Background: Subjects at ultra high-risk (UHR) for psychosis have an enhanced vulnerability to develop the disorder but the risk factors accounting for this accrued risk are undetermined.Method: Systematic review of associations between genetic or environmental risk factors for psychosis that are widely established in the literature and UHR state, based on comparisons to controls.Results: Forty-four studies encompassing 170 independent datasets and 54 risk factors were included. There were no studies on association between genetic or epigenetic risk factors and the UHR state that met the inclusion criteria. UHR subjects were more likely to show obstetric complications, tobacco use, physical inactivity, childhood trauma/emotional abuse/physical neglect, high perceived stress, childhood and adolescent low functioning, affective comorbidities, male gender, single status, unemployment and low educational level as compared to controls.Conclusions: The increased vulnerability of UHR subjects can be related to environmental risk factors like childhood trauma, adverse life events and affective dysfunction. The role of genetic and epigenetic risk factors awaits clarification.

The impact of precision psychiatry for clinical practice has not been systematically appraised. This study aims to provide a comprehensive review of validated prediction models to estimate the individual risk of being affected with a condition (diagnostic), developing outcomes (prognostic), or responding to treatments (predictive) in mental disorders. PRISMA/RIGHT/CHARMS-compliant systematic review of the Web of Science, Cochrane Central Register of Reviews, and Ovid/PsycINFO databases from inception until July 21, 2019 (PROSPERO CRD42019155713) to identify diagnostic/prognostic/predictive prediction studies that reported individualized estimates in psychiatry and that were internally or externally validated or implemented. Random effect meta-regression analyses addressed the impact of several factors on the accuracy of prediction models. Literature search identified 584 prediction modeling studies, of which 89 were included. 10.4% of the total studies included prediction models internally validated (n = 61), 4.6% models externally validated (n = 27), and 0.2% (n = 1) models considered for implementation. Across validated prediction modeling studies (n = 88), 18.2% were diagnostic, 68.2% prognostic, and 13.6% predictive. The most frequently investigated condition was psychosis (36.4%), and the most frequently employed predictors clinical (69.5%). Unimodal compared to multimodal models (β = .29, P = .03) and diagnostic compared to prognostic (β = .84, p < .0001) and predictive (β = .87, P = .002) models were associated with increased accuracy. To date, several validated prediction models are available to support the diagnosis and prognosis of psychiatric conditions, in particular, psychosis, or to predict treatment response. Advancements of knowledge are limited by the lack of implementation research in real-world clinical practice. A new generation of implementation research is required to address this translational gap.

Twenty percent of individuals at clinical high risk for psychosis (CHR-P) develop the disorder within 2 years. Extensive research has explored the factors that differentiate those who develop psychosis and those who do not, but the results are conflicting.The current systematic review and meta-analysis comprehensively addresses the consistency and magnitude of evidence for non-purely genetic risk and protective factors associated with the risk of developing psychosis in CHR-P individuals. Random effects meta-analyses, standardized mean difference (SMD) and odds ratio (OR) were used, in combination with an established stratification of evidence that assesses the association of each factor and the onset of psychotic disorders (from class I, convincing evidence to class IV weak evidence), while controlling for several types of biases.A total of 128 original controlled studies relating to 26 factors were retrieved. No factors showed class I-convincing evidence. Two further factors were associated with class II-highly suggestive evidence: attenuated positive psychotic symptoms (SMD = 0.348, 95% CI: 0.280, 0.415) and global functioning (SMD = −0.291, 95% CI: −0.370, −0.211). There was class III-suggestive evidence for negative psychotic symptoms (SMD = 0.393, 95% CI: 0.317, 0.469). There was either class IV-weak or no evidence for all other factors.Our findings suggest that despite the large number of putative risk factors investigated in the literature, only attenuated positive psychotic symptoms, global functioning, and negative psychotic symptoms show suggestive evidence or greater for association with transition to psychosis. The current findings may inform the refinement of clinical prediction models and precision medicine in this field.

Reduction of duration of untreated psychosis (DUP) is the key strategy of early interventions for improving the outcomes of first-episode psychosis. Although several controlled interventional studies have been conducted with the aim of reducing DUP, the results are highly inconsistent and conflicting. The current study systematically searches Web of Science and Ovid for English original articles investigating interventions adopted to reduce DUP, compared to a control intervention, up to April 6, 2017. Sixteen controlled interventional studies were retrieved, including 1964 patients in the intervention arm and 1358 in the control arm. The controlled intervention studies were characterized by standalone first episode psychosis services, standalone clinical high risk services, community interventions, healthcare professional training, and multifocus interventions. Random effects meta-analyses were conducted. There was no summary evidence that available interventions are successful in reducing DUP during the first episode of psychosis (Hedges’ g = −0.12, 95% CI = −0.25 to 0.01). Subgroup analyses showed no differences within each subgroup, with the exception of clinical high risk services (Hedges’ g = −0.386, 95% CI = −0.726 to −0.045). These negative findings may reflect a parceled research base in the area, lack of prospective randomized controlled trials (only 2 randomized cluster designed studies were present) and small sample sizes. There was substantial heterogeneity (I² = 66.4%), most of which was accounted by different definitions of DUP onset (R² = .88). Psychometric standardization of DUP definition, improvement of study design, and implementation of preventative strategies seem the most promising avenues for reducing DUP and improving outcomes of first-episode psychosis.