Progression from being at-risk to psychosis: next steps.


Journal

NPJ schizophrenia
ISSN: 2334-265X
Titre abrégé: NPJ Schizophr
Pays: United States
ID NLM: 101657919

Informations de publication

Date de publication:
05 Oct 2020
Historique:
received: 08 02 2020
accepted: 06 08 2020
entrez: 6 10 2020
pubmed: 7 10 2020
medline: 7 10 2020
Statut: epublish

Résumé

Over the past 20 years there has been a great deal of research into those considered to be at risk for developing psychosis. Much has been learned and studies have been encouraging. The aim of this paper is to offer an update of the current status of research on risk for psychosis, and what the next steps might be in examining the progression from CHR to psychosis. Advances have been made in accurate prediction, yet there are some methodological issues in ascertainment, diagnosis, the use of data-driven selection methods and lack of external validation. Although there have been several high-quality treatment trials the heterogeneity of this clinical high-risk population has to be addressed so that their treatment needs can be properly met. Recommendations for the future include more collaborative research programmes, and ensuring they are accessible and harmonized with respect to criteria and outcomes so that the field can continue to move forward with the development of large collaborative consortiums as well as increased funding for multisite projects.

Identifiants

pubmed: 33020486
doi: 10.1038/s41537-020-00117-0
pii: 10.1038/s41537-020-00117-0
pmc: PMC7536226
doi:

