holger schünemann, md, phd chair, department of clinical epidemiology & biostatistics

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HOW CAN WE ASSIST PRACTITIONERS TO ASSESS AND IMPLEMENT MEANINGFUL THERAPIES FOR THEIR PATIENTS: THE EXAMPLE OF THE GRADE APPROACH Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics Michael Gent Chair in Healthcare Research Professor of Clinical Epidemiology, Biostatistics and Medicine McMaster University, Hamilton, Canada Baltimore, May 5, 2009 1

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Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics Michael Gent Chair in Healthcare Research Professor of Clinical Epidemiology, Biostatistics and Medicine McMaster University, Hamilton, Canada Baltimore, May 5, 2009. - PowerPoint PPT Presentation

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Page 1: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

HOW CAN WE ASSIST PRACTITIONERS TO ASSESS AND IMPLEMENT MEANINGFUL THERAPIES FOR THEIR PATIENTS: THE EXAMPLE OF THE GRADE APPROACH

Holger Schünemann, MD, PhDChair, Department of Clinical Epidemiology & BiostatisticsMichael Gent Chair in Healthcare ResearchProfessor of Clinical Epidemiology, Biostatistics and MedicineMcMaster University, Hamilton, Canada

Baltimore, May 5, 2009

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Page 2: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

Disclosure

In the past three years, Dr. Schünemann received no personal payments for service from the pharmaceutical industry. During that time, his research group received research grants and - until April 2008 - fees and/or honoraria that were deposited into research accounts from Chiesi Foundation, Pfizer, UnitedBioSource 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. He is a GRADE Working Group Member

Page 3: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

Content Key principles of guidance

documents

GRADE approach Quality of evidence Strength of recommendations

Page 4: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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.

Interventions: antivirals, such as neuraminidase inhibitors oseltamivir and zanamivir

Page 5: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

Relevant healthcare question?Clinical question:Population: Avian Flu/influenza A (H5N1) patientsIntervention: Oseltamivir (or Zanamivir) Comparison: No pharmacological interventionOutcomes: Mortality, hospitalizations,

resource use, adverse outcomes, antimicrobial resistanceWHO Avian Influenza GL. Schunemann et

al., The Lancet ID, 2007

Page 6: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

There are no RCTs! Do you think that users of

recommendations would like to be informed about the basis (explanation) for a recommendation if they were asked (by their patients)?

I suspect the answer is “yes” If we need to provide the basis for

recommendations, we need to say whether the evidence is good or not so good; in other words perhaps “no RCTs” 7

Page 7: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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

Page 8: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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

Page 9: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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

Expert O

pinion

Expert Opinion

Page 10: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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

Page 11: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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Recommendations vs statements!

Page 12: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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

Page 13: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

GRADE WORKING GROUP

Grades of Recommendation Assessment,

Development and Evaluation

CMAJ 2003, BMJ 2004, BMC 2004, BMC 2005, AJRCCM 2006, Chest 2006, BMJ 2008

Page 14: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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

Page 15: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

GRADE Uptake

World Health Organization Allergic Rhinitis in Asthma Guidelines (ARIA) American Thoracic Society British Medical Journal 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

Page 16: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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

Page 17: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

Determinants of quality RCTs start high observational studies start low 5 factors that can lower quality

1. limitations of detailed design and execution2. inconsistency3. indirectness4. reporting bias5. Imprecision

3 factors can increase quality1. large magnitude of effect2. all plausible confounding may be working to reduce the

demonstrated effect or increase the effect if no effect was observed

3. dose-response gradient

Page 18: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

1. Design and Execution limitations

Randomization lack of concealment intention to treat principle violated inadequate blinding loss to follow-up early stopping for benefit

The evidence for the effect of sublingual immunotherapy in children with allergic rhinitis on the development of asthma, comes from a single randomised trial with no description of randomisation, concealment of allocation, and type of analysis, no blinding, and 21% of children lost to follow-up. These very serious limitations would limit our confidence in the estimates of effect and likely lead to downgrading the quality of evidence.

Page 19: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

1. Design and Execution From Cates , CDSR 2008

CDSR 2008

Page 20: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

1. Design and Execution

Overall judgment required

Page 21: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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

Page 22: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

3. Directness of Evidence

indirect comparisons interested in A versus B have A versus C and B versus C

differences in patients interventions outcomes

Page 23: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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 patients with asthma

Both oral and intravenous routes are effective but there is no direct comparison of these two routes of administration.

Page 24: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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 patients with asthma

Both oral and intravenous routes are effective but there is no direct comparison of these two routes of administration.

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.

Page 25: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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 patients with asthma

Both oral and intravenous routes are effective but there is no direct comparison of these two routes of administration.

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.

Page 26: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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 patients with asthma

Both oral and intravenous routes are effective but there is no direct comparison of these two routes of administration.

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.

Page 27: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

4. Publication Bias

Publication bias Cave! Only few small studies

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. These findings suggest that smaller studies demonstrating smaller effects might not have been published.

Page 28: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

5. Imprecision

small sample size small number of events

wide confidence intervals uncertainty about magnitude of effect

Observational studies examining the impact of exclusive breastfeeding on development of allergic rhinitis in high risk infants showed a relative risk of 0.87 (95% CI: 0.48 to 1.58) that neither rules out important benefit nor important harm (Mimouni Bloch 2002).

Page 29: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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

The parachute example: if we’d look at the observational evidence, we’d find a very large effect and the evidence probably would be high quality for preventing death

dose response relation (higher dose of brain radiation in childhood leukemia leads to greater risk of late malignancies)

Residual confounding unlikely to be responsible for observed effect

Page 30: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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

Page 31: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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/conditional

Page 32: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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

Page 33: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

Developing recommendations

Page 34: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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

Page 35: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

Judgments about the strength of a recommendation - oseltamivir for treatment of patients hospitalised with avian influenza (H5N1)Factors CommentsBalance between desirable

and undesirable effects“The benefits are uncertain, but

potentially large.”

Quality of the evidence “The quality of the evidence is very low.”

Values and preferences “All patients and care providers would accept treatment for H5N1 disease.” No alternative

Costs (resource use) “The cost is not high for treatment of sporadic cases.”

Page 36: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

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Recommendations vs statements!

Page 37: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

Example: Oseltamivir for Avian FluRecommendation: 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

Page 38: Holger Schünemann, MD, PhD Chair, Department of Clinical Epidemiology & Biostatistics

Conclusion

Clinicians need appropiate 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 wide adoption