Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-10T06:46:02.556Z Has data issue: false hasContentIssue false
  • English
  • Français

Psychosis prediction in Secondary Mental Health Services. a Broad, Comprehensive Approach to the “at Risk Mental State” Syndrome

Published online by Cambridge University Press:  16 December 2016

M. Francesconi ,
A. Minichino ,
R.E. Carrión ,
R. Delle Chiaie ,
A. Bevilacqua ,
M. Parisi ,
S. Rullo ,
F. Saverio Bersani ,
M. Biondi  and
K. Cadenhead
M. Francesconi
Affiliation:
Department of Neurology and Psychiatry, Sapienza University of Rome, Italy Department of Psychiatry, UCSD, La Jolla, CA, United States
A. Minichino*
Affiliation:
Department of Neurology and Psychiatry, Sapienza University of Rome, Italy Department of Psychiatry, UCSD, La Jolla, CA, United States
R.E. Carrión
Affiliation:
Division of Psychiatry, Zucker Hillside Hospital, Long Island, NY, United States
R. Delle Chiaie
Affiliation:
Department of Neurology and Psychiatry, Sapienza University of Rome, Italy
A. Bevilacqua
Affiliation:
Research Center in Neurobiology, Daniel Bovet (CRiN), Rome, Italy Department of Psychology, Section of Neuroscience, Sapienza University of Rome, Italy
M. Parisi
Affiliation:
Villa Armonia Nuova, Rome, Italy
S. Rullo
Affiliation:
Casa di Cura Villa Letizia, Rome, Italy
F. Saverio Bersani
Affiliation:
Department of Neurology and Psychiatry, Sapienza University of Rome, Italy
M. Biondi
Affiliation:
Department of Neurology and Psychiatry, Sapienza University of Rome, Italy
K. Cadenhead
Affiliation:
Department of Psychiatry, UCSD, La Jolla, CA, United States
*
* Corresponding author at: Viale dell’Universita’, 30, 00185 Rome, Italy. Tel.: +39 3389561007/+1 4152440441. E-mail address:amedeomin@gmail.com (A. Minichino).
Get access

Abstract

Background

Accuracy of risk algorithms for psychosis prediction in “at risk mental state” (ARMS) samples may differ according to the recruitment setting. Standardized criteria used to detect ARMS individuals may lack specificity if the recruitment setting is a secondary mental health service. The authors tested a modified strategy to predict psychosis conversion in this setting by using a systematic selection of trait-markers of the psychosis prodrome in a sample with a heterogeneous ARMS status.

Methods

138 non-psychotic outpatients (aged 17–31) were consecutively recruited in secondary mental health services and followed-up for up to 3 years (mean follow-up time, 2.2 years; SD = 0.9). Baseline ARMS status, clinical, demographic, cognitive, and neurological soft signs measures were collected. Cox regression was used to derive a risk index.

Results

48% individuals met ARMS criteria (ARMS-Positive, ARMS+). Conversion rate to psychosis was 21% for the overall sample, 34% for ARMS+, and 9% for ARMS-Negative (ARMS−). The final predictor model with a positive predictive validity of 80% consisted of four variables: Disorder of Thought Content, visuospatial/constructional deficits, sensory-integration, and theory-of-mind abnormalities. Removing Disorder of Thought Content from the model only slightly modified the predictive accuracy (−6.2%), but increased the sensitivity (+9.5%).

Conclusions

These results suggest that in a secondary mental health setting the use of trait-markers of the psychosis prodrome may predict psychosis conversion with great accuracy despite the heterogeneity of the ARMS status. The use of the proposed predictive algorithm may enable a selective recruitment, potentially reducing duration of untreated psychosis and improving prognostic outcomes.

Keywords

Clinical high riskUltra high riskTheory of mindNeurocognitionNeurological soft signs
Type
Original article
Information
European Psychiatry , Volume 40 , February 2017 , pp. 96 - 104
Copyright
Copyright © Elsevier Masson SAS 2017

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

1

These two authors contributed equally to this work.

