Why ultra high risk criteria for psychosis prediction do not work well outside clinical samples and what to do about it

Gene Polymorphisms and Expression of NRG1, DAOA, and DISC1 Genes in a Chinese Han Population with an Ultra-High Risk for Psychosis

Purpose

Although there is previous evidence supporting that ultra-high risk (UHR) for psychosis transformation is associated with NRG1, DAOA, and DISC1 genes, there have been no relevant studies in the Chinese population. The objective of the current study was to explore the gene polymorphism and expression of NRG1, DAOA, and DISC1 genes in a Han population with UHR for psychosis in China.

Methods

Eighteen UHR individuals, 61 first-degree relatives of patients with schizophrenia (FDR), 55 first-episode psychosis individuals (FEP), and 61 healthy controls (HC) were enrolled in the study. The genotypes at four loci of the NRG1 gene, four loci of the DAOA gene, and two loci of the DISC1 gene were tested for all subjects, and mRNAs of NRG1 and DISC1 were examined and analyzed in a pairwise comparison among the four groups. Statistical analysis of genetics was performed using snpStats software. For the case-control association analysis, a single site association study, epistatic effect analysis, and haplotype analysis were used to explore the association of the above genes.

Results

This study found that rs3918341 in the DAOA gene was associated with susceptibility to UHR by single site association analysis. Epistatic effect analysis results showed that the NRG1 gene interacted with the DAOA gene and DISC1 gene in the susceptibility to UHR. Haplotype association analysis showed that all haplotypes were not significantly associated with UHR. NRG1 mRNA was significantly downregulated in the UHR group compared with the HC group as well as the FEP group.

Conclusion

Our preliminary results show that NRG1, DAOA, and DISC1 genes may play a role in psychosis onset, opening the way to the identification of prognostic biomarkers.

Depressive symptom screening and endorsement of psychosis risk-related experiences in a diverse adolescent and young adult outpatient clinic in the US

BACKGROUND

Early identification and intervention is a gold standard for psychotic disorders, for which delays in care can have serious consequences. Screening for psychosis in primary care may circumvent barriers related to stigma and facilitate shorter pathways to care. Yet, there is debate regarding the benefit-risk balance for psychosis screening in general adolescent populations.

METHODS

Primary care patients of an adolescent/young adult medical clinic in the US ages 14-21 self-administered surveys assessing age, sex, receipt of psychotherapy, and occurrence, frequency (1-5), and distress (0-3) for 23 psychosis risk (PR) symptoms, including 6 general/nonspecific items and 17 psychosis-specific items. Participants also completed the 9-item Patient Health Questionnaire (PHQ-9); scores of ≥10 suggested clinically significant depressive symptoms. Analyses characterized PR symptoms and examined associations of PR symptom distress with current therapy and depressive symptom severity.

RESULTS

Of 212 patients who completed the survey, 75% endorsed ≥1 PR symptom and 27% rated ≥3 on distress for psychosis-specific items. Those with high PHQ-9 scores reported higher PR distress overall (t = -6.1, df = 52.3, p < 0.001) but not on psychosis-specific items such as hallucinations and suspiciousness. One in 9 participants reported heightened PR distress without being in therapy or having high depressive symptoms.

CONCLUSIONS

Most adolescents in this primary care sample endorsed symptoms associated with PR. Distress related to these symptoms was less common but occurred even in the absence of depressive symptoms. PR screening only in youth with high depressive symptom screens or in mental health care may miss youth needing further assessment for psychosis.

Differential contributions between objective and subjective psychosis-like experiences to suicidal ideation in college students

AIM

The present study aimed to investigate the prevalence rate of objective and subjective psychosis-like experiences (PLEs) in non-help-seeking college students and to explore their differential contributions to suicidal ideation.

METHODS

First-year college students were recruited and surveyed with the Chinese version of the 16-item Prodromal Questionnaire (CPQ-16), Childhood Trauma Questionnaire (CTQ-SF), Patient Health Questionnaire-9 (PHQ-9), General Anxiety Disorder-7 (GAD-7) and Beck Scale for Suicide Ideation (BSI). The Structured Interview of Psychosis-Risk Syndromes (SIPS) was conducted in individuals with a CPQ-16 score of 9 or higher.

RESULTS

Data were available for 8367 students. Three hundred and seventy of them scored 9 or higher on the CPQ-16, suggesting potential PLEs (4.42%). Among them, 194 agreed to the SIPS screening. The PLEs were confirmed in 103 individuals who scored 1-5 on any positive symptom scales of the SIPS (objective PLEs, oPLEs). For the remaining 91 individuals, their PLEs were not confirmed by the SIPS and thus were categorized as individuals with subjective PLEs (sPLEs). In univariate logistic regression, oPLEs was associated with a two times risk of suicidal ideation compared to sPLEs (OR = 1.971, p = .029). In multivariate logistic regression when non-PLE status was set as a reference, oPLEs significantly predicted suicidal ideation (OR = 3.441, p = .011), while the sPLEs (OR = 2.277, p = .091) was no longer a significant predictor after controlling for PHQ-9, GAD-7 and CPQ-SF scores.

CONCLUSIONS

OPLEs and sPLEs have differential contributions to suicidal ideation. OPLEs seems to be associated with a higher risk of suicidal ideation and is independent of other psychopathology.

Prognostic accuracy and clinical utility of psychometric instruments for individuals at clinical high-risk of psychosis: a systematic review and meta-analysis

Accurate prognostication of individuals at clinical high-risk for psychosis (CHR-P) is an essential initial step for effective primary indicated prevention. We aimed to summarise the prognostic accuracy and clinical utility of CHR-P assessments for primary indicated psychosis prevention. Web of Knowledge databases were searched until 1st January 2022 for longitudinal studies following-up individuals undergoing a psychometric or diagnostic CHR-P assessment, reporting transition to psychotic disorders in both those who meet CHR-P criteria (CHR-P + ) or not (CHR-P-). Prognostic accuracy meta-analysis was conducted following relevant guidelines. Primary outcome was prognostic accuracy, indexed by area-under-the-curve (AUC), sensitivity and specificity, estimated by the number of true positives, false positives, false negatives and true negatives at the longest available follow-up time. Clinical utility analyses included: likelihood ratios, Fagan's nomogram, and population-level preventive capacity (Population Attributable Fraction, PAF). A total of 22 studies (n = 4 966, 47.5% female, age range 12-40) were included. There were not enough meta-analysable studies on CHR-P diagnostic criteria (DSM-5 Attenuated Psychosis Syndrome) or non-clinical samples. Prognostic accuracy of CHR-P psychometric instruments in clinical samples (individuals referred to CHR-P services or diagnosed with 22q.11.2 deletion syndrome) was excellent: AUC = 0.85 (95% CI: 0.81-0.88) at a mean follow-up time of 34 months. This result was driven by outstanding sensitivity (0.93, 95% CI: 0.87-0.96) and poor specificity (0.58, 95% CI: 0.50-0.66). Being CHR-P + was associated with a small likelihood ratio LR + (2.17, 95% CI: 1.81-2.60) for developing psychosis. Being CHR-P- was associated with a large LR- (0.11, 95%CI: 0.06-0.21) for developing psychosis. Fagan's nomogram indicated a low positive (0.0017%) and negative (0.0001%) post-test risk in non-clinical general population samples. The PAF of the CHR-P state is 10.9% (95% CI: 4.1-25.5%). These findings consolidate the use of psychometric instruments for CHR-P in clinical samples for primary indicated prevention of psychosis. Future research should improve the ability to rule in psychosis risk.

