Hostname: page-component-54dcc4c588-rz4zl Total loading time: 0 Render date: 2025-10-06T20:05:28.823Z Has data issue: false hasContentIssue false
  • English
  • Français

Poor functional recovery is better predicted than conversion in studies of outcomes of clinical high risk of psychosis: insight from SHARP

Published online by Cambridge University Press:  27 August 2019

TianHong Zhang ,
ShuWen Yang ,
LiHua Xu ,
XiaoChen Tang ,
YanYan Wei ,
HuiRu Cui ,
HuiJun Li ,
YingYing Tang ,
Li Hui  and
ChunBo Li
...Show all authors
TianHong Zhang
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
ShuWen Yang
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
LiHua Xu
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
XiaoChen Tang
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
YanYan Wei
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
HuiRu Cui
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
HuiJun Li
Affiliation:
Department of Psychology, Florida A&M University, Tallahassee, Florida32307, USA
YingYing Tang
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
Li Hui
Affiliation:
Institute of Mental Health, The Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou215137, Jiangsu, PR China
ChunBo Li
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China
XingShi Chen*
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China Institute of Mental Health, The Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou215137, Jiangsu, PR China
JiJun Wang*
Affiliation:
Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai200030, PR China Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai, PR China Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China
*
Author for correspondence: JiJun Wang, E-mail: jijunwang27@163.com; XingShi Chen, E-mail: chenxingshi2008@163.com
Author for correspondence: JiJun Wang, E-mail: jijunwang27@163.com; XingShi Chen, E-mail: chenxingshi2008@163.com
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Few of the previous studies of clinical high risk of psychosis (CHR) have explored whether outcomes other than conversion, such as poor functioning or treatment responses, are better predicted when using risk calculators. To answer this question, we compared the predictive accuracy between the outcome of conversion and poor functioning by using the NAPLS-2 risk calculator.

Methods

Three hundred CHR individuals were identified using the Chinese version of the Structured Interview for Prodromal Symptoms. Of these, 228 (76.0%) completed neurocognitive assessments at baseline and 199 (66.3%) had at least a 1-year follow-up assessment. The latter group was used in the NAPLS-2 risk calculator.

Results

We divided the sample into two broad categories based on different outcome definitions, conversion (n = 46) v. non-conversion (n = 153) or recovery (n = 138) v. poor functioning (n = 61). Interestingly, the NAPLS-2 risk calculator showed moderate discrimination of subsequent conversion to psychosis in this sample with an area under the receiver operating characteristic curve (AUC) of 0.631 (p = 0.007). However, for discriminating poor functioning, the AUC of the model increased to 0.754 (p < 0.001).

Conclusions

Our results suggest that the current risk calculator was a better fit for predicting a poor functional outcome and treatment response than it was in the prediction of conversion to psychosis.

Keywords

Follow-uppredictionrisk calculatortransitionultra-high risk

Information

Type
Original Articles
Information
Psychological Medicine , Volume 50 , Issue 9 , July 2020 , pp. 1578 - 1584
Copyright
Copyright © Cambridge University Press 2019

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.)

Article purchase

Temporarily unavailable

Footnotes

*

This author shares first authorship.

†

Co-corresponding author.

