Dominic Oliver, Maite Arribas, Benjamin I Perry, Daniel Whiting, Graham Blackman, Kamil Krakowski, Aida Seyedsalehi, Emanuele F Osimo, Siân Lowri Griffiths, Daniel Stahl, Andrea Cipriani, Seena Fazel, Paolo Fusar-Poli, Philip McGuire
The use of clinical prediction models to produce individualised risk estimates can facilitate the implementation of precision psychiatry. As a source of data from large, clinically representative patient samples, electronic health records (EHRs) provide a platform to develop and validate clinical prediction models, as well as potentially implementing them in routine clinical care. The present review describes promising use cases for the application of precision psychiatry to EHR data and considers their performance in terms of discrimination (ability to separate individuals with and without the outcome) and calibration (extent to which predicted risk estimates correspond to observed outcomes), as well as their potential clinical utility (weighing benefits and costs associated with the model compared to different approaches across different assumptions of the number-needed-to-test)...
February 24, 2024: Biological Psychiatry