References

Addington, J.Liu, L.Buchy, L.Cadenhead, K.S.Cannon, T.D.Cornblatt, B.A.et al.North American Prodrome Longitudinal Study (NAPLS 2): the prodromal symptoms J Nerv Ment Dis 2015; 203(5): 328–335CrossRefGoogle ScholarPubMed
Seidman, L.J.Neuropsychology of the prodrome to psychosis in the NAPLS consortium. Relationship to family history and conversion to psychosis. Arch Gen Psychiatry 2010; 67(6): 578CrossRefGoogle ScholarPubMed
Yung, A.R.Yuen, H.P.McGorry, P.D.Phillips, L.J.Kelly, D.Dell’Olio, M.et al.Mapping the onset of psychosis: the Comprehensive Assessment of At-Risk Mental States. Aust N Z J Psychiatry 2004; 39(11–12):964–971CrossRefGoogle Scholar
Miller, T.J.McGlashan, T.H.Rosen, J.L.Cadenhead, K.Cannon, T.Ventura, J.et al.Prodromal assessment with the structured interview for prodromal syndromes and the scale of prodromal symptoms: predictive validity, interrater reliability, and training to reliability Schizophr Bull 2003; 29(4): 703–715CrossRefGoogle ScholarPubMed
Fusar-Poli, P.Bonoldi, I.Yung, A.R.Borgwardt, S.Kempton, M.J.Valmaggia, L.et al.Predicting psychosis: meta-analysis of transition outcomes in individuals at high clinical risk Arch Gen Psychiatry 2012; 69(3): 220–229CrossRefGoogle ScholarPubMed
Nelson, B.Yuen, H.P.Wood, S.J.Lin, A.Spiliotacopoulos, D.Bruxner, A.et al.Long-term follow-up of a group at ultra high risk (“prodromal”) for psychosis: the PACE 400 study JAMA Psychiatry 2013; 70(8): 793–802CrossRefGoogle ScholarPubMed
Simon, A.E.Velthorst, E.Nieman, D.H.Linszen, D.Umbricht, D.de Haan, L.Ultra high-risk state for psychosis and non-transition: a systematic review. Schizophr Res 2011; 132(1): 8–17CrossRefGoogle ScholarPubMed
Simon, A.E.Borgwardt, S.Riecher-Rössler, A.Velthorst, E.de Haan, L.Fusar-Poli, P.Moving beyond transition outcomes: meta-analysis of remission rates in individuals at high clinical risk for psychosis. Psychiatry Res 2013; 209(3): 266–272CrossRefGoogle ScholarPubMed
Simon, A.E.Umbricht, D.Lang, U.E.Borgwardt, S.Declining transition rates to psychosis: the role of diagnostic spectra and symptom overlaps in individuals with attenuated psychosis syndrome. Schizophr Res 2014; 159(2–3):292–298CrossRefGoogle ScholarPubMed
Cornblatt, B.A.Carrión, R.E.Auther, A.Mclaughlin, D.Olsen, R.H.John, M. et al. Psychosis prevention: a modified clinical high risk perspective from the recognition and prevention (RAP) program. Am J Psychiatry 2015; 172(10):986–94.CrossRefGoogle Scholar
Hanssen, M.Bak, M.Bijl, R.Vollebergh, W.van Os, J.The incidence and outcome of subclinical psychotic experiences in the general population. Br J Clin Psychol 2005; 44(June (Pt 2)):181–191CrossRefGoogle ScholarPubMed
Yung, A.R.McGorry, P.D.The prodromal phase of first-episode psychosis: past and current conceptualizations. Schizophr Bull 1996; 22(2): 353–370CrossRefGoogle ScholarPubMed
Chen, Y.Bidwell, L.C.Norton, D.Trait vs. state markers for schizophrenia: identification and characterization through visual processes. Curr Psychiatry Rev 2006; 2(November (4)):431–438CrossRefGoogle ScholarPubMed
Simon, A.E.Umbricht, D.High remission rates from an initial ultra-high risk state for psychosis. Schizophr Res 2010; 116(2–3):168–172CrossRefGoogle Scholar
