Grading evidence and recommendations - PowerPoint PPT Presentation

Grading evidence and recommendations

Holger Schünemann

Andy Oxman

for the GRADE Working Group

Professional good intentions and plausible theories are insufficient for selecting policies and practices for protecting, promoting and restoring health.

Iain Chalmers

How can we judge the extent of our confidence that adherence to a recommendation will do more good than harm?

GRADE

Grades of Recommendation Assessment, Development and Evaluation

• Have prepared a guideline
• Read the BMJ paper
• Have prepared a systematic review and a summary of findings table
• Have attended a GRADE meeting, workshop or talk

• Began as informal working group in 2000
• Researchers/guideline developers with interest in methodology
• Aim: to develop a common system for grading the quality of evidence and the strength of recommendations that is sensible and to explore the range of interventions and contexts for which it might be useful*
• 12 meetings (~10 – 35 attendants)
• Evaluation of existing systems and reliability*
• Workshops at Cochrane Colloquia, WHO and GIN since 2000

*Grade Working Group. CMAJ 2003, BMJ 2004, BMC 2004, BMC 2005

Dana Best, assistant professorb

Peter A Briss, chiefc

Martin Eccles, professord

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

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, associate professorg,s

Tessa Tan-Torres Edejer, medical officer/scientistt

Helena Varonen, associate editoru

Gunn E Vist, researcherf

John W Williams Jr, associate 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

• users looking for different things
• just tell me what to do (recommendation)
• what to do, and on strong or weak grounds
• recommendation and grade
• recommend, grade, evidence summary, values
• systematic review, value statement
• evidence from individual studies

• current profusion: can there be consensus?
• trade-off benefits and risks
• do it (or don’t do it)
• probably do it (or probably don’t do it)
• quality of underlying evidence
• high quality (well done RCT)
• intermediate (quasi-RCT)
• low (well done observational)
• very low (anything else)

• poor RCT design, implementation
• inconsistency
• indirect
• A vs B, but have A to C, B to C
• patients, interventions, outcomes
• reporting bias
• reporting bias

• magnitude of effect
• dose-response
• biases favor control
• for-profit, not-for-profit

• never
• patient values differ
• just lay out benefits and risks
• when evidence strong enough
• when very weak, too uncertain
• clinicians need guidance
• intense study demands decision

• People draw conclusions about the
• quality of evidence
• strength of recommendations
• Systematic and explicit approaches can help
• protect against errors
• resolve disagreements
• facilitate critical appraisal
• communicate information
• However, there is wide variation in currently used approaches

II-2 B

C+ 1

Strong Strongly recommended

Organization

USPSTF

ACCP

GCPS

B Class I

C+ 1

IV C

Organization

AHA

ACCP

SIGN

Recommendation for use of oral anticoagulation in patients with atrial fibrillation and rheumatic mitral valve disease

• First ACCP guidelines in 1986 (J. Hirsh; J. Dalen)
• Initially aimed at consensus
• Methodologists involved since beginning
• Now formally convening every 2 to 3 years
• > 200.000 copies in 2001
• Seventh conference held in 2003
• 87 panel members, 22 chapters
• Across subspecialties
• 565 recommendations, 230 new
• Evidence Based Recommendations

• Evidence – recommendation: transparent link
• Explicit inclusion criteria
• Comprehensive search
• Standardized consideration of study quality
• Conduct/use meta-analysis
• Grade recommendations
• Acknowledge values and preferences underlying recommendations

Schünemann et al. Chest 2004

Schünemann et al. Chest 2004

Schünemann HJ et al. Chest 2004

Albers et al. Chest 2004

The extent to which one can be confident that an estimate of effect or association is correct.

It depends on the:

• study design (e.g. RCT, cohort study)
• study quality/limitations (protection against bias; e.g. concealment of allocation, blinding, follow-up)
• consistency of results
• directness of the evidence including the
• populations (those of interest versus similar; for example, older, sicker or more co-morbidity)
• interventions (those of interest versus similar; for example, drugs within the same class)
• outcomes (important versus surrogate outcomes)
• comparison (A - C versus A - B & C - B)

The quality of the evidence (i.e. our confidence) may also be REDUCEDwhen there is:

• Sparse or imprecise data
• Reporting bias

The quality of the evidence (i.e. our confidence) may be INCREASEDwhen there is:

• A strong association
• A dose response relationship
• All plausible confounders would have reduced the observed effect
• All plausible biases would have increased the observed lack of effect

Quality assessment criteria

• 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.

