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Neuroimaging and Treatment Evidence for Clinical Staging in Psychotic Disorders: From the At-Risk Mental State to Chronic Schizophrenia

      A new approach to understanding severe mental disorders such as schizophrenia is to adopt a clinical staging model. Such a model defines the extent of the illness such that earlier and milder phenomena are distinguished from later, more impairing features. Specifically, a clinical staging model makes three key predictions. First, pathologic measures should be more abnormal in more severe stages. Second, patients who progress between the stages should show change in these same pathologic measures. Finally, treatment should be more effective in the earlier stages, as well as more benign. In this article, we review the evidence for these three predictions from studies of psychotic disorders, with a focus on neuroimaging data. For all three, the balance of evidence supports the predictions of the staging model. However, there are a number of alternative explanations for these findings, including the effects of medication and symptom heterogeneity.

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      Linked Article

      • Challenges Associated with Application of Clinical Staging Models to Psychotic Disorders
        Biological PsychiatryVol. 70Issue 7
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          Previously, McGorry and colleagues (1,2) proposed the application of clinical staging models to psychiatric disorders, with a focus on psychoses and severe mood disorders. In this issue, Wood et al. (3) expand on this staging model for psychotic disorders, using pathophysiological data and treatment response data to evaluate key predictions associated with a valid staging model (3). The staging model proposed uses clinical criteria to define illness severity stages that progress from relatively few, mild, and nonspecific symptoms to an increasing number of more severe symptoms, including psychotic symptoms, neurocognitive impairments, comorbid conditions, and functional decline, culminating in the persistent disabling symptoms of chronic schizophrenia.
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