A narrative review of digital biomarkers in the management of major depressive disorder and treatment-resistant forms - Vignapiano, Annarita; Monaco, Francesco; Pagano, Claudio; Piacente, Martina; Farina, Federica; Petrillo, Gianvito; Sica, Raffaella; Marenna, Alessandra; Shin, Jae Il; Solmi, Marco; Corrivetti, Giulio (Frontiers in Psychiatry, 2023)
Depression is the leading cause of worldwide disability and a leading contributor to global healthcare costs. Digital technologies have the potential to provide more objective and precise tools to detect depression-related symptoms and its resistant forms (TRD). Deployment of digital technologies in clinical research can enable remote collection of large volumes of clinically relevant data, which may be less burdensome than traditional in-clinic visits and may be more reflective of clinically relevant changes. Wearable technologies, such as smartwatches and novel sensors can generate useful digital biomarkers of depression in real-world setting. The present review will focus onthe use of digital technologies to identify biomarkers for patients whose depressive disorder does not respond satisfactorily to adequate treatment clearly have harder to treat depression. The state of the art of digital biomarkers as diagnostic and predictive tools will be depicted; main pitfalls and innovative perspectives will be highlighted. Main contributions provided by development of digital technologies in clinical research will be examined for the purposes of diagnosis, prediction of outcome and treatment response in MDD and TRD.