Abstract
BACKGROUND: There is substantial uncertainty regarding the efficacy of antidepressants in the treatment of bipolar disorders. METHODS: Traditional randomized controlled trials and statistical methods are not designed to discover if, when, and to whom an intervention should be applied; thus, other methodological approaches are needed that allow for the practice of personalized, evidence-based medicine with patients with bipolar depression. RESULTS: Dynamic treatment regimes operationalize clinical decision-making as a sequence of decision rules, one per stage of clinical intervention, that map patient information to a recommended treatment. Using data from the acute depression randomized care (RAD) pathway of the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) study, we estimate an optimal dynamic treatment regime via Q-learning. CONCLUSIONS: The estimated optimal treatment regime presents some evidence that patients in the RAD pathway of STEP-BD who experienced a (hypo)manic episode before the depressive episode may do better to forgo adding an antidepressant to a mandatory mood stabilizer.