University of Oulu

Annika Seppälä, Jenni Pylvänäinen, Heli Lehtiniemi, Noora Hirvonen, Iluminada Corripio, Hannu Koponen, Jussi Seppälä, Anthony Ahmed, Matti Isohanni, Jouko Miettunen, Erika Jääskeläinen, Predictors of response to pharmacological treatments in treatment-resistant schizophrenia – A systematic review and meta-analysis, Schizophrenia Research, Volume 236, 2021, Pages 123-134, ISSN 0920-9964,

Predictors of response to pharmacological treatments in treatment-resistant schizophrenia : a systematic review and meta-analysis

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Author: Seppälä, Annika1,2; Pylvänäinen, Jenni1,2; Lehtiniemi, Heli1,2,3;
Organizations: 1Center for Life Course Health Research, University of Oulu, Oulu, Finland
2Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
3Arctic Biobank, Infrastructure for Population Studies, Faculty of Medicine, University of Oulu, Oulu, Finland
4Information Studies, Faculty of Humanities, University of Oulu, Oulu, Finland
5Department of Psychiatry, Hospital de la Santa Creu i Sant Pau, CIBERSAM G21, U.A.B (Autonomous University of Barcelona), Barcelona, Spain
6University of Helsinki and Helsinki University Hospital, Psychiatry, Helsinki, Finland
7Department of Mental Health and Substance Use Disorders, South Carelia Social and Health Care District, Lappeenranta, Finland
8Department of Psychiatry, Weill Cornell Medicine, Cornell University, White Plains, USA
9Department of Psychiatry, University Hospital of Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 2.2 MB)
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Language: English
Published: Elsevier, 2021
Publish Date: 2021-11-12


Background: As the burden of treatment-resistant schizophrenia (TRS) on patients and society is high it is important to identify predictors of response to medications in TRS. The aim was to analyse whether baseline patient and study characteristics predict treatment response in TRS in drug trials.

Methods: A comprehensive search strategy completed in PubMed, Cochrane and Web of Science helped identify relevant studies. The studies had to meet the following criteria: English language clinical trial of pharmacological treatment of TRS, clear definition of TRS and response, percentage of response reported, at least one baseline characteristic presented, and total sample size of at least 15. Meta-regression techniques served to explore whether baseline characteristics predict response to medication in TRS.

Results: 77 articles were included in the systematic review. The overall sample included 7546 patients, of which 41% achieved response. Higher positive symptom score at baseline predicted higher response percentage. None of the other baseline patient or study characteristics achieved statistical significance at predicting response. When analysed in groups divided by antipsychotic drugs, studies of clozapine and other atypical antipsychotics produced the highest response rate.

Conclusions: This meta-analytic review identified surprisingly few baseline characteristics that predicted treatment response. However, higher positive symptoms and the use of atypical antipsychotics – particularly clozapine –was associated with the greatest likelihood of response. The difficulty involved in the prediction of medication response in TRS necessitates careful monitoring and personalised medication management. There is a need for more investigations of the predictors of treatment response in TRS.

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Series: Schizophrenia research
ISSN: 0920-9964
ISSN-E: 1573-2509
ISSN-L: 0920-9964
Volume: 236
Pages: 123 - 134
DOI: 10.1016/j.schres.2021.08.005
Type of Publication: A2 Review article in a scientific journal
Field of Science: 3124 Neurology and psychiatry
Funding: This work was supported by grants from the Finnish Cultural Foundation, Grant number 2DC49079, Jalmari and Rauha Ahokas' Foundation, the Academy of Finland, Grant number 316563 and Oulu University Hospital funding.
Academy of Finland Grant Number: 316563
Detailed Information: 316563 (Academy of Finland Funding decision)
Copyright information: © 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (