TY  - JOUR
TI  - Using a statistical learning approach to identify sociodemographic and clinical predictors of response to clozapine
Y1  - 2022/04//
VL  - 36
EP  - 506
A1  - Fonseca de Freitas, Daniela
A1  - Kadra-Scalzo, Giouliana
A1  - Agbedjro, Deborah
A1  - Francis, Emma
A1  - Ridler, Isobel
A1  - Pritchard, Megan
A1  - Shetty, Hitesh
A1  - Segev, Aviv
A1  - Casetta, Cecilia
A1  - Smart, Sophie E
A1  - Downs, Johnny
A1  - Christensen, Søren Rahn
A1  - Bak, Nikolaj
A1  - Kinon, Bruce J
A1  - Stahl, Daniel
A1  - MacCabe, James H
A1  - Hayes, Richard D
KW  - Refractory psychosis
KW  -  health records
KW  -  machine learning
KW  -  zaponex
KW  -  clorazil
IS  - 4
N1  - © The Author(s) 2022.
Creative Commons License (CC BY 4.0)
This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
ID  - discovery10167753
UR  - https://doi.org/10.1177/02698811221078746
PB  - SAGE Publications
JF  - Journal of Psychopharmacology
SP  - 498
SN  - 0269-8811
N2  - 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) scale. RESULTS: We identified 242 service-users with a treatment-resistant psychotic disorder who had their first trial of clozapine and continued the treatment for at least 3 months. The LASSO regression identified three predictors of response to clozapine: higher severity of illness at baseline, female gender and having a comorbid mood disorder. These factors are estimated to explain 18% of the variance in clozapine response. The model's optimism-corrected calibration slope was 1.37, suggesting that the model will underfit when applied to new data. CONCLUSIONS: These findings suggest that women, people with a comorbid mood disorder and those who are most ill at baseline respond better to clozapine. However, the accuracy of the internally validated and recalibrated model was low. Therefore, future research should indicate whether a prediction model developed by including routinely collected data, in combination with biological information, presents adequate predictive ability to be applied in clinical settings.
AV  - public
ER  -