scholarly journals Overlooking the transition elephant in the ultra-high-risk room: are we missing functional equivalents of transition to psychosis?

2019 ◽  
pp. 1-4
Author(s):  
Andrea Raballo ◽  
Michele Poletti
Keyword(s):  
High Risk ◽  
Mental State ◽  
Predictive Value ◽  
Dilution Effect ◽  
Transition Rates ◽  
Confounding Effect ◽  
Ultra High Risk ◽  
Unique Outcome

Abstract In the wake of the almost quarter of a century since the conceptualization of ultra-high-risk (UHR) states for psychosis, empirical evidences in the field are constantly scrutinized and re-assessed through meta-analytic lens. Briefly, such scrutiny converges on three major evidences: pretest risk enrichment, risk hierarchy within UHR states, and declining transition rates. While the former two are intuitive, the dilution effect remains elusive and might be rather symptomatic of unsolved issues in the field. Those include the heterogeneously reported antipsychotic (AP) exposure in UHR samples and the almost univocal focus on purely psychometric transition to psychosis. Both issues lead to the neglect of functional equivalents of transition, i.e. that of a mental state at immediate need for AP medication, and might have a cascading confounding effect on the predictive value of contemporary risk calculators centered on criterial transition as a unique outcome.

scholarly journals Declining transition rates to psychotic disorder in “ultra-high risk” clients: Investigation of a dilution effect

2016 ◽  
Vol 170 (1) ◽  
pp. 130-136 ◽  
Author(s):  
Jessica A. Hartmann ◽  
Hok Pan Yuen ◽  
Patrick D. McGorry ◽  
Alison R. Yung ◽  
Ashleigh Lin ◽  
...  
Keyword(s):  
High Risk ◽  
Psychotic Disorder ◽  
Dilution Effect ◽  
Transition Rates ◽  
Ultra High Risk

scholarly journals The reality of at risk mental state services: a response to recent criticisms

2019 ◽  
pp. 1-7 ◽  
Author(s):  
Alison R. Yung ◽  
Stephen J. Wood ◽  
Ashok Malla ◽  
Barnaby Nelson ◽  
Patrick McGorry ◽  
...  
Keyword(s):  
At Risk ◽  
High Risk ◽  
Psychotic Disorder ◽  
Mental State ◽  
Help Seeking ◽  
Psychotic Symptoms ◽  
Ultra High Risk ◽  
Psychological Medicine ◽  
Poor Outcomes ◽  
At Risk Mental State

AbstractBackgroundIn the 1990s criteria were developed to detect individuals at high and imminent risk of developing a psychotic disorder. These are known as the at risk mental state, ultra high risk or clinical high risk criteria. Individuals meeting these criteria are symptomatic and help-seeking. Services for such individuals are now found worldwide. Recently Psychological Medicine published two articles that criticise these services and suggest that they should be dismantled or restructured. One paper also provides recommendations on how ARMS services should be operate.MethodsIn this paper we draw on the existing literature in the field and present the perspective of some ARMS clinicians and researchers.ResultsMany of the critics' arguments are refuted. Most of the recommendations included in the Moritz et al. paper are already occurring.ConclusionsARMS services provide management of current problems, treatment to reduce risk of onset of psychotic disorder and monitoring of mental state, including attenuated psychotic symptoms. These symptoms are associated with a range of poor outcomes. It is important to assess them and track their trajectory over time. A new approach to detection of ARMS individuals can be considered that harnesses broad youth mental health services, such as headspace in Australia, Jigsaw in Ireland and ACCESS Open Minds in Canada. Attention should also be paid to the physical health of ARMS individuals. Far from needing to be dismantled we feel that the ARMS approach has much to offer to improve the health of young people.

