holger schünemann, md, phd professor mcmaster university, hamilton, canada madrid, spain november...

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

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

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)



Comment








Comment

Quality of the evidence High


Clear balance towards harm

Values and preferences Little variability

Costs (resource allocation) Lowering use of supplements will reduce resource use


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


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


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

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?


I.V. Mg in acute myocardial infarctionPublication bias

Meta-analysisYusuf S.Circulation 1993

ISIS-4Lancet 1995


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?

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

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

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


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


(-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



Comment






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


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.


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


“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


Comment



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 & 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

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

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:



*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

The GRADE approach

Separation of 2 issues:1) 4 categories of quality of evidence:



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


(-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


(-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



Comment







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).



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.


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

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.

holger schünemann, md, phd professor mcmaster university, hamilton, canada madrid, spain november...

Documents

evidence evidence

decisions slide

overall quality slide

grading evidence

clinical professor

case series

approaches grade

content background