Dynamic Treatment Regimes for Chronic, Relapsing Disorders

Friday, December 6, 2002 - 9:10am - 9:35am
Keller 3-180
Susan Murphy (University of Michigan)
The management of chronic, relapsing disorders can be viewed as a control problem in that multi-stage treatment decisions are made with the goal of optimizing mean response. For example, in the prevention of relapse by recovering alcoholics, the response might be percent days abstinent and the treatment decisions might be, which preventative treatment should be used initially, how long should we wait to declare the initial treatment ineffective and switch to a secondary treatment, which secondary treatment should be used, when should treatment be stopped, etc. These treatment decisions would be made on the basis of time varying covariates such as number of days heavy drinking, measures of craving, measures of stress, patient preference and results of urinalyses.

A important open problem in this area is how we might use a batch of data, i.e., a longitudinal sample of individuals for whom both response, covariates and treatment decisions are recorded for each time period, so as to estimate the optimal decision rules. This challenging area is characterized by delayed effects of treatment, an unknown model relating past treatment and covariates to future covariates and a high noise to signal ratio.