Checking the predictive accuracy of basic symptoms against ultra high-risk criteria and testing of a multivariable prediction model: Evidence from a prospective three-year observational study of persons at clinical high-risk for psychosis

2017 ◽  
Vol 45 ◽  
pp. 27-35 ◽  
Author(s):  
M.P. Hengartner ◽  
K. Heekeren ◽  
D. Dvorsky ◽  
S. Walitza ◽  
W. Rössler ◽  
...  
Keyword(s):  
High Risk ◽  
Prediction Model ◽  
Sensitivity And Specificity ◽  
Predictive Value ◽  
Predictive Accuracy ◽  
Positive Symptoms ◽  
Clinical High Risk ◽  
Verbal Iq ◽  
Basic Symptoms ◽  
Ultra High Risk

AbstractBackground:The aim of this study was to critically examine the prognostic validity of various clinical high-risk (CHR) criteria alone and in combination with additional clinical characteristics.Methods:A total of 188 CHR positive persons from the region of Zurich, Switzerland (mean age 20.5 years; 60.2% male), meeting ultra high-risk (UHR) and/or basic symptoms (BS) criteria, were followed over three years. The test battery included the Structured Interview for Prodromal Syndromes (SIPS), verbal IQ and many other screening tools. Conversion to psychosis was defined according to ICD-10 criteria for schizophrenia (F20) or brief psychotic disorder (F23).Results:Altogether n = 24 persons developed manifest psychosis within three years and according to Kaplan–Meier survival analysis, the projected conversion rate was 17.5%. The predictive accuracy of UHR was statistically significant but poor (area under the curve [AUC] = 0.65, P < .05), whereas BS did not predict psychosis beyond mere chance (AUC = 0.52, P = .730). Sensitivity and specificity were 0.83 and 0.47 for UHR, and 0.96 and 0.09 for BS. UHR plus BS achieved an AUC = 0.66, with sensitivity and specificity of 0.75 and 0.56. In comparison, baseline antipsychotic medication yielded a predictive accuracy of AUC = 0.62 (sensitivity = 0.42; specificity = 0.82). A multivariable prediction model comprising continuous measures of positive symptoms and verbal IQ achieved a substantially improved prognostic accuracy (AUC = 0.85; sensitivity = 0.86; specificity = 0.85; positive predictive value = 0.54; negative predictive value = 0.97).Conclusions:We showed that BS have no predictive accuracy beyond chance, while UHR criteria poorly predict conversion to psychosis. Combining BS with UHR criteria did not improve the predictive accuracy of UHR alone. In contrast, dimensional measures of both positive symptoms and verbal IQ showed excellent prognostic validity. A critical re-thinking of binary at-risk criteria is necessary in order to improve the prognosis of psychotic disorders.

scholarly journals Ultra High Risk Status and Transition to Psychosis in 22q11.2 Deletion Syndrome

2017 ◽  
Vol 41 (S1) ◽  
pp. S81-S82
Author(s):  
M. Armando ◽  
M. Schneider ◽  
M. Pontillo ◽  
S. Vicari ◽  
M. Debbane ◽  
...  
Keyword(s):  
High Risk ◽  
Predictive Value ◽  
Transition Rate ◽  
22Q11.2 Deletion Syndrome ◽  
Human Model ◽  
Deletion Syndrome ◽  
Additional Contribution ◽  
22Q11.2 Deletion ◽  
Level Of Functioning ◽  
Ultra High Risk