Neural Correlates of Facial Emotion Recognition in Non-help-seeking University Students With Ultra-High Risk for Psychosis

Background

Since the introduction of the neurodevelopmental perspective of schizophrenia research on individuals at ultra-high risk for psychosis (UHR) has gained increasing interest, aiming at early detection and intervention. Results from fMRI studies investigating behavioral and brain functional changes in UHR during facial emotion recognition, an essential component of social cognition, showed heterogenous results, probably due clinical diversity across these investigations. This fMRI study investigated emotion recognition in a sub-group of the UHR spectrum, namely non-help-seeking, drug-naïve UHR with high cognitive functioning to reveal the neurofunctional underpinnings of their social functioning in comparison to healthy controls.

Methods

Two large cohorts of students from an elite University (n 1 = 4,040, n 2 = 4,364) were screened firstly with the Prodromal Questionnaires and by surpassing predefined cut-offs then interviewed with the semi-structured Interview for Psychosis-Risk Syndromes to verify their UHR status. Twenty-one identified non-help-seeking UHR and 23 non-UHR control subjects were scanned with functional magnetic resonance imaging while classifying emotions (i.e., neutral, happy, disgust and fear) in a facial emotion recognition task.

Results

Behaviorally, no group differences were found concerning accuracy, reaction times, sensitivity or specificity, except that non-help-seeking UHR showed higher specificity when recognizing neutral facial expressions. In comparison to healthy non-UHR controls, non-help-seeking UHR showed generally higher activation in the superior temporal and left Heschl's gyrus as well as in the somatosensory, insular and midcingulate cortex than the control subjects during the entire recognition task regardless of the emotion categories. In an exploratory analysis, in the non-help-seeking UHR group, functional activity in the left superior temporal gyrus was significantly correlated with deficits in the ability to experience emotions at uncorrected statistical thresholds.

Conclusions

Compared to healthy controls, non-help-seeking UHR show no behavioral deficits during facial emotion recognition, but functional hyperactivities in brain regions associated with this cognitive process. Our study may inspire future early intervention and provide loci for treatment using neural stimulation.

Turkish Version of Structured Interview of Psychosis-Risk Syndromes (SIPS) and Proposal of a Brief Version of SIPS as a Pretest Risk Enrichment

Introduction

The Structured Interview of Psychosis Risk Syndromes (SIPS) was created to identify patients with Clinical High Risk for psychosis (CHR). This study aimed i) to translate and validate the Scale of Prodromal Syndromes (SOPS) in Turkish adolescents, ii) to explore the factor structure of the SIPS/SOPS in the adolescent population, especially focusing on those under the age of 15, iii) to generate a brief version of SIPS (SIPS-B).

Methods

A total of 150 adolescents aged between 12 and 18 years, were consecutively interviewed using SIPS/SOPS. Patients with psychotic syndrome (n=20), psychosis risk syndrome (PRS) (n=59), and clinical controls (CC) (n=71) were included in the study.

Results

Principal component analysis (PCA) yielded three latent factors, explaining 62.7% of the total variance in the whole clinical sample, including positive symptom factor, disorganized symptom factor, and negative symptom factor. The area under curve calculated in ROC analyses involving PRS and CC supported the four-item form of the SIPS-B (optimal cut-off=12.5, sensitivity=87%, specificity=80%).

Conclusion

Our study results support the notion that the Turkish translation of SIPS/SOPS meets the reliability and validity criteria in Turkish adolescents. The SIPS-B could aid clinicians in their routine clinical practice to expedite referral procedures.

ITAlian partnership for psychosis prevention (ITAPP): Improving the mental health of young people

Background

The European impact of the clinical high risk for psychosis (CHR-P) paradigm is constrained by the lack of critical mass (detection) to power prognostic and preventive interventions.

Methods

An ITAlian partnership for psychosis prevention (ITAPP) was created across CHR-P centers, which were surveyed to describe: (a) service, catchment area, and outreach; (b) service users; and (c) interventions and outcomes. Descriptive statistics and Kaplan–Meier failure function complemented the analyses.

Results

The ITAPP included five CHR-P clinical academic centers established from 2007 to 2018, serving about 13 million inhabitants, with a recruitment capacity of 277 CHR-P individuals (mean age: 18.7 years, SD: 4.8, range: 12–39 years; 53.1% females; 85.7% meeting attenuated psychotic symptoms; 85.8% without any substance abuse). All centers were multidisciplinary and included adolescents and young adults (transitional) primarily recruited through healthcare services. The comprehensive assessment of at-risk mental state was the most widely used instrument, while the duration of follow-up, type of outreach, and preventive interventions were heterogeneous. Across 205 CHR-P individuals with follow up (663.7 days ± 551.7), the cumulative risk of psychosis increased from 8.7% (95% CI 5.3–14.1) at 1 year to 15.9% (95% CI 10.6–23.3) at 2 years, 21.8% (95% CI 14.9–31.3) at 3 years, 34.8% (95% CI 24.5–47.9) at 4 years, and 51.9% (95% CI 36.3–69.6) at 5 years.

Conclusions

The ITAPP is one of the few CHR-P clinical research partnerships in Europe for fostering detection, prognosis, and preventive care, as well as for translating research innovations into practice.

Preventive psychiatry: a blueprint for improving the mental health of young people

Preventive approaches have latterly gained traction for improving mental health in young people. In this paper, we first appraise the conceptual foundations of preventive psychiatry, encompassing the public health, Gordon's, US Institute of Medicine, World Health Organization, and good mental health frameworks, and neurodevelopmentally-sensitive clinical staging models. We then review the evidence supporting primary prevention of psychotic, bipolar and common mental disorders and promotion of good mental health as potential transformative strategies to reduce the incidence of these disorders in young people. Within indicated approaches, the clinical high-risk for psychosis paradigm has received the most empirical validation, while clinical high-risk states for bipolar and common mental disorders are increasingly becoming a focus of attention. Selective approaches have mostly targeted familial vulnerability and non-genetic risk exposures. Selective screening and psychological/psychoeducational interventions in vulnerable subgroups may improve anxiety/depressive symptoms, but their efficacy in reducing the incidence of psychotic/bipolar/common mental disorders is unproven. Selective physical exercise may reduce the incidence of anxiety disorders. Universal psychological/psychoeducational interventions may improve anxiety symptoms but not prevent depressive/anxiety disorders, while universal physical exercise may reduce the incidence of anxiety disorders. Universal public health approaches targeting school climate or social determinants (demographic, economic, neighbourhood, environmental, social/cultural) of mental disorders hold the greatest potential for reducing the risk profile of the population as a whole. The approach to promotion of good mental health is currently fragmented. We leverage the knowledge gained from the review to develop a blueprint for future research and practice of preventive psychiatry in young people: integrating universal and targeted frameworks; advancing multivariable, transdiagnostic, multi-endpoint epidemiological knowledge; synergically preventing common and infrequent mental disorders; preventing physical and mental health burden together; implementing stratified/personalized prognosis; establishing evidence-based preventive interventions; developing an ethical framework, improving prevention through education/training; consolidating the cost-effectiveness of preventive psychiatry; and decreasing inequalities. These goals can only be achieved through an urgent individual, societal, and global level response, which promotes a vigorous collaboration across scientific, health care, societal and governmental sectors for implementing preventive psychiatry, as much is at stake for young people with or at risk for emerging mental disorders.