Types de publication

Journal Article Review

Langues

eng

Pagination

27

Références

McGlashan, T., Walsh, B. & Woods, S. The Psychosis-Risk Syndrome: Handbook for Diagnosis and Follow-up (Oxford University Press, 2010).
Yung, A. R. et al. Mapping the onset of psychosis: the comprehensive assessment of at-risk mental states. Aust. N. Z. J. Psychiatry 39, 964–971 (2005).
pubmed: 16343296 doi: 10.1080/j.1440-1614.2005.01714.x
Fusar-Poli, P. et al. Predicting psychosis: meta-analysis of transition outcomes in individuals at high clinical risk. Arch. Gen. Psychiatry 69, 220–229 (2012).
pubmed: 22393215 doi: 10.1001/archgenpsychiatry.2011.1472
Cannon, T. et al. Prediction of psychosis in youth at high clinical risk: a multisite longitudinal study in North America. Arch. Gen. Psychiatry 65, 28–37 (2008).
pubmed: 18180426 pmcid: 3065347 doi: 10.1001/archgenpsychiatry.2007.3
Addington, J. et al. Clinical and functional characteristics of youth at clinical high-risk for psychosis who do not transition to psychosis. Psychol. Med. 49, 1670–1677 (2018).
pubmed: 30176955 doi: 10.1017/S0033291718002258
Lin, A. et al. Outcomes of nontransitioned cases in a sample at ultra-high risk for psychosis. Am. J. Psychiatry 172, 249–258 (2015).
pubmed: 25727537 doi: 10.1176/appi.ajp.2014.13030418
Addington, J. et al. Predictors of transition to psychosis in individuals at clinical high risk. Curr. Psychiatry Rep. 21, 39 (2019).
pubmed: 31037392 doi: 10.1007/s11920-019-1027-y
Studerus, E., Ramyead, A. & Riecher-Rossler, A. Prediction of transition to psychosis in patients with a clinical high risk for psychosis: a systematic review of methodology and reporting. Psychol. Med. 47, 1163–1178 (2017).
pubmed: 28091343 doi: 10.1017/S0033291716003494
Riecher-Rossler, A. & Studerus, E. Prediction of conversion to psychosis in individuals with an at-risk mental state: a brief update on recent developments. Curr. Opin. Psychiatry 30, 209–219 (2017).
pubmed: 28212173 doi: 10.1097/YCO.0000000000000320
Fusar-Poli, P. et al. Disorder, not just state of risk: meta-analysis of functioning and quality of life in people at high risk of psychosis. Br. J. Psychiatry 207, 198–206 (2015).
pubmed: 26329563 doi: 10.1192/bjp.bp.114.157115
Carrion, R. E. et al. The global functioning: social and role scales-further validation in a large sample of adolescents and young adults at clinical high risk for psychosis. Schizophr. Bull. 45, 763–772 (2019).
pubmed: 30351423 doi: 10.1093/schbul/sby126
Cornblatt, B. et al. Risk factors for psychosis: impaired social and role functioning. Schizophr. Bull. 38, 1247–1257 (2012).
pubmed: 22080497 doi: 10.1093/schbul/sbr136
Koutsouleris, N. et al. Prediction models of functional outcomes for individuals in the clinical high-risk state for psychosis or with recent-onset depression: a multimodal, multisite machine learning analysis. JAMA Psychiatry 75, 1156–1172 (2018).
pubmed: 30267047 pmcid: 6248111 doi: 10.1001/jamapsychiatry.2018.2165
Cannon, T. et al. Progressive reduction in cortical thickness as psychosis develops: a multisite longitudinal neuroimaging study of youth at elevated clinical risk. Biol. Psychiatry 77, 147–157 (2015).
pubmed: 25034946 doi: 10.1016/j.biopsych.2014.05.023
Chung, Y. et al. Use of machine learning to determine deviance in neuroanatomical maturity associated with future psychosis in youths at clinically high risk. JAMA Psychiatry 75, 960–968 (2018).
pubmed: 29971330 pmcid: 6142910 doi: 10.1001/jamapsychiatry.2018.1543
Zarogianni, E. et al. Individualized prediction of psychosis in subjects with an at-risk mental state. Schizophr. Res. 214, 18–23 (2019).
pubmed: 28935170 doi: 10.1016/j.schres.2017.08.061