References

Addington, J, Cadenhead, KS, Cornblatt, BA, Mathalon, DH, McGlashan, TH, Perkins, DO, Seidman, LJ, Tsuang, MT, Walker, EF, Woods, SW, Addington, JA and Cannon, TD (2012) North American Prodrome Longitudinal Study (NAPLS 2): overview and recruitment. Schizophrenia Research 142, 77–82.CrossRefGoogle ScholarPubMed
Austin, SF, Mors, O, Secher, RG, Hjorthoj, CR, Albert, N, Bertelsen, M, Jensen, H, Jeppesen, P, Petersen, L, Randers, L, Thorup, A and Nordentoft, M (2013) Predictors of recovery in first episode psychosis: the OPUS cohort at 10 year follow-up. Schizophrenia Research 150, 163–168.CrossRefGoogle ScholarPubMed
Cannon, TD, Yu, C, Addington, J, Bearden, CE, Cadenhead, KS, Cornblatt, BA, Heinssen, R, Jeffries, CD, Mathalon, DH, McGlashan, TH, Perkins, DO, Seidman, LJ, Tsuang, MT, Walker, EF, Woods, SW and Kattan, MW (2016) An individualized risk calculator for research in prodromal psychosis. The American Journal of Psychiatry 173, 980–988.CrossRefGoogle ScholarPubMed
Carrion, RE, Cornblatt, BA, Burton, CZ, Tso, IF, Auther, AM, Adelsheim, S, Calkins, R, Carter, CS, Niendam, T, Sale, TG, Taylor, SF and McFarlane, WR (2016) Personalized prediction of psychosis: external validation of the NAPLS-2 psychosis risk calculator with the EDIPPP project. The American Journal of Psychiatry 173, 989–996.CrossRefGoogle ScholarPubMed
Cornblatt, BA, Carrion, RE, Auther, A, McLaughlin, D, Olsen, RH, John, M and Correll, CU (2015) Psychosis prevention: a modified clinical high risk perspective from the recognition and prevention (RAP) program. The American Journal of Psychiatry 172, 986–994.CrossRefGoogle ScholarPubMed
Fusar-Poli, P, Borgwardt, S, Bechdolf, A, Addington, J, Riecher-Rossler, A, Schultze-Lutter, F, Keshavan, M, Wood, S, Ruhrmann, S, Seidman, LJ, Valmaggia, L, Cannon, T, Velthorst, E, De Haan, L, Cornblatt, B, Bonoldi, I, Birchwood, M, McGlashan, T, Carpenter, W, McGorry, P, Klosterkotter, J, McGuire, P and Yung, A (2013) The psychosis high-risk state: a comprehensive state-of-the-art review. JAMA Psychiatry 70, 107–120.CrossRefGoogle ScholarPubMed
Hanley, JA and McNeil, BJ (1982) The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143, 29–36.CrossRefGoogle Scholar
Harrow, M, Jobe, TH and Faull, RN (2012) Do all schizophrenia patients need antipsychotic treatment continuously throughout their lifetime? A 20-year longitudinal study. Psychological Medicine 42, 2145–2155.CrossRefGoogle ScholarPubMed
Jones, SH, Thornicroft, G, Coffey, M and Dunn, G (1995) A brief mental health outcome scale-reliability and validity of the Global Assessment of Functioning (GAF). The British Journal of Psychiatry 166, 654–659.CrossRefGoogle Scholar
Keefe, RS, Goldberg, TE, Harvey, PD, Gold, JM, Poe, MP and Coughenour, L (2004) The brief assessment of cognition in schizophrenia: reliability, sensitivity, and comparison with a standard neurocognitive battery. Schizophrenia Research 68, 283–297.CrossRefGoogle ScholarPubMed
Kern, RS, Nuechterlein, KH, Green, MF, Baade, LE, Fenton, WS, Gold, JM, Keefe, RS, Mesholam-Gately, R, Mintz, J, Seidman, LJ, Stover, E and Marder, SR (2008) The MATRICS consensus cognitive battery, part 2: co-norming and standardization. The American Journal of Psychiatry 165, 214–220.CrossRefGoogle ScholarPubMed
Kern, RS, Gold, JM, Dickinson, D, Green, MF, Nuechterlein, KH, Baade, LE, Keefe, RS, Mesholam-Gately, RI, Seidman, LJ, Lee, C, Sugar, CA and Marder, SR (2011) The MCCB impairment profile for schizophrenia outpatients: results from the MATRICS psychometric and standardization study. Schizophrenia Research 126, 124–131.CrossRefGoogle ScholarPubMed
Liu, CC and Demjaha, A (2013) Antipsychotic interventions in prodromal psychosis: safety issues. CNS Drugs 27, 197–205.CrossRefGoogle ScholarPubMed
McGlashan, T, Walsh, B and Woods, S (2010). The Psychosis-Risk Syndrome: Handbook for Diagnosis and Follow-up. New York: Oxford University Press.Google Scholar
Miller, TJ, McGlashan, TH, Rosen, JL, Somjee, L, Markovich, PJ, Stein, K and Woods, SW (2002) Prospective diagnosis of the initial prodrome for schizophrenia based on the structured interview for prodromal syndromes: preliminary evidence of interrater reliability and predictive validity. The American Journal of Psychiatry 159, 863–865.CrossRefGoogle ScholarPubMed