Worldwide implementation of clinical services for the prevention of psychosis: The IEPA early intervention in mental health survey

BACKGROUND

Clinical research into the Clinical High Risk state for Psychosis (CHR-P) has allowed primary indicated prevention in psychiatry to improve outcomes of psychotic disorders. The strategic component of this approach is the implementation of clinical services to detect and take care of CHR-P individuals, which are recommended by several guidelines. The actual level of implementation of CHR-P services worldwide is not completely clear.

AIM

To assess the global geographical distribution, core characteristics relating to the level of implementation of CHR-P services; to overview of the main barriers that limit their implementation at scale.

METHODS

CHR-P services worldwide were invited to complete an online survey. The survey addressed the geographical distribution, general implementation characteristics and implementation barriers.

RESULTS

The survey was completed by 47 CHR-P services offering care to 22 248 CHR-P individuals: Western Europe (51.1%), North America (17.0%), East Asia (17.0%), Australia (6.4%), South America (6.4%) and Africa (2.1%). Their implementation characteristics included heterogeneous clinical settings, assessment instruments and length of care offered. Most CHR-P patients were recruited through mental or physical health services. Preventive interventions included clinical monitoring and crisis management (80.1%), supportive therapy (70.2%) or structured psychotherapy (61.7%), in combination with pharmacological treatment (in 74.5%). Core implementation barriers were staffing and financial constraints, and the recruitment of CHR-P individuals. The dynamic map of CHR-P services has been implemented on the IEPA website: https://iepa.org.au/list-a-service/.

CONCLUSIONS

Worldwide primary indicated prevention of psychosis in CHR-P individuals is possible, but the implementation of CHR-P services is heterogeneous and constrained by pragmatic challenges.

Outreach and support in South-London (OASIS) 2001-2020: Twenty years of early detection, prognosis and preventive care for young people at risk of psychosis

This study aims to describe twenty years of early detection, prognosis and preventive care in the Outreach and Support In South-London (OASIS) mental health service for individuals at Clinical High risk of psychosis (CHR-P). The study presents a comprehensive analysis of the 2001- 2020 activity of the OASIS team encompassing core domains: (i) service characteristics, (ii) detection, (iii) prognosis, (iv) treatment and (v) clinical research. The analyses employed descriptive statistics, population-level data, the epidemiological incidence of psychosis, Kaplan Meier failure functions and Greenwood 95% CIs and Electronic Health Records. OASIS is part of the South London and Maudsley (SLaM) NHS trust, the largest European mental health provider, serving a total urban population of 1,358,646 individuals (population aged 16-35: 454,525). Incidence of psychosis in OASIS's catchment area ranges from 58.3 to 71.9 cases per 100,000 person-years, and it is higher than the national average of 41.5 cases per 100,000 person-year. OASIS is a standalone, NHS-funded, multidisciplinary (team leader, consultant and junior psychiatrists, clinical psychologists, mental health professionals), transitional (for those aged 14-35 years) community mental health service with a yearly caseload of 140 CHR-P individuals. OASIS regularly delivers a comprehensive service promotion outreach to several local community organisations. Referrals to OASIS (2366) are made by numerous agencies; about one-third of the referrals eventually met CHR-P criteria. Overall, 600 CHR-P individuals (55.33% males, mean age 22.63 years, white ethnicity 46.44%) have been under the care of the OASIS service: 80.43% met attenuated psychotic symptoms, 18.06% brief and limited intermittent psychotic symptoms and 1.51% genetic risk and deterioration CHR-P criteria. All CHR-P individuals were offered cognitive behavioural therapy and psychosocial support; medications were used depending on individual needs. The cumulative risk of psychosis at ten years was 0.365 (95%CI 0.302-0.437). At six years follow-up, across two-third of individuals non-transitioning to psychosis, 79.24% still displayed some mental health problem, and only 20.75% achieved a complete clinical remission. Research conducted at OASIS encompassed clinical, prognostic, neurobiological and interventional studies and leveraged local, national and international infrastructures; over the past ten years, OASIS-related research attracted about £ 50 million of grant income, with 5,922 citations in the international databases. Future developments may include broadening OASIS to prevent other serious mental disorders beyond psychosis and fostering translational risk prediction and interventional research. With a twenty-years activity, OASIS' cutting-edge quality of preventive care, combined with translational research innovations, consolidated the service as a leading reference model for evidence-based prevention of psychosis worldwide.

Individualized Diagnostic and Prognostic Models for Patients With Psychosis Risk Syndromes: A Meta-analytic View on the State of the Art

BACKGROUND

The clinical high risk (CHR) paradigm has facilitated research into the underpinnings of help-seeking individuals at risk for developing psychosis, aiming at predicting and possibly preventing transition to the overt disorder. Statistical methods such as machine learning and Cox regression have provided the methodological basis for this research by enabling the construction of diagnostic models (i.e., distinguishing CHR individuals from healthy individuals) and prognostic models (i.e., predicting a future outcome) based on different data modalities, including clinical, neurocognitive, and neurobiological data. However, their translation to clinical practice is still hindered by the high heterogeneity of both CHR populations and methodologies applied.

METHODS

We systematically reviewed the literature on diagnostic and prognostic models built on Cox regression and machine learning. Furthermore, we conducted a meta-analysis on prediction performances investigating heterogeneity of methodological approaches and data modality.

RESULTS

A total of 44 articles were included, covering 3707 individuals for prognostic studies and 1052 individuals for diagnostic studies (572 CHR patients and 480 healthy control subjects). CHR patients could be classified against healthy control subjects with 78% sensitivity and 77% specificity. Across prognostic models, sensitivity reached 67% and specificity reached 78%. Machine learning models outperformed those applying Cox regression by 10% sensitivity. There was a publication bias for prognostic studies yet no other moderator effects.

CONCLUSIONS

Our results may be driven by substantial clinical and methodological heterogeneity currently affecting several aspects of the CHR field and limiting the clinical implementability of the proposed models. We discuss conceptual and methodological harmonization strategies to facilitate more reliable and generalizable models for future clinical practice.

Sex differences in symptomatology of psychosis-risk patients and in prediction of psychosis

Sex differences may be important for understanding underlying pathophysiological mechanisms and developing effective preventions and treatments of mental disorders. Despite sex differences in the onset of psychosis, patients at clinical high risk for psychosis (CHR) are underinvestigated for sex effects, especially with respect to models for prediction of conversion to psychosis. We studied psychopathological sex differences in referrals to a German early detection service and in its subgroup of converters and examined sex-specific psychopathological prediction models. In 152 male and 90 female referrals (88% at CHR; 35% converters), symptoms assessed with the Structured Interview for Psychosis-Risk Syndromes were investigated for sex differences using effect sizes. Sex-specific prediction models of psychosis were separately generated using Cox regressions with a LASSO operator. We found different small sex effects (0.10 < Rosenthal's r < 0.30) in the referral and in the converter sample. In the referral sample, exclusively, males showed more pronounced symptoms (all negative symptoms incl. reduced stress tolerance, grandiosity, and disorganized communication); in converters, females experienced more pronounced perceptual abnormalities, bizarre thinking, and odd behaviors, while males expressed and experienced emotions to a lower degree. Furthermore, sexes differed in psychosis-predictive symptoms: "suspiciousness" and "disorganized communication" were prominent in prediction of psychosis in males, whereas "trouble with focus and attention" was so in females. While most sex differences in patients attending an early detection service seem to reflect general differences that are not specifically related to psychosis, others might be psychosis-specific. These results can inform the development of more individualized and effective interventions for CHR patients based on more precise sex-specific prediction models.