Zarogianni, E., Storkey, A. J., Johnstone, E. C., Owens, D. G. C. & Lawrie, S. M. Improved individualized prediction of schizophrenia in subjects at familial high risk, based on neuroanatomical data, schizotypal and neurocognitive features. Schizophr. Res. 181, 6–12 (2017).
pubmed: 27613509 doi: 10.1016/j.schres.2016.08.027
Cao, H. et al. Cerebello-thalamo-cortical hyperconnectivity as a state-independent functional neural signature for psychosis prediction and characterization. Nat. Commun. 9, 3836 (2018).
pubmed: 30242220 pmcid: 6155100 doi: 10.1038/s41467-018-06350-7
Bernard, J. A., Orr, J. M. & Mittal, V. A. Cerebello-thalamo-cortical networks predict positive symptom progression in individuals at ultra-high risk for psychosis. NeuroImage Clin. 14, 622–628 (2017).
pubmed: 28348953 pmcid: 5357699 doi: 10.1016/j.nicl.2017.03.001
Anticevic, A. et al. Association of thalamic dysconnectivity and conversion to psychosis in youth and young adults at elevated clinical risk. JAMA Psychiatry 72, 882–891 (2015).
pubmed: 26267151 pmcid: 4892891 doi: 10.1001/jamapsychiatry.2015.0566
Bodatsch, M., Brockhaus-Dumke, A., Klosterkotter, J. & Ruhrmann, S. Forecasting psychosis by event-related potentials-systematic review and specific meta-analysis. Biol. Psychiatry 77, 951–958 (2015).
pubmed: 25636178 doi: 10.1016/j.biopsych.2014.09.025
van Tricht, M. J. et al. Auditory ERP components before and after transition to a first psychotic episode. Biol. Psychol. 87, 350–357 (2011).
pubmed: 21536095 doi: 10.1016/j.biopsycho.2011.04.005
Hamilton, H. K. et al. Association between P300 responses to auditory Oddball stimuli and clinical outcomes in the psychosis risk syndrome. JAMA Psychiatry https://doi.org/10.1001/jamapsychiatry.2019.2135 (2019).
Focking, M. et al. Differential expression of the inflammation marker IL12p40 in the at-risk mental state for psychosis: a predictor of transition to psychotic disorder? BMC Psychiatry 16, 326 (2016).
pubmed: 27650124 pmcid: 5029014 doi: 10.1186/s12888-016-1039-7
Perkins, D. O. et al. Towards a psychosis risk blood diagnostic for persons experiencing high-risk symptoms: preliminary results from the NAPLS project. Schizophr. Bull. 41, 419–428 (2015).
pubmed: 25103207 doi: 10.1093/schbul/sbu099
Chaumette, B. et al. Salivary cortisol in early psychosis: new findings and meta-analysis. Psychoneuroendocrinology 63, 262–270 (2016).
pubmed: 26520686 doi: 10.1016/j.psyneuen.2015.10.007
Riecher-Rossler, A. Oestrogens, prolactin, hypothalamic-pituitary-gonadal axis, and schizophrenic psychoses. Lancet Psychiatry 4, 63–72 (2017).
pubmed: 27856396 doi: 10.1016/S2215-0366(16)30379-0
Perkins, D. O. et al. Polygenic risk score contribution to psychosis prediction in a target population of persons at clinical high risk. Am. J. Psychiatry 177, 155–163 (2020).
pubmed: 31711302 doi: 10.1176/appi.ajp.2019.18060721
Hengartner, M. P. et al. Course of psychotic symptoms, depression and global functioning in persons at clinical high risk of psychosis: Results of a longitudinal observation study over three years focusing on both converters and non-converters. Schizophr. Res. 189, 19–26 (2017).
pubmed: 28139360 doi: 10.1016/j.schres.2017.01.040
Ising, H. K. et al. Development of a stage-dependent prognostic model to predict psychosis in ultra-high-risk patients seeking treatment for co-morbid psychiatric disorders. Psychol. Med. 46, 1839–1851 (2016).
pubmed: 26979398 doi: 10.1017/S0033291716000325
Metzler, S. et al. Neurocognition in help-seeking individuals at risk for psychosis: prediction of outcome after 24 months. Psychiatry Res. 246, 188–194 (2016).
pubmed: 27718468 doi: 10.1016/j.psychres.2016.08.065
