Preventive Treatments for Psychosis: Umbrella Review (Just the Evidence)

Abstract

Background: Indicated primary prevention in young people at Clinical High Risk for Psychosis (CHR-P) is a promising avenue for improving outcomes of one of the most severe mental disorders but their effectiveness has recently been questioned. Methods: Umbrella review. A multi-step independent literature search of Web of Science until January 11, 2019, identified interventional meta-analyses in CHR-P individuals. The individual randomised controlled trials that were analysed by the meta-analyses were extracted. A review of ongoing trials and a simulation of living meta-analysis complemented the analysis. Results: Seven meta-analyses investigating preventive treatments in CHR-P individuals were included. None of them produced pooled effect sizes across psychological, pharmacological, or other types of interventions. The outcomes analysed encompassed risk of psychosis onset, the acceptability of treatments, the severity of attenuated positive/negative psychotic symptoms, depression, symptom-related distress, social functioning, general functioning, and quality of life. These meta-analyses were based on 20 randomised controlled trials: the vast majority defined the prevention of psychosis onset as their primary outcome of interest and only powered to large effect sizes. There was no evidence to favour any preventive intervention over any other (or control condition) for improving any of these clinical outcomes. Caution is required when making clinical recommendations for the prevention of psychosis in individuals at risk. Discussion: Prevention of psychosis from a CHR-P state has been, and should remain, the primary outcome of interventional research, refined and complemented by other clinically meaningful outcomes. Stagnation of knowledge should promote innovative and collaborative research efforts, in line with the progressive and incremental nature of medical knowledge. Advancements will most likely be associated with the development of new experimental therapeutics that are ongoing along with the ability to deconstruct the high heterogeneity within CHR-P populations. This would require the estimation of treatment-specific effect sizes through living individual participant data meta-analyses, controlling risk enrichment during recruitment, statistical power, and embedding precision medicine within youth mental health services that can accommodate sequential prognosis and advanced trial designs. Conclusions: The evidence-based challenges and proposed solutions addressed by this umbrella review can inform the next generation of research into preventive treatments for psychosis.

Keywords: evidence; meta-analysis; prevention; psychosis; schizophrenia; treatments.

Figure 1

The hype cycle of preventive treatments for psychosis.

Figure 2

Living meta-analyses. Current (inner circle) and emerging (outer circle) evidence-based health knowledge ecosystems. The current health knowledge ecosystem is characterized by inefficiencies that hamper the flow of knowledge from health practice through primary research, evidence synthesis and guidelines, and finally back to impacts on health practice. The emerging health knowledge ecosystem is characterized by a continuous flow of knowledge between living components, including the growing importance of learning health care systems (a dynamic system which is continuously learning from new data), which together with traditional primary research will populate common data repositories. Living evidence services derived from these repositories, supporting living guidance and decision support systems will close a ‘‘living’’ health knowledge loop. Adapted from (41).

Figure 3

Study identification and selection (PRISMA flowchart).

Figure 4

Example of sequential meta-analysis testing the preventive efficacy of CBT in CHR-P individuals. Plotted are the Randomized Controlled Trials of CBT vs Needs Based Intervention (NBI) in CHR-P patients that reported risk of psychosis onset at 6-month (part A) and 12 months (part B). The blue line represents the Z-value of each interim meta-analysis, the green line indicates the statistical significance threshold and the dotted red line the monitoring boundary. The red vertical line represents the a priori information size (APIS), i.e., the required sample size to detect a Relative Risk Reduction (RRR) = 0.5 with statistical power 0.9 on the risk of psychosis. Estimated using the package metacumbounds (101) and the previously published meta-analytical results (30).

Figure 5

Clinical Stratification of Pretest Risk Enrichment in Individuals undergoing a Clinical High Risk assessment (102).