Estimation and extrapolation of optimal treatment and testing strategies.
We review recent developments in the estimation of an optimal treatment strategy or regime from longitudinal data collected in an observational study. We also propose novel methods for using the data obtained from an observational database in one health-care system to determine the optimal treatment regime for biologically similar subjects in a second health-care system when, for cultural, logistical, or financial reasons, the two health-care systems differ (and will continue to differ) in the frequency of, and reasons for, both laboratory tests and physician visits. Finally, we propose a novel method for estimating the optimal timing of expensive and/or painful diagnostic or prognostic tests. Diagnostic or prognostic tests are only useful in so far as they help a physician to determine the optimal dosing strategy, by providing information on both the current health state and the prognosis of a patient because, in contrast to drug therapies, these tests have no direct causal effect on disease progression. Our new method explicitly incorporates this no direct effect restriction.
Robins
James
J
Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA. robins@hsph.harvard.edu
Orellana
Liliana
L
Rotnitzky
Andrea
A
D023241:Antiretroviral Therapy, Highly Active; D015982:Bias; D003627:Data Interpretation, Statistical; D015658:HIV Infections / Q000188:drug therapy*; D006801:Humans; D008137:Longitudinal Studies; D015233:Models, Statistical; D011379:Prognosis; D016896:Treatment Outcome