Predicting early clinical recovery in first-episode psychosis: development and external validation of a clinically interpretable multivariable model

A simple, interpretable logistic regression model based on routine clinical and cognitive variables can predict early recovery in FEP with acceptable generalisability. These findings support the use of transparent, clinically grounded models in early psychosis care and highlight the current limitations of genetic predictors for individualised treatment.