JSM 2005 - Toronto

Abstract #302361

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 378
Type: Invited
Date/Time: Wednesday, August 10, 2005 : 10:30 AM to 12:20 PM
Sponsor: ENAR
Abstract - #302361
Title: Estimating Mean Response as a Function of Treatment Duration, Where Treatment Duration May Be Informative Censored
Author(s): Anastasios A. Tsiatis*+ and Brent Johnson
Companies: North Carolina State University and University of North Carolina, Chapel Hill
Address: Department of Statistics, Raleigh, NC, 27695-8203, United States
Keywords: Adaptive treatment strategy ; Causal inference ; Counterfactual random variables ; No unmeasured confounders
Abstract:

In a recent clinical trial of patients with coronary heart disease who were scheduled to undergo percutaneous coronary intervention (PCI), patients randomized to receive Integrilin therapy had significantly better outcomes than patients randomized to placebo. The protocol recommended that Integrilin be given as a continuous infusion for 18--24 hours. There was debate among the clinicians on the optimal infusion duration in this 18--24-hour range, and we were asked to study this question statistically. Two issues complicated this analysis: (i) The choice of treatment duration was left to the discretion of the physician and (ii) treatment duration would have to be terminated (censored) if the patient experienced serious complications during the infusion period. To formalize the question, "What is the optimal infusion duration?" in terms of a statistical model, we developed a framework where the problem was cast using ideas developed for adaptive treatment strategies in causal inference. The problem is defined through parameters of the distribution of (unobserved) counterfactual random variables. We then show how, under some reasonable assumptions, these parameters could be estimated.


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Revised March 2005