Cornblatt, B. A. et al. Psychosis prevention: a modified clinical high risk perspective from the recognition and prevention (RAP) program. Am. J. Psychiatry 172, 986–994 (2015).
pubmed: 26046336 pmcid: 4993209 doi: 10.1176/appi.ajp.2015.13121686
Addington, J. et al. The role of cognition and social functioning as predictors in the transition to psychosis for youth with attenuated psychotic symptoms. Schizophr. Bull. 43, 57–63 (2017).
pubmed: 27798225 doi: 10.1093/schbul/sbw152
Clark, S. R. et al. Prediction of transition from ultra-high risk to first-episode psychosis using a probabilistic model combining history, clinical assessment and fatty-acid biomarkers. Transl. Psychiatry 6, e897 (2016).
pubmed: 27648919 pmcid: 5048208 doi: 10.1038/tp.2016.170
Cannon, T. et al. An individualized risk calculator for research in prodromal psychosis. Am. J. Psychiatry 173, 980–988 (2016).
pubmed: 27363508 pmcid: 5048498 doi: 10.1176/appi.ajp.2016.15070890
Carrión, R. E. et al. Personalized prediction of psychosis: external validation of the NAPLS2 psychosis risk calculator with the EDIPPP project. Am. J. Psychiatry 173, 989–996 (2017).
doi: 10.1176/appi.ajp.2016.15121565
Kattan, M. W., Yu, C., Stephenson, A. J., Sartor, O. & Tombal, B. Clinicians versus nomogram: predicting future technetium-99m bone scan positivity in patients with rising prostate-specific antigen after radical prostatectomy for prostate cancer. Urology 81, 956–961 (2013).
pubmed: 23375915 doi: 10.1016/j.urology.2012.12.010
Lee, T. H. et al. Derivation and prospective validation of a simple index for prediction of cardiac risk of major noncardiac surgery. Circulation 100, 1043–1049 (1999).
pubmed: 10477528 doi: 10.1161/01.CIR.100.10.1043
Pfeiffer, R. M. et al. Risk prediction for breast, endometrial, and ovarian cancer in white women aged 50 y or older: derivation and validation from population-based cohort studies. PLoS Med. 10, e1001492 (2013).
pubmed: 23935463 pmcid: 3728034 doi: 10.1371/journal.pmed.1001492
Ross, P. L. et al. Comparisons of nomograms and urologists’ predictions in prostate cancer. Semin. Urol. Oncol. 20, 82–88 (2002).
pubmed: 12012293 doi: 10.1053/suro.2002.32490
Fusar-Poli, P. et al. The dark side of the moon: meta-analytical impact of recruitment strategies on risk enrichment in the clinical high risk state for psychosis. Schizophr. Bull. 42, 732–743 (2016).
pubmed: 26591006 doi: 10.1093/schbul/sbv162
Steyerberg, E. W. Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating (Springer Science & Business Media, 2008).
Studerus, E., Papmeyer, M. & Riecher-Rössler, A. in Early Detection and Intervention in Psychosis Vol. 181, pp. 116–132 (Karger Publishers, 2016).
Yuen, H. P. & Mackinnon, A. Performance of joint modelling of time-to-event data with time-dependent predictors: an assessment based on transition to psychosis data. PeerJ 4, e2582 (2016).
pubmed: 27781169 pmcid: 5075698 doi: 10.7717/peerj.2582
Yuen, H. P., Mackinnon, A. & Nelson, B. A new method for analysing transition to psychosis: joint modelling of time-to-event outcome with time-dependent predictors. Int. J. Methods Psychiatr. Res. https://doi.org/10.1002/mpr.1588 (2018).
Studerus, E., Beck, K., Fusar-Poli, P. & Riecher-Rossler, A. Development and validation of a dynamic risk prediction model to forecast psychosis onset in patients at clinical high risk. Schizophr. Bull. https://doi.org/10.1093/schbul/sbz059 (2019).
Oliver, D. et al. What causes the onset of psychosis in individuals at clinical high risk? A meta-analysis of risk and protective factors. Schizophr. Bull. 46, 110–120 (2020).
pubmed: 31219164 doi: 10.1093/schbul/sbz039
Radua, J. et al. What causes psychosis? An umbrella review of risk and protective factors. World Psychiatry 17, 49–66 (2018).
pubmed: 29352556 pmcid: 5775150 doi: 10.1002/wps.20490