Clinical Validity of DSM-5 Attenuated Psychosis Syndrome: Advances in Diagnosis, Prognosis, and Treatment

IMPORTANCE

Since the release of the DSM-5 diagnosis of attenuated psychosis syndrome (DSM-5-APS) in 2013, several research studies have investigated its clinical validity. Although critical and narrative reviews have reviewed these progresses, no systematic review has comprehensively summarized the available evidence regarding the clinical validity of DSM-5-APS.

OBJECTIVE

To provide current evidence on the clinical validity of DSM-5-APS, focusing on recent advances in diagnosis, prognosis, and treatment.

EVIDENCE REVIEW

A multistep literature search using the Web of Science database, Cochrane Central Register of Reviews, Ovid/PsychINFO, conference proceedings, and trial registries from database inception to June 16, 2019, was conducted following PRISMA and MOOSE guidelines and PROSPERO protocol. Studies with original data investigating individuals diagnosed using DSM-5-APS or meeting comparable criteria were included. The results of the systematic review were summarized in tables and narratively synthesized against established evidence-based antecedent, concurrent, and prognostic validators. A quantitative meta-analysis was conducted to explore the cumulative risk of psychosis onset at 6, 12, 24, and 36 months in individuals diagnosed using DSM-5-APS criteria.

FINDINGS

The systematic review included 56 articles, which reported on 124 validators, including 15 antecedent, 55 concurrent, and 54 prognostic validators. The epidemiological prevalence of the general non-help-seeking young population meeting DSM-5-APS criteria was 0.3%; the prevalence of individuals meeting DSM-5-APS criteria was variable in clinical samples. The interrater reliability for DSM-5-APS criteria was comparable with that of other DSM-5 mental disorders and can be optimized by the use of specific psychometric instruments. DSM-5-APS criteria were associated with frequent depressive comorbid disorders, distress, suicidality, and functional impairment. The meta-analysis included 23 prospective cohort studies, including 2376 individuals. The meta-analytical risk of psychosis onset was 11% at 6 months, 15% at 12 months, 20% at 24 months, and 23% at 36 months. Research into predisposing and precipitating epidemiological factors, neurobiological correlates, and effective treatments for DSM-5-APS criteria has been limited.

CONCLUSIONS AND RELEVANCE

Over recent years, DSM-5-APS criteria have received substantial concurrent and prognostic validation, mostly driven by research into the clinical high-risk state for psychosis. Precipitating and predisposing factors, neurobiological correlates, and effective treatments are undetermined to date.

What Causes the Onset of Psychosis in Individuals at Clinical High Risk? A Meta-analysis of Risk and Protective Factors

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.

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

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.

Patterns of symptoms before a diagnosis of first episode psychosis: a latent class analysis of UK primary care electronic health records

BACKGROUND

The nature of symptoms in the prodromal period of first episode psychosis (FEP) remains unclear. The objective was to determine the patterns of symptoms recorded in primary care in the 5 years before FEP diagnosis.

METHODS

The study was set within 568 practices contributing to a UK primary care health record database (Clinical Practice Research Datalink). Patients aged 16-45 years with a first coded record of FEP, and no antipsychotic prescription more than 1 year prior to FEP diagnosis (n = 3045) was age, gender, and practice matched to controls without FEP (n = 12,180). Fifty-five symptoms recorded in primary care in the previous 5 years, categorised into 8 groups (mood-related, 'neurotic', behavioural change, volition change, cognitive change, perceptual problem, substance misuse, physical symptoms), were compared between cases and controls. Common patterns of symptoms prior to FEP diagnosis were identified using latent class analysis.

RESULTS

Median age at diagnosis was 30 years, 63% were male. Non-affective psychosis (67%) was the most common diagnosis. Mood-related, 'neurotic', and physical symptoms were frequently recorded (> 30% of patients) before diagnosis, and behavioural change, volition change, and substance misuse were also common (> 10%). Prevalence of all symptom groups was higher in FEP patients than in controls (adjusted odds ratios 1.33-112). Median time from the first recorded symptom to FEP diagnosis was 2-2.5 years except for perceptual problem (70 days). The optimal latent class model applied to FEP patients determined three distinct patient clusters: 'no or minimal symptom cluster' (49%) had no or few symptoms recorded; 'affective symptom cluster' (40%) mainly had mood-related and 'neurotic' symptoms; and 'multiple symptom cluster' (11%) consulted for three or more symptom groups before diagnosis. The multiple symptom cluster was more likely to have drug-induced psychosis, female, obese, and have a higher morbidity burden. Affective and multiple symptom clusters showed a good discriminative ability (C-statistic 0.766; sensitivity 51.2% and specificity 86.7%) for FEP, and many patients in these clusters had consulted for their symptoms several years before FEP diagnosis.

CONCLUSIONS

Distinctive patterns of prodromal symptoms may help alert general practitioners to those developing psychosis, facilitating earlier identification and referral to specialist care, thereby avoiding potentially detrimental treatment delay.

Clinical-learning versus machine-learning for transdiagnostic prediction of psychosis onset in individuals at-risk

Predicting the onset of psychosis in individuals at-risk is based on robust prognostic model building methods including a priori clinical knowledge (also termed clinical-learning) to preselect predictors or machine-learning methods to select predictors automatically. To date, there is no empirical research comparing the prognostic accuracy of these two methods for the prediction of psychosis onset. In a first experiment, no improved performance was observed when machine-learning methods (LASSO and RIDGE) were applied-using the same predictors-to an individualised, transdiagnostic, clinically based, risk calculator previously developed on the basis of clinical-learning (predictors: age, gender, age by gender, ethnicity, ICD-10 diagnostic spectrum), and externally validated twice. In a second experiment, two refined versions of the published model which expanded the granularity of the ICD-10 diagnosis were introduced: ICD-10 diagnostic categories and ICD-10 diagnostic subdivisions. Although these refined versions showed an increase in apparent performance, their external performance was similar to the original model. In a third experiment, the three refined models were analysed under machine-learning and clinical-learning with a variable event per variable ratio (EPV). The best performing model under low EPVs was obtained through machine-learning approaches. The development of prognostic models on the basis of a priori clinical knowledge, large samples and adequate events per variable is a robust clinical prediction method to forecast psychosis onset in patients at-risk, and is comparable to machine-learning methods, which are more difficult to interpret and implement. Machine-learning methods should be preferred for high dimensional data when no a priori knowledge is available.

Four reasons why early detection centers for psychosis should be renamed and their treatment targets reconsidered: we should not catastrophize a future we can neither reliably predict nor change

Since the 1990s, facilities for individuals at putative risk for psychosis have mushroomed and within a very short time have become part of the standard psychiatric infrastructure in many countries. The idea of preventing a severe mental disorder before its exacerbation is laudable, and early data indeed strongly suggested that the sooner the intervention, the better the outcome. In this paper, the authors provide four reasons why they think that early detection or prodromal facilities should be renamed and their treatment targets reconsidered. First, the association between the duration of untreated psychosis and outcome is empirically established but has become increasingly weak over the years. Moreover, its applicability to those who are considered at risk remains elusive. Second, instruments designed to identify future psychosis are prone to many biases that are not yet sufficiently controlled. None of these instruments allows an even remotely precise prognosis. Third, the rate of transition to psychosis in at-risk patients is likely lower than initially thought, and evidence for the success of early intervention in preventing future psychosis is promising but still equivocal. Perhaps most importantly, the treatment is not hope-oriented. Patients are more or less told that schizophrenia is looming over them, which may stigmatize individuals who will never, in fact, develop psychosis. In addition self-stigma has been associated with suicidality and depression. The authors recommend that treatment of help-seeking individuals with mental problems but no established diagnosis should be need-based, and the risk of psychosis should be de-emphasized as it is only one of many possible outcomes, including full remission. Prodromal clinics should not be abolished but should be renamed and restructured. Such clinics exist, but the transformation process needs to be facilitated.

