Evidence-based treatment pathways for translational studies in obsessive-compulsive disorders

Obsessive-compulsive disorder (OCD) and related disorders are costly and burdensome long-term illnesses. Whilst evidence-based pharmacological and psychological treatments are available for OCD, a significant proportion of OCD patients fail to respond and for many of the OCD-related disorders no validated treatments are as yet recognised. In addition, predictors of treatment response/non-response to guide clinicians in the management of individual patients are lacking. The introduction of personalised medicine to psychiatry is expected to offer the novel prospect of identifying the most effective treatment for a patient in a timely and cost-effective way. Translational research that investigates endophenotype predictors of treatment response in OCD and related disorders may pave the way toward personalised medicine. Such research is likely to require multidisciplinary collaboration between neuroscientists and clinicians, so that the right clinical questions are addressed, and large datasets, entailing multinational, multicentre sampling. In order to facilitate the translational investigation of the key aspects of the treatment response, these studies would require access to standardised treatment paradigms that are internationally recognised. In this chapter, we introduce some of the most important outstanding questions for personalised medicine that translational research could be expected to address within the next 10 years. We review the available tools and techniques for standardised clinical assessment and the criteria that are used to define the degree of therapeutic response (response, remission, relapse, resistance) that would naturally dictate the direction of treatment. We also present a series of consecutive stepped treatment algorithms based on evidence-based practice and modelled on naturalistic care that we believe could be adapted to multicentre settings as a template for the translational researcher to aid in the design of pragmatic treatment trials that are capable of identifying biomarkers of treatment response or non-response at each key stage of the evidence-based canon.