Notes
Slide Show
Outline
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Moving From Observational Studies to Clinical Trials:
 Why Do We Sometimes Get It Wrong?
  • Premises for the workshop:
  • Causal and non-causal associations are often confused by the medical science community, the media, the public, and policy makers.
  • This can have important consequences:
    • large randomized trials can be launched based on insufficient information
    • large randomized trials can be delayed (or not launched) based on unjustified inferences
    • ineffective or harmful health policy or practice can be instituted or continued
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Moving From Observational Studies to Clinical Trials:
 Why Do We Sometimes Get It Wrong?
  • Underlying question for the workshop:


  • How can mistakes be avoided when deciding whether or not to launch large “definitive” clinical or community trials?


  • Specifically:


  • What are the traditional tools to help us judge an intervention or a body of evidence?
  • What new methodologies are available (or are needed) to judge evidence in today's research environment?
  • What are research directions for validating methods to distinguish between causal and non-causal chains of evidence?
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Prioritization Criteria for Launching a Large Randomized Clinical Trial
  • Therapeutic equipoise among health professionals
  • Strength of evidence: not too strong, not too weak
  • Magnitude of potential health benefits or contribution to scientific understanding
  • Portfolio balance
  • Window of opportunity: potential for “runaway” practice
  • Social, political context/pressures
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Moving From Observational Studies to Clinical Trials:
 Why Do We Sometimes Get It Wrong?
  • Sessions:
  • I. Background
  • Distinguishing Causal From Non-causal Associations
  • Evaluating and Grading Strength of Evidence
  • Evaluating Study Outcomes: Biomarkers, Intermediate Endpoints, and Surrogate Endpoints
  • Expressing Study Results to the Professional and Public Communities
  • The Data and Safety Monitoring Board: Should This Trial Be Stopped?
  • Putting It All Together: Translating Data Into Health Policy





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"“The investigation of truth..."
  • “The investigation of truth is in one way hard, in another easy”
  • Aristotle, Metaphysics II