Psychosis Polyrisk Score (PPS) for the Detection of Individuals At-Risk and the Prediction of Their Outcomes

Primary prevention in individuals at Clinical High Risk for psychosis (CHR-P) can ameliorate the course of psychotic disorders. Further advancements of knowledge have been slowed by the standstill of the field, which is mostly attributed to its epidemiological weakness. The latter, in turn, underlies the limited identification power of at-risk individuals and the relatively modest ability of CHR-P interviews to rule-in a state of risk for psychosis. In the first part, this perspective review discusses these limitations and traces a new approach to overcome them. Theoretical concepts to support a Psychosis Polyrisk Score (PPS) integrating genetic and non-genetic risk and protective factors for psychosis are presented. The PPS hinges on recent findings indicating that risk enrichment in CHR-P samples is accounted for by the accumulation of non-genetic factors such as: parental and sociodemographic risk factors, perinatal risk factors, later risk factors, and antecedents. In the second part of this perspective review we present a prototype of a PPS encompassing core predictors beyond genetics. The PPS prototype may be piloted in the next generation of CHR-P research and combined with genetic information to refine the detection of individuals at-risk of psychosis and the prediction of their outcomes, and ultimately advance clinical research in this field.

Transdiagnostic Risk Calculator for the Automatic Detection of Individuals at Risk and the Prediction of Psychosis: Second Replication in an Independent National Health Service Trust

BACKGROUND

The benefits of indicated primary prevention among individuals at Clinical High Risk for Psychosis (CHR-P) are limited by the difficulty in detecting these individuals. To overcome this problem, a transdiagnostic, clinically based, individualized risk calculator has recently been developed and subjected to a first external validation in 2 different catchment areas of the South London and Maudsley (SLaM) NHS Trust.

METHODS

Second external validation of real world, real-time electronic clinical register-based cohort study. All individuals who received a first ICD-10 index diagnosis of nonorganic and nonpsychotic mental disorder within the Camden and Islington (C&I) NHS Trust between 2009 and 2016 were included. The model previously validated included age, gender, ethnicity, age by gender, and ICD-10 index diagnosis to predict the development of any ICD-10 nonorganic psychosis. The model's performance was measured using Harrell's C-index.

RESULTS

This study included a total of 13702 patients with an average age of 40 (range 16-99), 52% were female, and most were of white ethnicity (64%). There were no CHR-P or child/adolescent services in the C&I Trust. The C&I and SLaM Trust samples also differed significantly in terms of age, gender, ethnicity, and distribution of index diagnosis. Despite these significant differences, the original model retained an acceptable predictive performance (Harrell's C of 0.73), which is comparable to that of CHR-P tools currently recommended for clinical use.

CONCLUSIONS

This risk calculator may pragmatically support an improved transdiagnostic detection of at-risk individuals and psychosis prediction even in NHS Trusts in the United Kingdom where CHR-P services are not provided.

Real World Implementation of a Transdiagnostic Risk Calculator for the Automatic Detection of Individuals at Risk of Psychosis in Clinical Routine: Study Protocol

Background: Primary indicated prevention in individuals at-risk for psychosis has the potential to improve the outcomes of this disorder. The ability to detect the majority of at-risk individuals is the main barrier toward extending benefits for the lives of many adolescents and young adults. Current detection strategies are highly inefficient. Only 5% (standalone specialized early detection services) to 12% (youth mental health services) of individuals who will develop a first psychotic disorder can be detected at the time of their at-risk stage. To overcome these challenges a pragmatic, clinically-based, individualized, transdiagnostic risk calculator has been developed to detect individuals at-risk of psychosis in secondary mental health care at scale. This calculator has been externally validated and has demonstrated good prognostic performance. However, it is not known whether it can be used in the real world clinical routine. For example, clinicians may not be willing to adhere to the recommendations made by the transdiagnostic risk calculator. Implementation studies are needed to address pragmatic challenges relating to the real world use of the transdiagnostic risk calculator. The aim of the current study is to provide in-vitro and in-vivo feasibility data to support the implementation of the transdiagnostic risk calculator in clinical routine. Method: This is a study which comprises of two subsequent phases: an in-vitro phase of 1 month and an in-vivo phase of 11 months. The in-vitro phase aims at developing and integrating the transdiagnostic risk calculator in the local electronic health register (primary outcome). The in-vivo phase aims at addressing the clinicians' adherence to the recommendations made by the transdiagnostic risk calculator (primary outcome) and other secondary feasibility parameters that are necessary to estimate the resources needed for its implementation. Discussion: This is the first implementation study for risk prediction models in individuals at-risk for psychosis. Ultimately, successful implementation is the true measure of a prediction model's utility. Therefore, the overall translational deliverable of the current study would be to extend the benefits of primary indicated prevention and improve outcomes of first episode psychosis. This may produce significant social benefits for many adolescents and young adults and their families.

Short clinically-based prediction model to forecast transition to psychosis in individuals at clinical high risk state

Objective:

The predictive accuracy of the Clinical High Risk criteria for Psychosis (CHR-P) regarding the future development of the disorder remains suboptimal. It is therefore necessary to incorporate refined risk estimation tools which can be applied at the individual subject level. The aim of the study was to develop an easy-to use, short refined risk estimation tool to predict the development of psychosis in a new CHR-P cohort recruited in European country with less established early detection services.

Methods:

A cohort of 105 CHR-P individuals was assessed with the Comprehensive Assessment of At Risk Mental States12/2006, and then followed for a median period of 36 months (25th-75th percentile:10–59 months) for transition to psychosis. A multivariate Cox regression model predicting transition was generated with preselected clinical predictors and was internally validated with 1000 bootstrap resamples.

Results:

Speech disorganization and unusual thought content were selected as potential predictors of conversion on the basis of published literature. The prediction model was significant (p < 0.0001) and confirmed that both speech disorganization (HR = 1.69; 95%CI: 1.39–2.05) and unusual thought content (HR = 1.51; 95%CI: 1.27–1.80) were significantly associated with transition. The prognostic accuracy of the model was adequate (Harrell’s c- index = 0.79), even after optimism correction through internal validation procedures (Harrell’s c-index = 0.78).

Conclusions:

The clinical prediction model developed, and internally validated, herein to predict transition from a CHR-P to psychosis may be a promising tool for use in clinical settings. It has been incorporated into an online tool available at:https://link.konsta.com.pl/psychosis. Future external replication studies are needed.

