidence - GRADE
Guidelines/Recommendations
Confidence in evidence
There always is evidence “When there is a question there is
evidence” Better research greater confidence in
the evidence and decisions Evidence alone is never sufficient to
make a clinical decision
Evidence based clinical decisions
Research evidence
Patient valuesand preferences
Clinical state and circumstances
Expertise
Equal for allHaynes et al. 2002
About GRADE
Since 2000 Researchers/guideline developers with
interest in methodology Aim: to develop a common,
transparent and sensible system for grading the quality of evidence and the strength of recommendations
Evaluation of existing systems
GRADE Evidence Profiles
The GRADE approach
Clear separation of 2 issues:1) 4 categories of quality of evidence:
very low, low, moderate, or high quality? methodological quality of evidence likelihood of bias by outcome and across outcomes
2) Recommendation: 2 grades - weak or strong (for or against)? Quality of evidence only one factor
*www.GradeWorking-Group.org
Determinants of quality
RCTs start high
observational studies start low
what can lower quality?1. detailed design and execution2. inconsistency3. indirectness4. reporting bias5. imprecision
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The GRADE approach
Separation of 2 issues:1) 4 categories of quality of evidence:
very low, low, moderate, or high quality? methodological quality of evidence likelihood of bias by outcome and across outcomes
2) Recommendation: 2 grades - weak or strong (for or against)? Quality of evidence only one factor
www.GradeWorkingGroup.org
Grades of recommendation:Strength of recommendations
Strong recommendations high quality methods with large precise effect benefits much greater than downsides, or
downsides much greater than benefits we recommend Grade 1
Weak/conditional recommendations lower quality methods benefits not clearly greater or smaller than
downsides values and preferences uncertain or very variable we suggest Grade 2
Case scenario
A 13 year old girl who lives in rural Indonesia presented with flu symptoms and developed severe respiratory distress over the course of the last 2 days. She required intubation. The history reveals that she shares her living quarters with her parents and her three siblings. At night the family’s chicken stock shares this room too and several chicken had died unexpectedly a few days before the girl fell sick.
Relevant clinical question?Example from a not so common disease
Clinical question:
Population: Avian Flu/influenza A (H5N1) patients
Intervention: Oseltamivir (or Zanamivir)
Comparison: No pharmacological intervention
Outcomes: Mortality, hospitalizations, resource use, adverse
outcomes, antimicrobial resistanceSchunemann et al. The Lancet ID, 2007
Methods – WHO Rapid Advice Guidelines for management of Avian Flu Applied findings of a recent systematic evaluation
of guideline development for WHO/ACHR
Group composition (including panel of 13 voting members):
clinicians who treated influenza A(H5N1) patients infectious disease experts basic scientists public health officers methodologists
Independent scientific reviewers: Identified systematic reviews, recent RCTs, case series,
animal studies related to H5N1 infection
Evidence Profile
No of studies(Ref)
Design Limitations Consistency DirectnessOther
considerationsOseltamivir Placebo
Relative(95% CI )
Absolute(95% CI )
Mortality
0 - - - - - - - - - 9
5(TJ 06)
Randomised trial
No limitations One trial only Major uncertainty
(-2)1
Imprecise or sparse data (-1)
- - OR 0.22(0.02 to 2.16)
- Very low
6
0 - - - - - - - - - - 7
5(TJ 06)
Randomised trial
No limitations One trial only Major uncertainty
(-2)1
Imprecise or
sparse data (-1)2
2/982(0.2%)
9/662(1.4%)
RR 0.149(0.03 to 0.69)
- Very low
8
53
(TJ 06)(DT 03)
Randomised trials
No limitations4 Important inconsistency
(-1)5
Major uncertainty
(-2)1
- - - HR 1.303
(1.13 to 1.50)
- Very low
5
26
(TJ 06)
Randomised trials
No limitations -7 Major uncertainty
(-2)1
None - - - WMD -0.738
(-0.99 to -0.47)
Low
4
0 - - - - - - - - - - 4
0 - - - - - - - - - - 7
09 - - - - - - - - - - 7
311
(TJ 06)
Randomised trials
No limitations -12 Some uncertainty
(-1)13
Imprecise or
sparse data (-1)14
- - OR range15
(0.56 to 1.80)
- Low
0 - - - - - - - - - - 4
I mportance
Summary of findings
Cost of drugs
Outbreak control
Resistance
Serious adverse effects (Mention of significant or serious adverse effects)
Minor adverse effects 10 (number and seriousness of adverse effects)
Viral shedding (Mean nasal titre of excreted virus at 24h)
Duration of disease (Time to alleviation of symptoms/median time to resolution of symptoms – influenza cases only)
Duration of hospitalization
LRTI (Pneumonia - influenza cases only)
Healthy adults:
Hospitalisation (Hospitalisations from influenza – influenza cases only)
Quality assessmentNo of patients Effect
Quality
Oseltamivir for treatment of H5N1 infection:
-
-
Oseltamivir for Girl with Avian FluSummary of findings: No clinical trial of oseltamivir for treatment
of H5N1 patients. 4 systematic reviews and health technology
assessments (HTA) reporting on 5 studies of oseltamivir in seasonal influenza. Hospitalization: OR 0.22 (0.02 – 2.16) Pneumonia: OR 0.15 (0.03 - 0.69)
3 published case series. Many in vitro and animal studies. No alternative that is more promising at
present. Cost: ~ Euro 40$ per treatment course
Determinants of the strength of recommendation
Factors that can strengthen a recommendation
Comment
Quality of the evidence The higher the quality of evidence, the more likely is a strong recommendation.