• Most systems not explicit
• Options:
• strongest outcome
• primary outcome
• benefits
• weighted
• separate grades for benefits and harms
• no overall grade
• weakest outcome
• Based on lowest of all the critical outcomes
• Beyond the scope of a systematic review

The extent to which one can be confident that adherence to a recommendation will do more good than harm.

• trade-offs (the relative value attached to the expected benefits, harms and costs)
• quality of the evidence
• translation of the evidence into practice in a specific setting
• uncertainty about baseline risk

• Before considering cost and making a recommendation
• For a specified setting, taking into account issues of translation into practice

• the estimated size of the effect for each main outcome
• the precision of these estimates
• the relative value attached to the expected benefits and harms
• important factors that could be expected to modify the size of the expected effects in specific settings; e.g. proximity to a hospital

• Net benefits: The intervention does more good than harm.
• Trade-offs: There are important trade-offs between the benefits and harms.
• Uncertain net benefits: It is not clear whether the intervention does more good than harm.
• Not net benefits: The intervention does not do more good than harm.

This should include considerations of costs; i.e. “Is the net gain (benefits-harms) worth the costs?”

• Do it
• Probably do it

No recommendation

• Probably don’t do it
• Don’t do it

Will GRADE lead to change?

• Quality of evidence across studies for
• CHD
• Hip fracture
• Colorectal cancer
• Breast cancer
• Stroke
• Thrombosis
• Gall bladder disease
• Quality of evidence across critical outcomes
• Balance between benefits and harms
• Recommendations

Oestrogen + progestin versus usual care

• Diagnostic tests
• Complexity
• Costs
• (Equity)
• Empirical evaluations

GRADE profiler (GRADEpro)

• Critical appraisal of other systems
• Pilot test + sensibility
• “Case law” + practical experience
• Guidance for judgements
• Single studies
• Sparse data or imprecise data
• Agreement
• Validity?
• Comparisons with other systems
• Alternative presentations

• Explicit definitions
• Explicit, sequential judgements
• Components of quality
• Overall quality
• Relative importance of outcomes
• Balance between health benefits and harms
• Balance between incremental health benefits and costs
• Consideration of equity
• Evidence profiles
• International collaboration
• Software
• Consistent judgements?
• Communication?

• WHO
• American Endocrine Society
• American College of Chest Physicians (ACCP)
• Italian National Cancer Institute
• Clinical Evidence
• Norwegian Centre for Health Services
• UpToDate
• Close relationship with Cochrane Collaboration
• American Society of Clinical Oncology (ASCO)

We will serve the public more responsibly and ethically when research designed to reduce the likelihood that we will be misled by bias and the play of chance has become an expected element of professional and policy making practice, not an optional add-on.

Iain Chalmers

A prerequisitePractitioners and policy makers must make much clearer that they need rigorous evaluative research to help ensure that they do more good than harm.

Iain Chalmers

• Include important (disaggregated) costs in evidence summaries and balance sheets when relevant
• May be useful to aggregate and value (in monetary terms)
• Always include disaggregated resource utilisation
• Note when important information is missing
• Published cost-effectiveness analyses are rarely helpful
• Assess the quality of the evidence for important costs (consumption of resources) as for other effects (Were quantities measured reliably?)
• If costs are critical to a decision, low quality evidence can lower the overall quality of evidence
• Costs are negotiable (the value of resources)
• There are many possible criteria for making a recommendation

Should activated protein C be given to patients in severe sepsis?

An example with costs

• Name: Jaeschke and Schunemann
• Date: September 2004
• Question: Should APC be used for severe sepsis?
• Setting: ICU in Paris
• Baseline risk: Severe sepsis or septic shock > 24 h
• References: Effectiveness: Bernard 2001. Efficacy and safety of recombinant human activated protein C for severe sepsis. NEJM 2001; 344:699 and Manns 2002. An economic evaluation of activated protein C treatment for severe sepsis. NEJM 2002;347:993.
• Cost-effectiveness: Manns 2002. An economic evaluation of activated protein C treatment for severe sepsis. NEJM 2002;347:993.

• Treatment effect
• Adverse effects
• Cost
• Cost-effectiveness
• Equity
• Seriousness of the problem
• Administrative restrictions