Individualized Prediction of Transition to Psychosis in 1,676 Individuals at Clinical High Risk: Development and Validation of a Multivariable Prediction Model Based on Individual Patient Data Meta-Analysis

Background: The Clinical High Risk state for Psychosis (CHR-P) has become the cornerstone of modern preventive psychiatry. The next stage of clinical advancements rests on the ability to formulate a more accurate prognostic estimate at the individual subject level. Individual Participant Data Meta-Analyses (IPD-MA) are robust evidence synthesis methods that can also offer powerful approaches to the development and validation of personalized prognostic models. The aim of the study was to develop and validate an individualized, clinically based prognostic model for forecasting transition to psychosis from a CHR-P stage. Methods: A literature search was performed between January 30, 2016, and February 6, 2016, consulting PubMed, Psychinfo, Picarta, Embase, and ISI Web of Science, using search terms ("ultra high risk" OR "clinical high risk" OR "at risk mental state") AND [(conver* OR transition* OR onset OR emerg* OR develop*) AND psychosis] for both longitudinal and intervention CHR-P studies. Clinical knowledge was used to a priori select predictors: age, gender, CHR-P subgroup, the severity of attenuated positive psychotic symptoms, the severity of attenuated negative psychotic symptoms, and level of functioning at baseline. The model, thus, developed was validated with an extended form of internal validation. Results: Fifteen of the 43 studies identified agreed to share IPD, for a total sample size of 1,676. There was a high level of heterogeneity between the CHR-P studies with regard to inclusion criteria, type of assessment instruments, transition criteria, preventive treatment offered. The internally validated prognostic performance of the model was higher than chance but only moderate [Harrell's C-statistic 0.655, 95% confidence interval (CIs), 0.627-0.682]. Conclusion: This is the first IPD-MA conducted in the largest samples of CHR-P ever collected to date. An individualized prognostic model based on clinical predictors available in clinical routine was developed and internally validated, reaching only moderate prognostic performance. Although personalized risk prediction is of great value in the clinical practice, future developments are essential, including the refinement of the prognostic model and its external validation. However, because of the current high diagnostic, prognostic, and therapeutic heterogeneity of CHR-P studies, IPD-MAs in this population may have an limited intrinsic power to deliver robust prognostic models.

Transdiagnostic Individualized Clinically Based Risk Calculator for the Detection of Individuals at Risk and the Prediction of Psychosis: Model Refinement Including Nonlinear Effects of Age

Background: The first rate-limiting step for primary indicated prevention of psychosis is the detection of young people who may be at risk. The ability of specialized clinics to detect individuals at risk for psychosis is limited. A clinically based, individualized, transdiagnostic risk calculator has been developed and externally validated to improve the detection of individuals at risk in secondary mental health care. This calculator employs core sociodemographic and clinical predictors, including age, which is defined in linear terms. Recent evidence has suggested a nonlinear impact of age on the probability of psychosis onset. Aim: To define at a meta-analytical level the function linking age and probability of psychosis onset. To incorporate this function in a refined version of the transdiagnostic risk calculator and to test its prognostic performance, compared to the original specification. Design: Secondary analyses on a previously published meta-analysis and clinical register-based cohort study based on 2008-2015 routine secondary mental health care in South London and Maudsley (SLaM) National Health Service (NHS) Foundation Trust. Participants: All patients receiving a first index diagnosis of non-organic/non-psychotic mental disorder within SLaM NHS Trust in the period 2008-2015. Main outcome measure: Prognostic accuracy (Harrell's C). Results: A total of 91,199 patients receiving a first index diagnosis of non-organic and non-psychotic mental disorder within SLaM NHS Trust were included in the derivation (33,820) or external validation (54,716) datasets. The mean follow-up was 1,588 days. The meta-analytical estimates showed that a second-degree fractional polynomial model with power (-2, -1: age1 = age^-2 and age2 = age^-1) was the best-fitting model (P < 0.001). The refined model that included this function showed an excellent prognostic accuracy in the external validation (Harrell's C = 0.805, 95% CI from 0.790 to 0.819), which was statistically higher than the original model, although of modest magnitude (Harrell's C change = 0.0136, 95% CIs from 0.006 to 0.021, P < 0.001). Conclusions: The use of a refined version of the clinically based, individualized, transdiagnostic risk calculator, which allows for nonlinearity in the association between age and risk of psychosis onset, may offer a modestly improved prognostic performance. This calculator may be particularly useful in young individuals at risk of developing psychosis who access secondary mental health care.

Pan-London Network for Psychosis-Prevention (PNP)

Background: The empirical success of the Clinical High Risk for Psychosis (CHR-P) paradigm is determined by the concurrent integration of efficient detection of cases at-risk, accurate prognosis, and effective preventive treatment within specialized clinical services. The characteristics of the CHR-P services are relatively under-investigated. Method: A Pan-London Network for psychosis prevention (PNP) was created across urban CHR-P services. These services were surveyed to collect the following: description of the service and catchment area, outreach, service users, interventions, and outcomes. The results were analyzed with descriptive statistics and Kaplan Meier failure function. Results: The PNP included five CHR-P services across two NHS Trusts: Outreach and Support In South-London (OASIS) in Lambeth and Southwark, OASIS in Croydon and Lewisham, Tower Hamlets Early Detection Service (THEDS), City & Hackney At-Risk Mental State Service (HEADS UP) and Newham Early Intervention Service (NEIS). The PNP serves a total population of 2,318,515 Londoners (830,889; age, 16-35 years), with a yearly recruitment capacity of 220 CHR-P individuals (age, 22.55 years). Standalone teams (OASIS and THEDS) are more established and successful than teams that share their resources with other mental health services (HEADS UP, NEIS). Characteristics of the catchment areas, outreach and service users, differ across PNP services; all of them offer psychotherapy to prevent psychosis. The PNP is supporting several CHR-P translational research projects. Conclusions: The PNP is the largest CHR-P clinical network in the UK; it represents a reference benchmark for implementing detection, prognosis, and care in the real-world clinical routine, as well as for translating research innovations into practice.

Improving the Detection of Individuals at Clinical Risk for Psychosis in the Community, Primary and Secondary Care: An Integrated Evidence-Based Approach

Background: The first rate-limiting step for improving outcomes of psychosis through preventive interventions in people at clinical high risk for psychosis (CHR-P) is the ability to accurately detect individuals who are at risk for the development of this disorder. Currently, this detection power is sub-optimal. Methods: This is a conceptual and nonsystematic review of the literature, focusing on the work conducted by leading research teams in the field. The results will be structured in the following sections: understanding the CHR-P assessment, validity of the CHR-P as a universal risk state for psychosis, and improving the detection of at-risk individuals in secondary mental health care, in primary care, and in the community. Results: CHR-P instruments can provide adequate prognostic accuracy for the prediction of psychosis provided that they are employed in samples who have undergone risk enrichment during recruitment. This substantially limits their detection power in real-world settings. Furthermore, there is initial evidence that not all cases of psychosis onset are preceded by a CHR-P stage. A transdiagnostic individualized risk calculator could be used to automatically screen secondary mental health care medical notes to detect those at risk of psychosis and refer them to standard CHR-P assessment. Similar risk estimation tools for use in primary care are under development and promise to boost the detection of patients at risk in this setting. To improve the detection of young people who may be at risk of psychosis in the community, it is necessary to adopt digital and/or sequential screening approaches. These solutions are based on recent scientific evidence and have potential for implementation internationally. Conclusions: The best strategy to improve the detection of patients at risk for psychosis is to implement a clinical research program that integrates different but complementary detection approaches across community, primary, and secondary care. These solutions are based on recent scientific advancements in the development of risk estimation tools and e-health approaches and have the potential to be applied across different clinical settings.

