In most areas of medicine, biological tests are routinely used to assist diagnosis and treatment allocation. However, this is not the case in psychiatry, which is now one of the last areas of medicine where diseases are still diagnosed based on symptoms and biological tests to assist treatment allocation remain to be developed. Heterogeneity is widely recognized as a major challenge toward achieving these objectives and many approaches to tackle such heterogeneity have been proposed over the years, largely aiming to partition psychiatric disorders into more consistent subtypes. However, none of these stratifications have translated toward clinical practice. Here, we review the different approaches employed, focusing on methods that use biological measures to stratify psychiatric disorders. We highlight several recent prominent studies and identify key challenges for the field. Specifically, we argue that a lack of validation or replication of prospective stratifications coupled with a widespread fixation on finding sharply defined subtypes has impeded progress. We outline recently proposed methodological innovations that may be useful to move forward. Many of these innovations provide inferences at the level of individual participants and do not rest on the assumption that the biological fingerprints underlying psychiatric disorders can be cleanly separated into subtypes.
|Name||Personalized Psychiatry: Big Data Analytics in Mental Health|