The 22q11.2 deletion syndrome (22q11DS) is characterized by high rates of psychotic symptoms and schizophrenia, making this condition a promising human model for studying risk factors for psychosis. We explored the predictive value of ultra high-risk (UHR) criteria in a sample of patients with 22q11DS. We also examined the additional contribution of sociodemographic, clinical and cognitive variables to predict transition to psychosis within a mean interval of 32.56176 months after initial assessment. Eighty-nine participants with 22q11DS (age range: 8–30 years; mean: 16.1647) were assessed using the structured interview for psychosis-risk syndromes. Information on axis I diagnoses, internalizing and externalizing symptoms, level of functioning and IQ was also collected. At baseline, 22 (24.7%) participants met UHR criteria. Compared to those without a UHR condition, they had a significantly lower functioning, more frequent anxiety disorders and more severe psychopathology. Transition rate to psychosis was 27.3% in UHR and 4.5% in non-UHR participants. Cox regression analyses revealed that UHR status significantly predicted conversion to psychosis. Baseline level of functioning was the only other additional predictor. This is the first study investigating the predictive value of UHR criteria in 22q11DS. It indicates that the clinical path leading to psychosis is broadly comparable to that observed in other clinical high-risk samples. Nevertheless, the relatively high transition rate in non-UHR individuals suggests that other risk markers should be explored in this population. The role of low functioning as a predictor of transition to psychosis should also be investigated more in depth.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Cannabis use and transition to psychosis in individuals at ultra-high risk: review and meta-analysis

2015 ◽  
Vol 46 (4) ◽  
pp. 673-681 ◽  
Author(s):  
T. Kraan ◽  
E. Velthorst ◽  
L. Koenders ◽  
K. Zwaart ◽  
H. K. Ising ◽  
...  
Keyword(s):  
High Risk ◽  
Psychotic Disorders ◽  
Meta Analysis ◽  
Cannabis Use ◽  
Transition Rates ◽  
Cannabis Abuse ◽  
Ultra High Risk ◽  
Meta Analyses ◽  
Risk Review ◽  
The Relationship

BackgroundPrevious research has established the relationship between cannabis use and psychotic disorders. Whether cannabis use is related to transition to psychosis in patients at ultra-high risk (UHR) for psychosis remains unclear. The present study aimed to review the existing evidence on the association between cannabis use and transition to psychosis in UHR samples.MethodA search of PsychInfo, Embase and Medline was conducted from 1996 to August 2015. The search yielded 5559 potentially relevant articles that were selected on title and abstract. Subsequently 36 articles were screened on full text for eligibility. Two random-effects meta-analyses were performed. First, we compared transition rates to psychosis of UHR individuals with lifetime cannabis use with non-cannabis-using UHR individuals. Second, we compared transition rates of UHR individuals with a current DSM-IV cannabis abuse or dependence diagnosis with lifetime users and non-using UHR individuals.ResultsWe found seven prospective studies reporting on lifetime cannabis use in UHR subjects (n = 1171). Of these studies, five also examined current cannabis abuse or dependence. Lifetime cannabis use was not significantly associated with transition to psychosis [odds ratio (OR) 1.14, 95% confidence interval (CI) 0.856–1.524, p = 0.37]. A second meta-analysis yielded an OR of 1.75 (95% CI 1.135–2.710, p = 0.01), indicating a significant association between current cannabis abuse or dependence and transition to psychosis.ConclusionsOur results show that cannabis use was only predictive of transition to psychosis in those who met criteria for cannabis abuse or dependence, tentatively suggesting a dose–response relationship between current cannabis use and transition to psychosis.

Declining transition rates to psychosis: the contribution of potential changes in referral pathways to an ultra-high-risk service

2013 ◽  
Vol 9 (3) ◽  
pp. 200-206 ◽  
Author(s):  
Suzanne Wiltink ◽  
Eva Velthorst ◽  
Barnaby Nelson ◽  
Patrick M. McGorry ◽  
Alison R. Yung
Keyword(s):  
High Risk ◽  
Transition Rates ◽  
Ultra High Risk

scholarly journals At-risk mental state for psychosis: identification and current treatment approaches

2016 ◽  
Vol 22 (3) ◽  
pp. 186-193 ◽  
Author(s):  
Andrew Thompson ◽  
Steven Marwaha ◽  
Matthew R. Broome
Keyword(s):  
Risk Factors ◽  
At Risk ◽  
High Risk ◽  
Psychotic Disorder ◽  
Mental State ◽  
Ethical Issues ◽  
Current Treatment ◽  
Ultra High Risk ◽  
Psychosis Prodrome ◽  
At Risk Mental State