Oliver, D., Radua, J., Reichenberg, A., Uher, R. & Fusar-Poli, P. Psychosis polyrisk score (PPS) for the detection of individuals at-risk and the prediction of their outcomes. Front Psychiatry 10, 174 (2019).
pubmed: 31057431 pmcid: 6478670 doi: 10.3389/fpsyt.2019.00174
Addington, J., Devoe, D. J. & Santesteban-Echarri, O. Multidisciplinary treatment for individuals at clinical high risk of developing psychosis. Curr. Treat. Options Psychiatry 6, 1–16 (2019).
pubmed: 31403023 pmcid: 6688178 doi: 10.1007/s40501-019-0164-6
Morrison, A. P. et al. Cognitive therapy for the prevention of psychosis in people at ultra-high risk. Randomised controlled trial. Br. J. Psychiatry 185, 291–297 (2004).
pubmed: 15458988 doi: 10.1192/bjp.185.4.291
Morrison, A. P. et al. Early detection and intervention evaluation for people at risk of psychosis: multisite randomised controlled trial. BMJ 344, 1–14 (2012).
Ising, H. K. et al. Four-year follow-up of cognitive behavioral therapy in persons at ultra-high risk for developing psychosis: the Dutch Early Detection Intervention Evaluation (EDIE-NL) trial. Schizophr. Bull. 42, 124–152 (2016).
doi: 10.1093/schbul/sbw018
Van Der Gaag, M. et al. Cognitive behavioral therapy for subjects at ultra high risk for developing psychosis: a randomized controlled clinical trial. Schizophr. Bull. 38, 1180–1188 (2012).
pubmed: 22941746 pmcid: 3494039 doi: 10.1093/schbul/sbs105
Addington, J. et al. A randomized controlled trial of cognitive behavioral therapy for individuals at clinical high risk of psychosis. Schizophr. Res. 125, 54–61 (2011).
pubmed: 21074974 doi: 10.1016/j.schres.2010.10.015
Stain, H. J. et al. A randomised controlled trial of cognitive behaviour therapy versus non-directive reflective listening for young people at ultra high risk of developing psychosis: The detection and evaluation of psychological therapy (DEPTh) trial. Schizophr. Res. J. 176, 212–219 (2016).
doi: 10.1016/j.schres.2016.08.008
Miklowitz, D. J. et al. Family-focused treatment for adolescents and young adults at high risk for psychosis: results of a randomized trial. J. Am. Acad. Child Adolesc. Psychiatry 53, 848–858 (2014).
pubmed: 25062592 pmcid: 4112074 doi: 10.1016/j.jaac.2014.04.020
Bechdolf, A. et al. Preventing progression to first-episode psychosis in early initial prodromal states. Br. J. Psychiatry 200, 22–29 (2012).
pubmed: 22075649 doi: 10.1192/bjp.bp.109.066357
Woods, S. et al. Glycine treatment of the risk syndrome for psychosis: report of two pilot studies. Eur. Neuropsychopharmacol. 23, 931–940 (2013).
pubmed: 23089076 doi: 10.1016/j.euroneuro.2012.09.008
Kantrowitz, J. T. et al. “D-serine for the treatment of negative symptoms in individuals at clinical high risk of schizophrenia: a pilot, double-blind, placebo-controlled, randomised parallel group mechanistic proof-of-concept trial”: Correction. Lancet Psychiatry 3, 602 (2016).
doi: 10.1016/S2215-0366(16)30134-1
McGlashan, T. H. et al. Randomized, double-blind trial of olanzapine versus placebo in patients prodromally symptomatic for psychosis. Am. J. Psychiatry 163, 790–799 (2006).
pubmed: 16648318 doi: 10.1176/ajp.2006.163.5.790
McGorry, P. D. et al. Randomized controlled trial of interventions designed to reduce the risk of progression to first-episode psychosis in a clinical sample with subthreshold symptoms. Arch. Gen. Psychiatry 59, 921–928 (2002).
pubmed: 12365879 doi: 10.1001/archpsyc.59.10.921
Ruhrmann, S. et al. Acute effects of treatment for prodromal symptoms for people putatively in a late initial prodromal state of psychosis. Br. J. Psychiatry 191, s88–s95 (2007).
doi: 10.1192/bjp.191.51.s88
