Translational Psychiatry (May 2022)

Is it possible to stage schizophrenia? A systematic review

  • Clara Martínez-Cao,
  • Lorena de la Fuente-Tomás,
  • Ainoa García-Fernández,
  • Leticia González-Blanco,
  • Pilar A. Sáiz,
  • María Paz Garcia-Portilla,
  • Julio Bobes

DOI
https://doi.org/10.1038/s41398-022-01889-y
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 11

Abstract

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Abstract Introduction A staging model is a clinical tool used to define the development of a disease over time. In schizophrenia, authors have proposed different theoretical staging models of increasing complexity. Therefore, the aims of our study were to provide an updated and critical view of the proposed clinical staging models for schizophrenia and to review the empirical data that support them. Methods Systematic literature review following PRISMA guidelines. From the PubMed database and backward reference search, a total of 141 records were retrieved, but only 20 were selected according to the inclusion criteria: (a) available in English; (b) participants with schizophrenia ≥ 18 years; and (c) theoretical and empirical research studies intended to develop, validate, and/or improve staging models of schizophrenia. Results Different clinical staging models for schizophrenia were identified, information about the proposed stages was tabulated and presented in the Results section (Tables 1, 2). Most of which include neuroimaging, functioning, and psychopathology, but only two models add objective biomarkers and none include patient point of view. However, few models have been psychometrically tested or used small samples and thus have been validated only partially. In addition, five studies proposed therapeutic interventions according to the stage of the disorder from a theoretical point of view. Discussion In conclusion, it is possible to stage schizophrenia, but the models developed have several limitations. Empirical validation and inclusion of more specific biomarkers and measures of other life areas affected by schizophrenia could help in the development of more valid models.