Ziermans, T.B.Schothorst, P.F.Sprong, M.van Engeland, H.Transition and remission in adolescents at ultra-high risk for psychosis. Schizophr Res 2011; 126(1–3):58–64CrossRefGoogle ScholarPubMed
Escher, S.Romme, M.Buiks, A.Delespaul, P.van Os, J.Formation of delusional ideation in adolescents hearing voices: a prospective study. Am J Med Genet 2002; 114(8): 913–920CrossRefGoogle ScholarPubMed
Apter, A.Bleich, A.Tyano, S.Affective and psychotic psychopathology in hospitalized adolescents. J Am Acad Child Adolesc Psychiatry 1988; 27(January (1)):116–120CrossRefGoogle ScholarPubMed
Ulloa, R.E.Birmaher, B.Axelson, D.Williamson, D.E.Brent, D.A.Ryan, N.D.et al.Psychosis in a pediatric mood and anxiety disorders clinic: phenomenology and correlates J Am Acad Child Adolesc Psychiatry 2000; 39(3): 337–345CrossRefGoogle Scholar
Yee, L.Yee, L.Korner, A.J.McSwiggan, S.Meares, R.A.Stevenson, J.Persistent hallucinosis in borderline personality disorder. Compr Psychiatry 2013; 46(2): 147–154CrossRefGoogle Scholar
Rietdijk, J.Klaassen, R.Ising, H.Dragt, S.Nieman, D.H.van de Kamp, J.et al.Detection of people at risk of developing a first psychosis: comparison of two recruitment strategies Acta Psychiatr Scand 2012; 126(1): 21–30CrossRefGoogle ScholarPubMed
Brandizzi, M.Valmaggia, L.Byrne, M.Jones, C.Iwegbu, N.Badger, S.et al.Predictors of functional outcome in individuals at high clinical risk for psychosis at six years follow-up. J Psychiatr Res 2015; 65(June):115–123CrossRefGoogle ScholarPubMed
Lin, A.Wood, S.J.Nelson, B.Brewer, W.J.Spiliotacopoulos, D.Bruxner, A.et al.Neurocognitive predictors of functional outcome two to 13years after identification as ultra-high risk for psychosis Schizophr Res 2011CrossRefGoogle Scholar
Lee, T.Y.Hong, S.B.Shin, N.Y.Kwon, J.S.Social cognitive functioning in prodromal psychosis: a meta-analysis. Schizophr Res 2015; 164(1–3):28–34CrossRefGoogle ScholarPubMed
Tamagni, C.Studerus, E.Gschwandtner, U.Aston, J.Borgwardt, S.Riecher-Rössler, A.Are neurological soft signs pre-existing markers in individuals with an at-risk mental state for psychosis?. Psychiatry Res 2013; 210(2): 427–431CrossRefGoogle ScholarPubMed
Chan, R.C.K.Xu, T.Heinrichs, R.W.Yu, Y.Wang, Y.Neurological soft signs in schizophrenia: a meta-analysis. Schizophr Bull 2010; 36(6): 1089–1104CrossRefGoogle ScholarPubMed
Zhang, T.Li, H.Stone, W.S.Woodberry, K.A.Seidman, L.J.Tang, Y.Neuropsychological impairment in prodromal, first-episode, and chronic psychosis: assessing RBANS performance. PLoS ONE 2014; 10(5):e0125784CrossRefGoogle Scholar
Bora, E.Yücel, M.Pantelis, C.Theory of mind impairment: a distinct trait-marker for schizophrenia spectrum disorders and bipolar disorder?. Acta Psychiatr Scand 2009; 120(4): 253–264CrossRefGoogle ScholarPubMed
Rietdijk, J.Hogerzeil, S.J.van Hemert, A.M.Cuijpers, P.Linszen, D.H.van der Gaag, M.Pathways to psychosis: help-seeking behavior in the prodromal phase. Schizophr Res 2011; 132(2–3):213–219CrossRefGoogle ScholarPubMed
