The Effect of Substance Use on 10-Year Outcome in First-Episode Psychosis

Very long-term outcome of schizophrenia

PURPOSE

The principal aim is to review recent data concerning the very long-term outcome of schizophrenia and schizophrenia spectrum disorders. We examine factors that influence outcome, including therapeutic interventions.

METHOD

PubMed and Scopus databases were searched for papers published between 2008 and 2017 reporting on prospective studies of schizophrenia or schizophrenia spectrum with a follow-up period ≥5 years with adequate outcome information. Additional publications were found in reference lists and authors' reference libraries.

RESULTS

The average proportion of patients with symptomatic remission at follow-up ranged between 16.4% in never-treated patients to 37.5% in patients who were systematically treated with antipsychotics. Good outcomes at follow-up were observed in schizophrenia and schizophrenia spectrum patients on low doses of antipsychotics and in patients with no pharmacological treatment at that time. Early detection and intensive treatment of the first episode as well as the availability of continued psychosocial treatment and support over subsequent years appeared associated with better outcomes.

CONCLUSION

The long-term outcome of schizophrenia is highly variable, depending on access to mental healthcare, early detection of psychosis and pharmacological treatment. Recent data support the effectiveness of low-dose antipsychotic treatment for long-term maintenance in some patients. A proportion of first-episode schizophrenia patients, perhaps 20%, do not need long-term maintenance antipsychotic treatment. That proportion may be higher in schizophrenia spectrum patients. The reasons why these patients do not need the long-term treatment are not well understood. Methods to predict the membership in this subgroup are not yet good enough for clinical use in individual patients.

Drug-related predictors of readmission for schizophrenia among patients admitted to treatment for drug use disorders

BACKGROUND

Patients with schizophrenia and comorbid drug use disorders (DUD) have a severe course of illness. Despite strong evidence that drug use can exacerbate psychotic symptoms, we have limited knowledge of how specific drugs may increase risk of schizophrenia readmission in this group. This study aimed to assess drug-related predictors of readmission for schizophrenia among a national cohort of patients with a history of schizophrenia admitted to DUD treatment.

METHODS

A record-linkage study was used to assess drug-related factors associated with readmission to mental health treatment for schizophrenia, using a consecutive cohort of 634 patients admitted to DUD treatment between 2000 and 2006 in Danish treatment services and tracked until February 2013 or death, controlling for baseline psychiatric treatment variables.

RESULTS

The majority of patients were males (79.8%) and the mean age was 34.7years. Of all patients, 78.7% were readmitted for schizophrenia during follow-up, and 6.8% died without having been readmitted. We found a robust association between use of amphetamine at baseline and elevated risk of readmission, a less robust association between use of cannabis and elevated risk of readmission, and no association with cocaine, opioids, alcohol, benzodiazepines, and MDMA. Furthermore, one or more psychiatric inpatients visit in the year prior to DUD admission was robustly associated with elevated risk of schizophrenia readmission.

CONCLUSIONS

Use of amphetamine and cannabis are risk markers for schizophrenia readmission among patients with a history of schizophrenia and DUD. Psychiatric history is a predictor of schizophrenia readmission in this patient group.

Is It Possible to Predict the Future in First-Episode Psychosis?

The outcome of first-episode psychosis (FEP) is highly variable, ranging from early sustained recovery to antipsychotic treatment resistance from the onset of illness. For clinicians, a possibility to predict patient outcomes would be highly valuable for the selection of antipsychotic treatment and in tailoring psychosocial treatments and psychoeducation. This selective review summarizes current knowledge of prognostic markers in FEP. We sought potential outcome predictors from clinical and sociodemographic factors, cognition, brain imaging, genetics, and blood-based biomarkers, and we considered different outcomes, like remission, recovery, physical comorbidities, and suicide risk. Based on the review, it is currently possible to predict the future for FEP patients to some extent. Some clinical features-like the longer duration of untreated psychosis (DUP), poor premorbid adjustment, the insidious mode of onset, the greater severity of negative symptoms, comorbid substance use disorders (SUDs), a history of suicide attempts and suicidal ideation and having non-affective psychosis-are associated with a worse outcome. Of the social and demographic factors, male gender, social disadvantage, neighborhood deprivation, dysfunctional family environment, and ethnicity may be relevant. Treatment non-adherence is a substantial risk factor for relapse, but a small minority of patients with acute onset of FEP and early remission may benefit from antipsychotic discontinuation. Cognitive functioning is associated with functional outcomes. Brain imaging currently has limited utility as an outcome predictor, but this may change with methodological advancements. Polygenic risk scores (PRSs) might be useful as one component of a predictive tool, and pharmacogenetic testing is already available and valuable for patients who have problems in treatment response or with side effects. Most blood-based biomarkers need further validation. None of the currently available predictive markers has adequate sensitivity or specificity used alone. However, personalized treatment of FEP will need predictive tools. We discuss some methodologies, such as machine learning (ML), and tools that could lead to the improved prediction and clinical utility of different prognostic markers in FEP. Combination of different markers in ML models with a user friendly interface, or novel findings from e.g., molecular genetics or neuroimaging, may result in computer-assisted clinical applications in the near future.

The Group of Treatment Resistant Schizophrenias. Heterogeneity in Treatment Resistant Schizophrenia (TRS)

Schizophrenia is composed of a heterogeneous group of patient segments. Our current notion of the heterogeneity in schizophrenia is based on patients presenting with diverse disease symptom phenotypes, risk factors, structural and functional neuropathology, and a mixed range of expressed response to treatment. It is important for clinicians to recognize the various clinical presentations of resistance to treatment in schizophrenia and to understand how heterogeneity across treatment resistant patient segments may potentially inform new strategies for the development of effective treatments for Treatment Resistant Schizophrenia (TRS). The heterogeneity of schizophrenia may be reduced by parsing patient segments based on whether patients demonstrate an adequate or inadequate response to treatment. In our current concept of TRS, TRS is defined as non-response to at least two adequate trials of antipsychotic medication and is estimated to affect about 30% of all patients with schizophrenia. In this narrative review, the author discusses that the demonstration of inadequate response to antipsychotic drugs (APDs) may infer that some TRS patients may be suffering from a non-dopamine pathophysiology since D2 receptor antagonist-based treatment is ineffective. Preliminary neurobiological findings may further support the pathophysiologic distinction of TRS from that of general schizophrenia. Investigation of the basis for heterogeneity in TRS through the systematic investigation of relevant "clusters" of similarly at risk individuals may hopefully bring us closer to realize a precision medicine approach for developing effective therapies for TRS patient segments.