Using a statistical learning approach to identify sociodemographic and clinical predictors of response to clozapine.

ABSTRACT:

Background

A proportion of people with treatment-resistant schizophrenia fail to show improvement on clozapine treatment. Knowledge of the sociodemographic and clinical factors predicting clozapine response may be useful in developing personalised approaches to treatment.

Methods

This retrospective cohort study used data from the electronic health records of the South London and Maudsley (SLaM) hospital between 2007 and 2011. Using the Least Absolute Shrinkage and Selection Operator (LASSO) regression statistical learning approach, we examined 35 sociodemographic and clinical factors' predictive ability of response to clozapine at 3 months of treatment. Response was assessed by the level of change in the severity of the symptoms using the Clinical Global Impression (CGI) sca

SUBMITTER: Fonseca de Freitas D 

PROVIDER: S-EPMC9066692 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature