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1
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2
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- 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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3
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- 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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4
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- 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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5
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- 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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6
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- “The investigation of truth is in one way hard, in another easy”
- Aristotle, Metaphysics II
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