Multivariate prediction of emerging psychosis in adolescents at high risk for schizophrenia

Integrative modeling of multivariate data from familial, neurobiological, socioenvironmental, cognitive and clinical domains represents a powerful approach to prediction of psychosis development. The high specificity and low sensitivity found using a combination of such variables suggests that their utility may be in confirmatory testing among already selected high-risk individuals, rather than for initial screening. These findings also highlight the importance of data from a broad array of etiologic and risk factors, even within a familial high-risk population. With further refinement and validation, such methods could form key components of early detection, intervention and prevention programs.