SummaryThe concept of an ‘at-risk mental state’ for psychosis arose from previous work attempting to identify a putative psychosis prodrome. In this article we summarise the current criteria used to identify ‘at-risk’ individuals, such as the ultra-high-risk (UHR) criteria, and the further identification of important clinical risk factors or biomarkers to improve prediction of who might develop a psychotic disorder. We also discuss important ethical issues in classifying and treating at-risk individuals, current treatment trials in this area and what treatment current services can offer.

scholarly journals Twelve-month psychosis-predictive value of the ultra-high risk criteria in children and adolescents

2015 ◽  
Vol 169 (1-3) ◽  
pp. 186-192 ◽  
Author(s):  
Marco Armando ◽  
Maria Pontillo ◽  
Franco De Crescenzo ◽  
Luigi Mazzone ◽  
Elena Monducci ◽  
...  
Keyword(s):  
High Risk ◽  
Children And Adolescents ◽  
Predictive Value ◽  
Risk Criteria ◽  
Ultra High Risk

scholarly journals Risk stratification of smoldering multiple myeloma: predictive value of free light chains and group-based trajectory modeling

2018 ◽  
Vol 2 (12) ◽  
pp. 1470-1479 ◽  
Author(s):  
Vernon Wu ◽  
Erin Moshier ◽  
Siyang Leng ◽  
Bart Barlogie ◽  
Hearn Jay Cho ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
High Risk ◽  
Risk Stratification ◽  
Predictive Value ◽  
Light Chains ◽  
Free Light Chains ◽  
Trajectory Modeling ◽  
Smoldering Multiple Myeloma ◽  
Key Points ◽  
Ultra High Risk

Key Points FLCr ≥100 and BMPC ≥60% identify high-risk SMM, although with more modest median TTP and 2-year PD than previously published. Baseline immunoparesis, eMP, eHb, and edFLC can help identify an ultra-high-risk SMM cohort.

The structure of the ultra high risk mental state for psychosis. A latent class cluster analysis study

2011 ◽  
Vol 26 (S2) ◽  
pp. 2087-2087 ◽  
Author(s):  
L. Valmaggia ◽  
D. Stahl ◽  
A. Yung ◽  
B. Nelson ◽  
P. McGorry ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
High Risk ◽  
Mental State ◽  
Negative Symptoms ◽  
Latent Class ◽  
Community Mental Health Services ◽  
Psychotic Symptoms ◽  
Latent Class Cluster Analysis ◽  
Class 1 ◽  
Ultra High Risk

IntroductionIndividuals at Ultra High Risk (UHR) for psychosis typically present with attenuated psychotic symptoms. However it is difficult to predict which individuals will later develop frank psychosis when their mental state is rated in terms of individual symptoms.The objective of the study was to examine the phenomenological structure of the UHR mental state and identify symptom profiles that predict later transition to psychosis.MethodPsychopathological data from a large sample of UHR subjects were analysed using latent class cluster analysis.A total of 318 individuals with a UHR for psychosis. Data were collected from two specialised community mental health services for people at UHR for psychosis: OASIS in London and PACE, in Melbourne.ResultsLatent class cluster analysis produced 4 classes: Class 1 - Mild was characterized by lower scores on all the CAARMS items. Subjects in Class 2 - Moderate scored moderately on all CAARMS items and was more likely to be in employment. Those in Class 3 - Moderate-Severe scored moderately-severe on negative symptoms, social isolation and impaired role functioning. Class 4 - Severe was the smallest group and was associated with the most impairment: subjects in this class scored highest on all items of the CAARMS, had the lowest GAF score and were more likely to be unemployed. This group was also characterized by the highest transition rate (41%).ConclusionsDifferent constellations of symptomatology are associates with varying levels of risk to of transition to psychosis.

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