Miller, TJ, McGlashan, TH, Rosen, JL, Cadenhead, K, Cannon, T, Ventura, J, McFarlane, W, Perkins, DO, Pearlson, GD and Woods, SW (2003) Prodromal assessment with the structured interview for prodromal syndromes and the scale of prodromal symptoms: predictive validity, interrater reliability, and training to reliability. Schizophrenia Bulletin 29, 703–715.CrossRefGoogle ScholarPubMed
Milne, BJ, Caspi, A, Crump, R, Poulton, R, Rutter, M, Sears, MR and Moffitt, TE (2009) The validity of the family history screen for assessing family history of mental disorders. American Journal of Medical Genetics. Part B, Neuropsychiatric Genetics 150, 41–49.CrossRefGoogle Scholar
Rosenbaum, B, Harder, S, Knudsen, P, Koster, A, Lindhardt, A, Lajer, M, Valbak, K and Winther, G (2012) Supportive psychodynamic psychotherapy versus treatment as usual for first-episode psychosis: two-year outcome. Psychiatry 75, 331–341.CrossRefGoogle ScholarPubMed
Roy, MA, Walsh, D and Kendler, KS (1996) Accuracies and inaccuracies of the family history method: a multivariate approach. Acta Psychiatrica Scandinavica 93, 224–234.CrossRefGoogle ScholarPubMed
Shapiro, AM, Benedict, RH, Schretlen, D and Brandt, J (1999) Construct and concurrent validity of the Hopkins Verbal Learning Test-revised. The Clinical Neuropsychologist 13, 348–358.CrossRefGoogle ScholarPubMed
Shi, C, He, Y, Cheung, EF, Yu, X and Chan, RC (2013) An ecologically valid performance-based social functioning assessment battery for schizophrenia. Psychiatry Research 210, 787–793.CrossRefGoogle Scholar
Simonsen, C, Faerden, A, Romm, KL, Berg, AO, Bjella, T, Sundet, K, Ueland, T, Andreassen, O and Melle, I (2017) Early clinical recovery in first-episode psychosis: symptomatic remission and its correlates at 1-year follow-up. Psychiatry Research 254, 118–125.CrossRefGoogle ScholarPubMed
Swets, JA (1988) Measuring the accuracy of diagnostic systems. Science 240, 1285–1293.CrossRefGoogle ScholarPubMed
van Os, J and Guloksuz, S (2017) A critique of the ‘ultra-high risk’ and ‘transition’ paradigm. World Psychiatry 16, 200–206.CrossRefGoogle Scholar
Zhang, T, Li, H, Woodberry, KA, Seidman, LJ, Zheng, L, Li, H, Zhao, S, Tang, Y, Guo, Q, Lu, X, Zhuo, K, Qian, Z, Chow, A, Li, C, Jiang, K, Xiao, Z and Wang, J (2014) Prodromal psychosis detection in a counseling center population in China: an epidemiological and clinical study. Schizophrenia Research 152, 391–399.CrossRefGoogle Scholar
Zhang, T, Li, H, Woodberry, KA, Seidman, LJ, Chow, A, Xiao, Z and Wang, J (2015) Interaction of social role functioning and coping in people with recent-onset attenuated psychotic symptoms: a case study of three Chinese women at clinical high risk for psychosis. Neuropsychiatric Disease and Treatment 11, 1647–1654.CrossRefGoogle ScholarPubMed
Zhang, TH, Li, HJ, Woodberry, KA, Xu, LH, Tang, YY, Guo, Q, Cui, HR, Liu, XH, Chow, A, Li, CB, Jiang, KD, Xiao, ZP, Seidman, LJ and Wang, JJ (2017) Two-year follow-up of a Chinese sample at clinical high risk for psychosis: timeline of symptoms, help-seeking and conversion. Epidemiology and Psychiatric Sciences, 26, 287–298.CrossRefGoogle ScholarPubMed
Zhang, T, Li, H, Tang, Y, Niznikiewicz, MA, Shenton, ME, Keshavan, MS, Stone, WS, McCarley, RW, Seidman, LJ and Wang, J (2018 a) Validating the predictive accuracy of the NAPLS-2 psychosis risk calculator in a clinical high-risk sample from the SHARP (Shanghai At Risk for Psychosis) program. The American Journal of Psychiatry 175, 906–908.CrossRefGoogle Scholar
Zhang, T, Xu, L, Tang, Y, Cui, H, Li, H, Wei, Y, Xu, Y, Jiang, L, Zhu, Y, Li, C, Jiang, K, Xiao, Z and Wang, J (2018 b) Using ‘WeChat’ online social networking in a real-world needs analysis of family members of youths at clinical high risk of psychosis. The Australian and New Zealand Journal of Psychiatry 52, 375–382.CrossRefGoogle Scholar
Zheng, L, Wang, J, Zhang, T, Li, H, Li, C and Jiang, K (2012) The Chinese version of the SIPS/SOPS: a pilot study of reliability and validity. Chinese Mental Health Journal 26, 571–576.Google Scholar