JSM Activity #341


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Activity ID:  341
Title
! Beyond Intention to Treat: New Methodology for Estimating Treatment Effects in Clinical Trials
Date / Time / Room Sponsor Type
08/14/2002
2:00 PM - 3:50 PM
Room: H-Madison Suite
Biometrics Section*, Biopharmaceutical Section*, ENAR Invited
Organizer: Sati Mazumdar, University of Pittsburgh
Chair: Howard E. Rockette, University of Pittsburgh
Discussant: 3:20 PM - Peter Lachenbruch, Food and Drug Administration    
Floor Discussion 3:40 PM
Description

The session will start with a discussion of varying definitions of what constitutes intention to treat (ITT), regulatory mandates and examples providing evidential basis of successful submissions. These examples will range from ITT in the strong sense, through ITT in the weak sense to Not ITT. The rest of the session will focus on new methodology for estimating treatment effects in clinical trials in the face of events such as loss to follow-up, noncompliance and confounders associated with switching treatments. Bayesian hierarchical models to estimate intent-to-treat effect (ITE) and average causal effect (ACE) and propensity adjusted instrumental variable estimates will be discussed with application to clinical trials.
  300047  By:  Michael  Nessly 2:05 PM 08/14/2002
Is the Road to Drug Registration Paved with Good Intentions to Treat?

  300048  By:  Joseph W. Hogan 2:30 PM 08/14/2002
A Hierarchical Potential Outcomes Model for Estimating Both Causal and Intention-to-Treat Effects from Repeated Measures Under 'Double Sampling'

  300374  By:  Sue  Marcus 2:55 PM 08/14/2002
Comparison of Propensity-Score-Adjusted Instrumental Variable Estimate with Intent-to-Treat Estimate in Randomized Clinical Trials with Noncompliance

JSM 2002

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Revised March 2002