McGorry, P. N. B. et al. Randomized controlled trial of interventions for young people at ultra-high risk of psychosis: twelve-month outcome. J. Clin. psychiatry 74, 349–356 (2013).
pubmed: 23218022 doi: 10.4088/JCP.12m07785
Woods, S. et al. Effects of ziprasidone versus placebo in patients at clinical high risk for psychosis. Schizophr. Bull. 43, S58 (2017).
Amminger, G. P. et al. Long-chain omega-3 fatty acids for indicated prevention of psychotic disorders: a randomized, placebo-controlled trial. Arch. Gen. Psychiatry 67, 146–154 (2010).
pubmed: 20124114 doi: 10.1001/archgenpsychiatry.2009.192
Cadenhead, K. et al. 23. omega-3 fatty acid versus placebo in a clinical high-risk sample from the North American Prodrome Longitudinal Studies (NAPLS) consortium. Schizophr. Bull. 43, S16–S16 (2017).
pmcid: 5475494 doi: 10.1093/schbul/sbx021.042 pubmed: 5475494
McGorry, P. et al. Effect of omega-3 polyunsaturated fatty acids in young people at ultrahigh risk for psychotic disorders: The NEURAPRO randomized clinical trial. JAMA Psychiatry 74, 19–27 (2017).
pubmed: 27893018 doi: 10.1001/jamapsychiatry.2016.2902
Davies, C. et al. Lack of evidence to favor specific preventive interventions in psychosis: a network meta‐analysis. World Psychiatry 17, 196–209 (2018).
pubmed: 29856551 pmcid: 5980552 doi: 10.1002/wps.20526
Devoe, D., Farris, M., Townes, P. & Addington, J. Interventions and transition in youth at risk of psychosis: a systematic review and meta-analysis. J. Clin. Psychiatry 81, 17r12053 PMID 32433834.
Devoe, D. J., Farris, M. S., Townes, P. & Addington, J. Interventions and social functioning in youth at risk of psychosis: a systematic review and meta-analysis. Early Interv. Psychiatry https://doi.org/10.1111/eip.12689 (2018).
Devoe, D. J., Farris, M. S., Townes, P. & Addington, J. Attenuated psychotic symptom interventions in youth at risk of psychosis: a systematic review and meta-analysis. Early Interv. Psychiatry https://doi.org/10.1111/eip.12677 (2018).
Davies, C. et al. Efficacy and acceptability of interventions for attenuated positive psychotic symptoms in individuals at clinical high risk of psychosis: a network meta-analysis. Front. Psychiatry 9, 187 (2018).
pubmed: 29946270 pmcid: 6005890 doi: 10.3389/fpsyt.2018.00187
Devoe, D. J., Peterson, A. & Addington, J. Negative symptom interventions in youth at risk of psychosis: a systematic review and network meta-analysis. Schizophr. Bull. https://doi.org/10.1093/schbul/sbx139 (2017).
Lin, L., Xing, A., Kofler, M. J. & Murad, M. H. Borrowing of strength from indirect evidence in 40 network meta-analyses. J. Clin. Epidemiol. 106, 41–49 (2019).
pubmed: 30342086 doi: 10.1016/j.jclinepi.2018.10.007
Bosnjak Kuharic, D., Kekin, I., Hew, J., Rojnic Kuzman, M. & Puljak, L. Interventions for prodromal stage of psychosis. Cochrane Database Syst. Rev. https://doi.org/10.1002/14651858.CD012236.pub2 (2019).
Davies, C. et al. Lack of evidence to favor specific preventive interventions in psychosis: a network meta‐analysis. World Psychiatry 17, 196–209 (2018).
pubmed: 29856551 pmcid: 5980552 doi: 10.1002/wps.20526
Nelson, B. et al. Evidence for preventive treatments in young patients at clinical high risk of psychosis: the need for context. Lancet Psychiatry https://doi.org/10.1016/s2215-0366(19)30513-9 (2019).
Bhattacharyya, S. et al. Effect of cannabidiol on medial temporal, midbrain, and striatal dysfunction in people at clinical high risk of psychosis: a randomized clinical trial. JAMA Psychiatry 75, 1107–1117 (2018).
pubmed: 30167644 pmcid: 6248101 doi: 10.1001/jamapsychiatry.2018.2309
Davies, C. et al. Oxytocin modulates hippocampal perfusion in people at clinical high risk for psychosis. Neuropsychopharmacology 44, 1300–1309 (2019).