Insel, T.Cuthbert, B.Garvey, M.Heinssen, R.Pine, D.S.Quinn, K.et al.Research domain criteria (RDoC): toward a new classification framework for research on mental disorders Am J Psychiatry 2010; 167(7): 748–751CrossRefGoogle Scholar
Ruhrmann, S.Schultze-Lutter, F.Salokangas, R.K.R.Heinimaa, M.Linszen, D.Dingemans, P.et al.Prediction of psychosis in adolescents and young adults at high risk: results from the prospective European prediction of psychosis study Arch Gen Psychiatry 2010; 67(3): 241–251CrossRefGoogle Scholar
Buchanan, R.W.Heinrichs, D.W.The Neurological Evaluation Scale (NES): a structured instrument for the assessment of neurological signs in schizophrenia. Psychiatry Res 1989; 27(3): 335–350CrossRefGoogle Scholar
Kay, S.R.Fiszbein, A.Opler, L.A.The Positive and Negative Syndrome Scale (PANSS) for schizophrenia. Schizophr Bull 1987; 13(2): 261–276CrossRefGoogle Scholar
Randolph, C.Tierney, M.C.Mohr, E.Chase, T.N.The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS): preliminary clinical validity J Clin Exp Neuropsychol 2010Google Scholar
Vellante, M.Baron-Cohen, S.Melis, M.Marrone, M.Petretto, D.R.Masala, C.et al.The “Reading the Mind in the Eyes” test: systematic review of psychometric properties and a validation study in Italy Cogn Neuropsychiatry 2013; 18(4): 326–354CrossRefGoogle Scholar
Stone, V.E.Baron-Cohen, S.Knight, R.T.Frontal lobe contributions to theory of mind. J Cogn Neurosci 1998; 10(5): 640–656CrossRefGoogle ScholarPubMed
Bosco, F.M.Colle, L.De Fazio, S.Bono, A.Ruberti, S.Tirassa, M.Th.o.m.a.s.: an exploratory assessment of Theory of Mind in schizophrenic subjects Conscious Cogn 2009CrossRefGoogle Scholar
Rosen, A.Hadzi-pavlovic, D.Parker, G.The life skills profile: a measure assessing function and disability in schizophrenia Schizophr Bull 1989CrossRefGoogle Scholar
Hajebi, A.Motevalian, A.Amin-Esmaeili, M.Hefazi, M.Radgoodarzi, R.Rahimi-Movaghar, A.et al.Telephone versus face-to-face administration of the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, for diagnosis of psychotic disorders Compr Psychiatry 2012; 53(5): 579–583CrossRefGoogle ScholarPubMed
Cannon, T.D.Cadenhead, K.Cornblatt, B.Woods, S.W.Addington, J.Walker, E.et al.Prediction of psychosis in youth at high clinical risk: a multisite longitudinal study in North America. Arch Gen Psychiatry 2008; 65(January (1)):28–37CrossRefGoogle ScholarPubMed
Meyer, E.C.Carrión, R.E.Cornblatt, B.A.Addington, J.Cadenhead, K.S.Cannon, T.D.et al.The relationship of neurocognition and negative symptoms to social and role functioning over time in individuals at clinical high risk in the first phase of the North American Prodrome Longitudinal Study Schizophr Bull 2014; 40(6): 1452–1461CrossRefGoogle ScholarPubMed
Chan, R.C.K.Wang, Y.Wang, L.Chen, E.Y.H.Manschreck, T.C.Li, Z.et al.Neurological soft signs and their relationships to neurocognitive functions: a re-visit with the structural equation modeling design. PLoS ONE 2009; 4(12):e8469CrossRefGoogle ScholarPubMed
Hosmer, D.W. Jr.Lemeshow, S.Sturdivant, R.X.Applied logistic regression [Internet] Hoboken, NJ, USA: John Wiley & Sons, Inc.; 2013CrossRefGoogle Scholar
Sauerbrei, W.Schumacher, M.A bootstrap resampling procedure for model building: application to the Cox regression model. Stat Med 1992; 11(16): 2093–2109CrossRefGoogle ScholarPubMed