Efficacy and Acceptability of Interventions for Attenuated Positive Psychotic Symptoms in Individuals at Clinical High Risk of Psychosis: A Network Meta-Analysis

Background: Attenuated positive psychotic symptoms represent the defining features of the clinical high-risk for psychosis (CHR-P) criteria. The effectiveness of each available treatment for reducing attenuated positive psychotic symptoms remains undetermined. This network meta-analysis (NMA) investigates the consistency and magnitude of the effects of treatments on attenuated positive psychotic symptoms in CHR-P individuals, weighting the findings for acceptability. Methods: Web of Science (MEDLINE), PsycInfo, CENTRAL and unpublished/gray literature were searched up to July 18, 2017. Randomized controlled trials in CHR-P individuals, comparing at least two interventions and reporting on attenuated positive psychotic symptoms at follow-up were included, following PRISMA guidelines. The primary outcome (efficacy) was level of attenuated positive psychotic symptoms at 6 and 12 months; effect sizes reported as standardized mean difference (SMD) and 95% CIs in mean follow-up scores between two compared interventions. The secondary outcome was treatment acceptability [reported as odds ratio (OR)]. NMAs were conducted for both primary and secondary outcomes. Treatments were cluster-ranked by surface under the cumulative ranking curve values for efficacy and acceptability. Assessments of biases, assumptions, sensitivity analyses and complementary pairwise meta-analyses for the primary outcome were also conducted. Results: Overall, 1,707 patients from 14 studies (57% male, mean age = 20) were included, representing the largest evidence synthesis of the effect of preventive treatments on attenuated positive psychotic symptoms to date. In the NMA for efficacy, ziprasidone + Needs-Based Intervention (NBI) was found to be superior to NBI (SMD = -1.10, 95% CI -2.04 to -0.15), Cognitive Behavioral Therapy-French and Morrison protocol (CBT-F) + NBI (SMD = -1.03, 95% CI -2.05 to -0.01), and risperidone + CBT-F + NBI (SMD = -1.18, 95% CI -2.29 to -0.07) at 6 months. However, these findings did not survive sensitivity analyses. For acceptability, aripiprazole + NBI was significantly more acceptable than olanzapine + NBI (OR = 3.73; 95% CI 1.01 to 13.81) at 12 months only. No further significant NMA effects were observed at 6 or 12 months. The results were not affected by inconsistency or evident small-study effects, but only two studies had an overall low risk of bias. Conclusion: On the basis of the current literature, there is no robust evidence to favor any specific intervention for improving attenuated positive psychotic symptoms in CHR-P individuals.

Lack of evidence to favor specific preventive interventions in psychosis: a network meta-analysis

Preventing psychosis in patients at clinical high risk may be a promising avenue for pre-emptively ameliorating outcomes of the most severe psychiatric disorder. However, information on how each preventive intervention fares against other currently available treatment options remains unavailable. The aim of the current study was to quantify the consistency and magnitude of effects of specific preventive interventions for psychosis, comparing different treatments in a network meta-analysis. PsycINFO, Web of Science, Cochrane Central Register of Controlled Trials, and unpublished/grey literature were searched up to July 18, 2017, to identify randomized controlled trials conducted in individuals at clinical high risk for psychosis, comparing different types of intervention and reporting transition to psychosis. Two reviewers independently extracted data. Data were synthesized using network meta-analyses. The primary outcome was transition to psychosis at different time points and the secondary outcome was treatment acceptability (dropout due to any cause). Effect sizes were reported as odds ratios and 95% confidence intervals (CIs). Sixteen studies (2,035 patients, 57% male, mean age 20.1 years) reported on risk of transition. The treatments tested were needs-based interventions (NBI); omega-3 + NBI; ziprasidone + NBI; olanzapine + NBI; aripiprazole + NBI; integrated psychological interventions; family therapy + NBI; D-serine + NBI; cognitive behavioural therapy, French & Morrison protocol (CBT-F) + NBI; CBT-F + risperidone + NBI; and cognitive behavioural therapy, van der Gaag protocol (CBT-V) + CBT-F + NBI. The network meta-analysis showed no evidence of significantly superior efficacy of any one intervention over the others at 6 and 12 months (insufficient data were available after 12 months). Similarly, there was no evidence for intervention differences in acceptability at either time point. Tests for inconsistency were non-significant and sensitivity analyses controlling for different clustering of interventions and biases did not materially affect the interpretation of the results. In summary, this study indicates that, to date, there is no evidence that any specific intervention is particularly effective over the others in preventing transition to psychosis. Further experimental research is needed.

Can We Predict Psychosis Outside the Clinical High-Risk State? A Systematic Review of Non-Psychotic Risk Syndromes for Mental Disorders

Recent evidence has suggested that psychosis could develop not only in people at clinical high risk for psychosis (CHR-P) but also in those with clinical risk syndromes for emergent nonpsychotic mental disorders. The proportion of people with these clinical risk syndromes who will develop psychosis rather than to other nonpsychotic mental disorders is undetermined. Electronic databases were searched for studies reporting on clinical risk syndromes for the development of emergent nonpsychotic mental disorders. Incidence of emerging psychotic and nonpsychotic mental disorders defined on the ICD or DSM. Of a total of 9 studies relating to 3006 nonpsychotic at-risk individuals were included. Within prospective studies (n = 4, sample = 1051), the pooled incidence of new psychotic disorders across these clinical risk syndromes was of 12.9 per 1000 person-years (95% CI: 4.3 to 38.6) and that of nonpsychotic disorders (n = 3, sample = 538) was of 43.5 per 1000 person-years (95% CI: 30.9 to 61.3). Psychotic disorders may emerge outside the CHR-P paradigm, from clinical risk syndromes for incident nonpsychotic disorders, albeit at lower rates than in the CHR-P group. The clinical risk syndromes for emerging nonpsychotic disorders may exhibit a pluripotential risk of developing several types of mental disorders compared with CHR-P. If substantiated by future research, the current findings suggest that it may be useful to move beyond the current strategy of identifying individuals meeting CHR-P criteria only.

Why transition risk to psychosis is not declining at the OASIS ultra high risk service: The hidden role of stable pretest risk enrichment

BACKGROUND

The reason for declining risk to psychosis across individuals assessed and meeting Ultra High Risk (UHR) criteria is still unclear. No studies have investigated the potential substantial role of the underlying risk enrichment across all the individuals undergoing an UHR assessment.

METHODS

Cohort study including all non-psychotic subjects who were assessed on suspicion of psychosis risk by the OASIS UHR service in the period 2001 to 2015. Posttest (after UHR assessment) and pretest risk (before UHR assessment) of psychosis were stratified and compared across three time periods (2001-2005, 2006-2010, 2011-2015) with Cox analysis and modulating factors were investigated.

RESULTS

The posttest risk of psychosis at the OASIS service has increased from the initial pilot years of the service (2001-2005) and then stabilised and not declined over the following decade (2006-2010 and 2011-2015). This was paralleled by a similar course of pretest risk for psychosis. Stability of pretest risk for psychosis over the past decade was associated with a lack of change in ethnicity and to counterweighting changes in the type of referral sources over different time periods.

CONCLUSIONS

The time course of transition risk to psychosis in UHR services is strictly associated with the time course of pretest risk enrichment. If the latter remains stable over time, as for the OASIS service, no declining transition risk is observed over the most recent years. Pretest risk enrichment is determined by recruitment and sampling strategies. This study confirms the need to control these factors in the UHR field.

