Research from JAMA Psychiatry — Heterogeneity of Psychosis Risk Within Individuals at Clinical High Risk — A Meta-analytical Stratification

Existing treatments for psychotic disorders have little effect on the course of illness within standard care.^1,2 Prevention and early intervention may be the only available clinical possibility to alter the course of psychosis.³ Prevention of psychosis has been feasible since the introduction of the At Risk Mental State (ARMS) construct 2 decades ago.⁴ The ARMS construct has been validated internationally,^5-7 and it can reliably identify young individuals at specific enhanced risk for the development of psychotic disorders,⁸ mostly schizophrenia spectrum disorders,⁹ but not of nonpsychotic disorders,^10,11 during the 2 to 3 years after initial assessment.¹² Randomized clinical trials have shown that focused interventions, if offered to ARMS individuals, can effectively reduce the risk of future illness.^13,14 Owing to these unprecedented potentials, the ARMS construct has gained traction to the point that specialized assessment and treatment is recognized as a key component of secondary mental health services by National Institute for Health and Care Excellence guidelines.¹⁵

Validity of current International Classification of Disease/Diagnostic and Statistical Manual of Mental Disorders (ICD/DSM) first episode psychosis diagnoses is essential in clinical practice, research, training and public health. We provide a meta-analytical estimate of prospective diagnostic stability and instability in ICD-10 or DSM-IV first episode diagnoses of functional psychoses. Independent extraction by multiple observers. Random effect meta-analysis conducted with the “metaprop,” “metaninf,” “metafunnel,” “metabias,” and “metareg” packages of STATA13.1. Moderators were tested with meta-regression analyses. Heterogeneity was assessed with the I² index. Sensitivity analyses tested robustness of results. Publication biases were assessed with funnel plots and Egger’s test. 42 studies and 45 samples were included, for a total of 14 484 first episode patients and an average follow-up of 4.5 years. Prospective diagnostic stability ranked: schizophrenia 0.90 (95% CI 0.85–0.95), affective spectrum psychoses 0.84 (95% CI 0.79–0.89), schizoaffective disorder 0.72 (95% CI 0.61–0.73), substance-induced psychotic disorder 0.66 (95% CI 0.51–0.81), delusional disorder 0.59 (95% CI 0.47–0.71), acute and transient psychotic disorder/brief psychotic disorder 0.56 (95% CI 0.62–0.60), psychosis not otherwise specified 0.36 (95% CI 0.27–0.45, schizophreniform disorder 0.29 (95% CI 0.22–0.38). Diagnostic stability within schizophrenia spectrum psychoses was 0.93 (95% CI 0.89–0.97); changes to affective spectrum psychoses were 0.05 (95% CI 0.01–0.08). About 0.10 (95% CI 0.05–0.15) of affective spectrum psychoses changed to schizophrenia spectrum psychosis. Across the other psychotic diagnoses there was high diagnostic instability, mostly to schizophrenia. There is meta-analytical evidence for high prospective diagnostic stability in schizophrenia spectrum and affective spectrum psychoses, with no significant ICD/DSM differences. These results may inform the development of new treatment guidelines for early psychosis and impact drug licensing from regulatory agencies.

The individual risk of developing psychosis after being tested for clinical high-risk (CHR) criteria (posttest risk of psychosis) depends on the underlying risk of the disease of the population from which the person is selected (pretest risk of psychosis), and thus on recruitment strategies. Yet, the impact of recruitment strategies on pretest risk of psychosis is unknown. Meta-analysis of the pretest risk of psychosis in help-seeking patients selected to undergo CHR assessment: total transitions to psychosis over the pool of patients assessed for potential risk and deemed at risk (CHR+) or not at risk (CHR−). Recruitment strategies (number of outreach activities per study, main target of outreach campaign, and proportion of self-referrals) were the moderators examined in meta-regressions. 11 independent studies met the inclusion criteria, for a total of 2519 (CHR+: n = 1359; CHR−: n = 1160) help-seeking patients undergoing CHR assessment (mean follow-up: 38 months). The overall meta-analytical pretest risk for psychosis in help-seeking patients was 15%, with high heterogeneity (95% CI: 9%–24%, I² = 96, P < .001). Recruitment strategies were heterogeneous and opportunistic. Heterogeneity was largely explained by intensive ( n = 11, β = −.166, Q = 9.441, P = .002) outreach campaigns primarily targeting the general public ( n = 11, β = −1.15, Q = 21.35, P < .001) along with higher proportions of self-referrals ( n = 10, β = −.029, Q = 4.262, P = .039), which diluted pretest risk for psychosis in patients undergoing CHR assessment. There is meta-analytical evidence for overall risk enrichment (pretest risk for psychosis at 38monhts = 15%) in help-seeking samples selected for CHR assessment as compared to the general population (pretest risk of psychosis at 38monhts=0.1%). Intensive outreach campaigns predominantly targeting the general population and a higher proportion of self-referrals diluted the pretest risk for psychosis.

Major depression is associated with a 4-fold increased risk for premature death, largely accounted by cardiovascular disease (CVD). The relationship between depression and CVD is thought to be mediated by the so-called metabolic syndrome (MeS). Epidemiological studies have consistently demonstrated a co-occurrence of depression with MeS components, ie, visceral obesity, dyslipidemia, insulin resistance, and hypertension. Although the exact mechanisms linking MeS to depression are unclear, different hypotheses have been put forward. On the one hand, MeS could be the hallmark of the unhealthy lifestyle habits of depressed patients. On the other, MeS and depression might share common alterations of the stress system, including the hypothalamus–pituitary–adrenal (HPA) axis, the autonomic nervous system, the immune system, and platelet and endothelial function. Both the conditions induce a low grade chronic inflammatory state that, in turn, leads to increased oxidative and nitrosative (O&NS) damage of neurons, pancreatic cells, and endothelium. Recently, neurobiological research revealed that peripheral hormones, such as leptin and ghrelin, which are classically involved in homeostatic energy balance, may play a role in mood regulation. Metabolic risk should be routinely assessed in depressed patients and taken into account in therapeutic decisions. Alternative targets should be considered for innovative antidepressant agents, including cytokines and their receptors, intracellular inflammatory mediators, glucocorticoids receptors, O&NS pathways, and peripheral mediators.