Lin, A.Yung, A.R.Nelson, B.Brewer, W.J.Riley, R.Simmons, M.et al.Neurocognitive predictors of transition to psychosis: medium- to long-term findings from a sample at ultra-high risk for psychosis. Psychol Med 2013; 43(11): 2349–2360CrossRefGoogle ScholarPubMed
Giuliano, A.J.Li, H.Mesholam-Gately, R.I.Sorenson, S.M.Woodberry, K.A.Seidman, L.J.Neurocognition in the psychosis risk syndrome: a quantitative and qualitative review. Curr Pharm Des 2012; 18(4): 399–415CrossRefGoogle ScholarPubMed
Ilonen, T.Heinimaa, M.Korkeila, J.Svirskis, T.Salokangas, R.K.R.Differentiating adolescents at clinical high risk for psychosis from psychotic and non-psychotic patients with the Rorschach. Psychiatry Res 2010; 179(2): 151–156CrossRefGoogle ScholarPubMed
Lindgren, M.Manninen, M.Laajasalo, T.Mustonen, U.Kalska, H.Suvisaari, J.et al.The relationship between psychotic-like symptoms and neurocognitive performance in a general adolescent psychiatric sample. Schizophr Res 2010; 123(1): 77–85CrossRefGoogle Scholar
Fusar-Poli, P.Deste, G.Smieskova, R.Barlati, S.Yung, A.R.Howes, O.et al.Cognitive functioning in prodromal psychosis: a meta-analysis. Arch Gen Psychiatry 2012; 69(6): 562–571CrossRefGoogle ScholarPubMed
Kim, H.S.Shin, N.Y.Jang, J.H.Kim, E.Shim, G.Park, H.Y.et al.Social cognition and neurocognition as predictors of conversion to psychosis in individuals at ultra-high risk. Schizophr Res 2011; 130(August (1–3)):170–175CrossRefGoogle ScholarPubMed
Van Overwalle, F.Baetens, K.Understanding others’ actions and goals by mirror and mentalizing systems: a meta-analysis. Neuroimage 2009; 48(3): 564–584CrossRefGoogle ScholarPubMed
Zhao, Q.Li, Z.Huang, J.Yan, C.Dazzan, P.Pantelis, C.et al.Neurological soft signs are not “soft” in brain structure and functional networks: evidence from ALE meta-analysis. Schizophr Bull 2014; 40(May (3)):626–641CrossRefGoogle Scholar
Tanaka, S.Modality-specific cognitive function of medial and lateral human Brodmann area 6. J Neurosci 2005; 25(2): 496–501CrossRefGoogle ScholarPubMed
Herold, R.Feldmann, A.Simon, M.Tényi, T.Kövér, F.Nagy, F.et al.Regional gray matter reduction and theory of mind deficit in the early phase of schizophrenia: a voxel-based morphometric study. Acta Psychiatr Scand 2009; 119(3): 199–208CrossRefGoogle ScholarPubMed
Corcoran, C.M.Keilp, J.G.Kayser, J.Klim, C.Butler, P.D.Bruder, G.E.et al.Emotion recognition deficits as predictors of transition in individuals at clinical high risk for schizophrenia: a neurodevelopmental perspective. Psychol Med 2015; 45(14): 2959–2973CrossRefGoogle ScholarPubMed
Cornblatt, B.A.Lencz, T.Smith, C.W.Olsen, R.Auther, A.M.Nakayama, E.et al.Can antidepressants be used to treat the schizophrenia prodrome? Results of a prospective, naturalistic treatment study of adolescents. J Clin Psychiatry 2007; 68(4): 546–557CrossRefGoogle ScholarPubMed
Supplementary material: File

Francesconi et al. supplementary material

Supplementary materials

Download Francesconi et al. supplementary material(File)
File 130.2 KB
Submit a response

Comments

No Comments have been published for this article.