What causes psychosis? An umbrella review of risk and protective factors

Psychosis is a heterogeneous psychiatric condition for which a multitude of risk and protective factors have been suggested. This umbrella review aimed to classify the strength of evidence for the associations between each factor and psychotic disorders whilst controlling for several biases. The Web of Knowledge database was searched to identify systematic reviews and meta-analyses of observational studies which examined associations between socio-demographic, parental, perinatal, later factors or antecedents and psychotic disorders, and which included a comparison group of healthy controls, published from 1965 to January 31, 2017. The literature search and data extraction followed PRISMA and MOOSE guidelines. The association between each factor and ICD or DSM diagnoses of non-organic psychotic disorders was graded into convincing, highly suggestive, suggestive, weak, or non-significant according to a standardized classification based on: number of psychotic cases, random-effects p value, largest study 95% confidence interval, heterogeneity between studies, 95% prediction interval, small study effect, and excess significance bias. In order to assess evidence for temporality of association, we also conducted sensitivity analyses restricted to data from prospective studies. Fifty-five meta-analyses or systematic reviews were included in the umbrella review, corresponding to 683 individual studies and 170 putative risk or protective factors for psychotic disorders. Only the ultra-high-risk state for psychosis (odds ratio, OR=9.32, 95% CI: 4.91-17.72) and Black-Caribbean ethnicity in England (OR=4.87, 95% CI: 3.96-6.00) showed convincing evidence of association. Six factors were highly suggestive (ethnic minority in low ethnic density area, second generation immigrants, trait anhedonia, premorbid IQ, minor physical anomalies, and olfactory identification ability), and nine were suggestive (urbanicity, ethnic minority in high ethnic density area, first generation immigrants, North-African immigrants in Europe, winter/spring season of birth in Northern hemisphere, childhood social withdrawal, childhood trauma, Toxoplasma gondii IgG, and non-right handedness). When only prospective studies were considered, the evidence was convincing for ultra-high-risk state and suggestive for urbanicity only. In summary, this umbrella review found several factors to be associated with psychotic disorders with different levels of evidence. These risk or protective factors represent a starting point for further etiopathological research and for the improvement of the prediction of psychosis.

Diagnostic and Prognostic Significance of DSM-5 Attenuated Psychosis Syndrome in Services for Individuals at Ultra High Risk for Psychosis

BACKGROUND

The diagnostic and prognostic significance of the DSM-5-defined Attenuated Psychosis Syndrome (DSM-5-APS) in individuals undergoing an ultra high risk (UHR) clinical assessment for suspicion of psychosis risk is unknown.

METHODS

Prospective cohort study including all consecutive help-seeking individuals undergoing both a DSM-5-APS and a Comprehensive Assessment of At Risk Mental States (CAARMS 12/2006) assessment for psychosis risk at the Outreach and Support in South London (OASIS) UHR service (March 2013-April 2014). The diagnostic significance of DSM-5-APS was assessed with percent overall agreement, prevalence bias adjusted kappa, Bowker's test, Stuart-Maxwell test, residual analysis; the prognostic significance with Cox regression, Kaplan-Meier failure function, time-dependent area under the curve (AUC) and net benefits analysis. The impact of specific revisions of the DSM-5-APS was further tested.

RESULT

In 203 help-seeking individuals undergoing UHR assessment, the agreement between the DSM-5-APS and the CAARMS 12/2006 was only moderate (kappa 0.59). Among 142 nonpsychotic cases, those meeting DSM-5-APS criteria had a 5-fold probability (HR = 5.379) of developing psychosis compared to those not meeting DSM-5-APS criteria, with a 21-month cumulative risk of psychosis of 28.17% vs 6.49%, respectively. The DSM-5-APS prognostic accuracy was acceptable (AUC 0.76 at 24 months) and similar to the CAARMS 12/2006. The DSM-5-APS designation may be clinically useful to guide the provision of indicated interventions within a 7%-35% (2-year) range of psychosis risk. The removal of the criterion E or C of the DSM-5-APS may improve its prognostic performance and transdiagnostic value.

CONCLUSIONS

The DSM-5-APS designation may be clinically useful in individuals accessing clinical services for psychosis prevention.

Improving outcomes of first-episode psychosis: an overview

Outcomes of psychotic disorders are associated with high personal, familiar, societal and clinical burden. There is thus an urgent clinical and societal need for improving those outcomes. Recent advances in research knowledge have opened new opportunities for ameliorating outcomes of psychosis during its early clinical stages. This paper critically reviews these opportunities, summarizing the state-of-the-art knowledge and focusing on recent discoveries and future avenues for first episode research and clinical interventions. Candidate targets for primary universal prevention of psychosis at the population level are discussed. Potentials offered by primary selective prevention in asymptomatic subgroups (stage 0) are presented. Achievements of primary selected prevention in individuals at clinical high risk for psychosis (stage 1) are summarized, along with challenges and limitations of its implementation in clinical practice. Early intervention and secondary prevention strategies at the time of a first episode of psychosis (stage 2) are critically discussed, with a particular focus on minimizing the duration of untreated psychosis, improving treatment response, increasing patients' satisfaction with treatment, reducing illicit substance abuse and preventing relapses. Early intervention and tertiary prevention strategies at the time of an incomplete recovery (stage 3) are further discussed, in particular with respect to addressing treatment resistance, improving well-being and social skills with reduction of burden on the family, treatment of comorbid substance use, and prevention of multiple relapses and disease progression. In conclusion, to improve outcomes of a complex, heterogeneous syndrome such as psychosis, it is necessary to globally adopt complex models integrating a clinical staging framework and coordinated specialty care programmes that offer pre-emptive interventions to high-risk groups identified across the early stages of the disorder. Only a systematic implementation of these models of care in the national health care systems will render these strategies accessible to the 23 million people worldwide suffering from the most severe psychiatric disorders.

Long-term validity of the At Risk Mental State (ARMS) for predicting psychotic and non-psychotic mental disorders

BACKGROUND

The long-term clinical validity of the At Risk Mental State (ARMS) for the prediction of non-psychotic mental disorders is unknown.

METHODS

Clinical register-based cohort study including all non-psychotic individuals assessed by the Outreach And Support in South London (OASIS) service (2002-2015). The primary outcome was risk of developing any mental disorder (psychotic or non-psychotic). Analyses included Cox proportional hazard models, Kaplan-Meier survival/failure function and C statistics.

RESULTS

A total of 710 subjects were included. A total of 411 subjects were at risk (ARMS+) and 299 not at risk (ARMS-). Relative to ARMS-, the ARMS+ was associated with an increased risk (HR=4.825) of developing psychotic disorders, and a reduced risk (HR=0.545) of developing non-psychotic disorders (mainly personality disorders). At 6-year, the ARMS designation retained high sensitivity (0.873) but only modest specificity (0.456) for the prediction of psychosis onset (AUC 0.68). The brief and limited intermittent psychotic symptoms (BLIPS) subgroup had a higher risk of developing psychosis, and a lower risk of developing non-psychotic disorders as compared to the attenuated psychotic symptoms (APS) subgroup (P<0.001).

CONCLUSIONS

In the long-term, the ARMS specifically predicts the onset of psychotic disorders, with modest accuracy, but not of non-psychotic disorders. Individuals meeting BLIPS criteria have distinct clinical outcomes.

SIGNIFICANT OUTCOMES

In the long-term, the ARMS designation is still significantly associated with an increased risk of developing psychotic disorders but its prognostic accuracy is only modest. There is no evidence that the ARMS is associated with an increased risk of developing non-psychotic mental disorders. The BLIPS subgroup at lower risk of developing non-psychotic disorders compared to the APS subgroup.

LIMITATIONS

While incident diagnoses employed in this study are high in ecological validity they have not been subjected to formal validation with research-based criteria.