Balance between desirable and undesirable effects
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 weak recommendation warranted.
Values and preferences The greater the variability in values and preferences, or uncertainty in values and preferences, the more likely weak recommendation warranted.
Costs (resource allocation) The higher the costs of an intervention – that is, the more resources consumed – the less likely is a strong recommendation warranted
Example: Oseltamivir for Avian Flu
Recommendation: In patients with confirmed or strongly suspected infection with avian influenza A (H5N1) virus, clinicians should administer oseltamivir treatment as soon as possible (????? recommendation, very low quality evidence).
Schunemann et al. The Lancet ID, 2007
Example: Oseltamivir for Avian Flu
Recommendation: In patients with confirmed or strongly suspected infection with avian influenza A (H5N1) virus, clinicians should administer oseltamivir treatment as soon as possible (strong recommendation, very low quality evidence). Values and PreferencesRemarks: This recommendation places a high value on the prevention of death in an illness with a high case fatality. It places relatively low values on adverse reactions, the development of resistance and costs of treatment.
Schunemann et al. The Lancet ID, 2007
Other explanations
Remarks: Despite the lack of controlled treatment data for H5N1, this is a strong recommendation, in part, because there is a lack of known effective alternative pharmacological interventions at this time.
The panel voted on whether this recommendation should be strong or weak and there was one abstention and one dissenting vote.
ACCP: Acute coronary syndromeWould a recommendation ignoring V & P be possible?
For all patients presenting with NSTE ACS, without a clear allergy to aspirin, we recommend immediate aspirin, 75 to 325 mg po, and then daily, 75 to 162 mg po (strong recommendation, high quality evidence).
Value sensitive recommendation
Idiopathic deep venous thrombosis (DVT) is potentially life threatening condition
Patients usually receive blood thinners for one year Continuing therapy will reduce a patients absolute
risk for recurrent DVT by 7% per year for several years
The burdens include: taking a blood thinner daily keeping dietary intake of vitamin K constant blood tests to monitor the intensity of anticoagulation living with increased risk of minor and major bleeding
Value sensitive recommendations→ Patients who are very averse to a recurrent DVT would consider the benefits of avoiding DVT worth the downsides of taking warfarin. Other patients are likely to consider the benefit not worth the harms and burden. For patients with idiopathic DVT, without elevated bleeding risk, we suggest long term warfarin therapy (weak recommendation, high quality evidence).
Values and preferences: this recommendation ascribes a low value to bleeding complications and burden from therapy and a high value to avoiding DVTs
Background to GRADEpro
People faced with a health care decision need summaries, including information about the quality of evidence Detailed summaries: providing guidance for large
audiences, e.g. guideline panels – detailed profiles
Usable shorter summaries: users of systematic reviews, e.g. clinicians
How do I create a summary of findings table or evidence profile GRADEpro – software to create SoF Import data from RevMan 5 into
GRADEpro Create table – author makes
suggestions about information to present and GRADEs the evidence
Export table from GRADEpro and import into RevMan 5
Creating a new GRADEpro file
Profile groups
Profiles
Profiles: Questions
Importing a RevMan 5 file of a systematic review
Imported data from RevMan 5 file: • outcomes• meta-analyses results• bibliographic information
Managing outcomes to include a maximum of 7
Entering/editing information for dichotomous outcomes
Entering/editing information to grade the quality of the evidence
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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
3. Directness of Evidence
indirect comparisons interested in A versus B have A versus C and B versus C
differences in patients interventions outcomes
Directness of EvidenceTable 5. Sources of likely indirectness of evidenceSource of indirectness Question of interest ExampleIndirect comparison Early emergency department
systemic corticosteroids to treat acute exacerbations in adult patients with asthma
Both oral and intravenous routes are effective but there is no direct comparison of these two routes of administration in adults.
Differences in populations
Anti-leukotrienes plus inhaled glucocorticosteroids vs. inhaled glucocorticosteroids alone to prevent asthma exacerbations and nighttime symptoms in patients with chronic asthma and allergic rhinitis.
Trials that measured asthma exacerbations and nighttime symptoms did not include patients with allergic rhinitis.
Differences in intervention
Avoidance of pet allergens in non-allergic infants or preschool children to prevent development of allergy.
Available studies used multifaceted interventions directed at multiple potential risk factors in addition to pet avoidance.
Differences in outcomes of interest
Intranasal glucocorticosteroids vs. oral H1-antihistamines in children with seasonal allergic rhinitis.
In the available study parents were rating the symptoms and quality of life of their teenage children, instead the children themselves.
4. Reporting Bias
reporting bias reporting of studies
publication bias number of small studies
reporting of outcomes
Example: a systematic review of topical treatments for seasonal allergic conjunctivitis showed that patients using topical sodium cromoglycate were more likely to perceive benefit than those using placebo. However, only small trials reported clinically and statistically significant benefits of active treatment, while a larger trial showed a much smaller and a statistically not significant effect (Owen 2004 [53]). These findings suggest that smaller studies demonstrating smaller effects might not have been published.
5. Imprecision
small sample size small number of events
wide confidence intervals uncertainty about magnitude of effect
Disclosure
In the past three years, Dr. Schünemann received no personal payments for service from the pharmaceutical industry. His research group received research grants and - until April 2008 - fees and/or honoraria that were deposited into research accounts from Chiesi Foundation and Lily, as lecture fees related to research methodology. He is documents editor for the American Thoracic Society. Institutions or organizations that he is affiliated with likely receive funding from for-profit sponsors that are supporting infrastructure and research that may serve his work.