pubmed: 30626906 pmcid: 6784972 doi: 10.1038/s41386-018-0311-6
Shi, J. et al. Systemic therapy for youth at clinical high risk for psychosis: a pilot study. Front. Psychiatry 8, 211 (2017).
pubmed: 29104547 pmcid: 5655006 doi: 10.3389/fpsyt.2017.00211
Yung, A. R. et al. Declining transition rate in ultra high risk (prodromal) services: dilution or reduction of risk? Schizophr. Bull. 33, 673–681 (2007).
pubmed: 17404389 pmcid: 2526154 doi: 10.1093/schbul/sbm015
Addington, J. et al. North American prodrome longitudinal study (NAPLS 2): the prodromal symptoms. J. Nerv. Ment. Dis. 203, 328–335 (2015).
pubmed: 25919383 pmcid: 4417745 doi: 10.1097/NMD.0000000000000290
Nelson, B., Amminger, G. P. & McGorry, P. D. Recent meta-analyses in the clinical high risk for psychosis population: clinical interpretation of findings and suggestions for future research. Front. Psychiatry https://doi.org/10.3389/fpsyt.2018.00502 (2018).
Fusar-Poli, P. et al. Towards a standard psychometric diagnostic interview for subjects at ultra high risk of psychosis: CAARMS versus SIPS. Psychiatry J. 2016, 7146341 (2016).
pubmed: 27314005 pmcid: 4904115 doi: 10.1155/2016/7146341
Fusar-Poli, P., Nelson, B., Valmaggia, L., Yung, A. R. & McGuire, P. K. Comorbid depressive and anxiety disorders in 509 individuals with an at-risk mental state: impact on psychopathology and transition to psychosis. Schizophr. Bull. 40, 120–131 (2014).
pubmed: 23180756 doi: 10.1093/schbul/sbs136
McAusland, L. et al. Anxiety in youth at clinical high risk for psychosis. Early Interv. Psychiatry 11, 480–487 (2017).
pubmed: 26456932 doi: 10.1111/eip.12274
Addington, J. et al. Comorbid diagnoses for youth at clinical high risk of psychosis. Schizophr. Res. 190, 90–95 (2017).
pubmed: 28372906 pmcid: 5731830 doi: 10.1016/j.schres.2017.03.043
Piskulic, D. et al. Negative symptoms in individuals at clinical high risk of psychosis. Psychiatry Res. 196, 220–224 (2012).
pubmed: 22445704 pmcid: 4119605 doi: 10.1016/j.psychres.2012.02.018
Alderman, T. et al. Negative symptoms and impaired social functioning predict later psychosis in Latino youth at clinical high risk in the North American Prodromal Longitudinal Studies consortium. Early Interv. Psychiatry 9, 467–475 (2015).
pubmed: 24576057 doi: 10.1111/eip.12128
Lam, M. et al. Baseline social amotivation predicts 1-year functioning in UHR subjects: a validation and prospective investigation. Eur. Neuropsychopharmacol. 25, 2187–2196 (2015).
pubmed: 26553972 doi: 10.1016/j.euroneuro.2015.10.007
Devoe, D. et al. Persistent negative symptoms in youth at clinical high risk for psychosis: a longitudinal study. Schizophr. Res. https://doi.org/10.1016/j.schres.2020.04.004 (2020). PMID 32362460.
Seidman, L. J. et al. Association of neurocognition with transition to psychosis: baseline functioning in the second phase of the North American prodrome longitudinal study. JAMA Psychiatry 73, 1239–1248 (2016).
pubmed: 27806157 pmcid: 5511703 doi: 10.1001/jamapsychiatry.2016.2479
Addington, J. & Barbato, M. The role of cognitive functioning in the outcome of those at clinical high risk for developing psychosis. Epidemiol. Psychiatr. Sci. 21, 335–342 (2012).
pubmed: 23174394 pmcid: 6998133 doi: 10.1017/S204579601200042X
Farris, M. S., Shakeel, M. K. & Addington, J. Cannabis use in individuals at clinical high-risk for psychosis: a comprehensive review. Soc. Psychiatry Psychiatr. Epidemiol. https://doi.org/10.1007/s00127-019-01810-x (2019).
doi: 10.1007/s00127-019-01810-x pubmed: 31796983
Addington, J. et al. At clinical high risk for psychosis: outcome for nonconverters. Am. J. Psychiatry 168, 800–805 (2011).
pubmed: 21498462 pmcid: 3150607 doi: 10.1176/appi.ajp.2011.10081191
Lee, T. Y. et al. Symptomatic and functional remission of subjects at clinical high risk for psychosis: a 2-year naturalistic observational study. Schizophr. Res. 156, 266–271 (2014).
pubmed: 24815568 doi: 10.1016/j.schres.2014.04.002
Woods, S. W. et al. Lack of diagnostic pluripotentiality in patients at clinical high risk for psychosis: specificity of comorbidity persistence and search for pluripotential subgroups. Schizophr. Bull. 44, 254–263 (2018).
pubmed: 29036402 doi: 10.1093/schbul/sbx138
Allswede, D. M. et al. Characterizing covariant trajectories of individuals at clinical high risk for psychosis across symptomatic and functional domains. Am. J. Psychiatry https://doi.org/10.1176/appi.ajp.2019.18111290 (2019).
Healey, K. M. et al. Latent profile analysis and conversion to psychosis: characterizing subgroups to enhance risk prediction. Schizophr. Bull. 44, 286–296 (2018).
pubmed: 29036587 doi: 10.1093/schbul/sbx080
McGorry, P. D., Hartmann, J. A., Spooner, R. & Nelson, B. Beyond the “at risk mental state” concept: transitioning to transdiagnostic psychiatry. World Psychiatry 17, 133–142 (2018).
pubmed: 29856558 pmcid: 5980504 doi: 10.1002/wps.20514
Lieberman, J. A., Small, S. A. & Girgis, R. R. Early detection and preventive intervention in schizophrenia: from fantasy to reality. Am. J. Psychiatry 176, 794–810 (2019).
pubmed: 31569988 doi: 10.1176/appi.ajp.2019.19080865
Schultze-Lutter, F. et al. Duration of unspecific prodromal and clinical high risk states, and early help-seeking in first-admission psychosis patients. Soc. Psychiatry Psychiatr. Epidemiol. 50, 1831–1841 (2015).
pubmed: 26155901 doi: 10.1007/s00127-015-1093-3
Shah, J. L. et al. Is the clinical high-risk state a valid concept? retrospective examination in a first-episode psychosis sample. Psychiatr. Serv. 68, 1046–1052 (2017).
pubmed: 28617204 doi: 10.1176/appi.ps.201600304
van Os, J. & Guloksuz, S. A critique of the “ultra-high risk” and “transition” paradigm. World Psychiatry 16, 200–206 (2017).
pubmed: 28498576 pmcid: 5428198 doi: 10.1002/wps.20423
Ajnakina, O., David, A. S. & Murray, R. M. ‘At risk mental state’ clinics for psychosis—an idea whose time has come—and gone! Psychol. Med. https://doi.org/10.1017/s0033291718003859 (2018).
Moritz, S., Gaweda, L., Heinz, A. & Gallinat, J. Early detection. A defense of our statement that we should not catastrophize a future we cannot reliably predict nor change. A plea for a faster transition of traditional ‘early intervention’ programs for psychosis into new treatment models. Psychol. Med. https://doi.org/10.1017/s0033291719003477 (2019).
Yung, A. R. et al. The reality of at risk mental state services: a response to recent criticisms. Psychol. Med. https://doi.org/10.1017/s003329171900299x (2019).
Addington, J. et al. North American Prodrome Longitudinal Study (NAPLS 2): overview and recruitment. Schizophr. Res. 142, 77–82 (2012).
pubmed: 23043872 pmcid: 3502644 doi: 10.1016/j.schres.2012.09.012
Satterthwaite, T. D. et al. The Philadelphia Neurodevelopmental Cohort: a publicly available resource for the study of normal and abnormal brain development in youth. Neuroimage 124, 1115–1119 (2016).
pubmed: 25840117 doi: 10.1016/j.neuroimage.2015.03.056

Auteurs

Jean Addington (J)

Hotchkiss Brain Institute, Department of Psychiatry, University of Calgary, Calgary, AB, Canada. jmadding@ucalgary.ca.

Megan Farris (M)

Hotchkiss Brain Institute, Department of Psychiatry, University of Calgary, Calgary, AB, Canada.

Daniel Devoe (D)

Hotchkiss Brain Institute, Department of Psychiatry, University of Calgary, Calgary, AB, Canada.

Paul Metzak (P)

Hotchkiss Brain Institute, Department of Psychiatry, University of Calgary, Calgary, AB, Canada.

Classifications MeSH