Hostname: page-component-848d4c4894-m9kch Total loading time: 0 Render date: 2024-06-02T13:11:01.333Z Has data issue: false hasContentIssue false
  • English
  • Français

Do antidepressants prevent transition to psychosis in individuals at clinical high-risk (CHR-P)? Systematic review and meta-analysis

Published online by Cambridge University Press:  03 June 2022

Andrea Raballo Open the ORCID record for Andrea Raballo [Opens in a new window] ,
Michele Poletti Open the ORCID record for Michele Poletti [Opens in a new window]  and
Antonio Preti Open the ORCID record for Antonio Preti [Opens in a new window]
Andrea Raballo*
Affiliation:
Section of Psychiatry, Clinical Psychology and Rehabilitation, Department of Medicine, University of Perugia, Perugia, Italy Center for Translational, Phenomenological and Developmental Psychopathology (CTPDP), Perugia University Hospital, Perugia, Italy
Michele Poletti
Affiliation:
Department of Mental Health and Pathological Addiction, Child and Adolescent Neuropsychiatry Service, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy
Antonio Preti
Affiliation:
Department of Neuroscience, University of Turin, Turin, Italy
*
Author for correspondence: Andrea Raballo, E-mail: andrea.raballo@unipg.it
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Emerging meta-analytical evidence indicates that baseline exposure to antipsychotics in individuals at clinical high-risk for psychosis (CHR-P) is associated with a higher risk of an imminent transition to psychosis. Despite their tolerability profile and potential beneficial effects, baseline exposure to antidepressants (AD) in CHR-P has surprisingly received far less attention as a potential risk modulator for transition to psychosis. The current systematic review and meta-analysis were performed to fix such a knowledge gap.

Methods

Systematic scrutiny of Medline and Cochrane library, performed up to 1 August 2021, searching for English-language studies on CHR-P reporting numeric data about the sample, the transition outcome at a predefined follow-up time and raw data on AD baseline exposure in relation to such outcome.

Results

Of 1942 identified records, 16 studies were included in the systematic review and meta-analysis. 26% of the participants were already exposed to AD at baseline; at the end of the follow-up 13.5% (95% CI 10.2–17.1%) of them (n = 448) transitioned to psychosis against 21.0% (18.9 to 23.3%) of non-AD exposed CHR-P (n = 1371). CHR-P participants who were already under AD treatment at baseline had a lower risk of transition than non-AD exposed CHR-P. The RR was 0.71 (95% CI 0.56–0.90) in the fixed-effects model (z = −2.79; p = 0.005), and 0.78 (0.58–1.05) in the random-effects model (z = −1.77; p = 0.096; tau-squared = 0.059). There was no relevant heterogeneity (Cochran's Q = 18.45; df = 15; p = 0.239; I2 = 18.7%).

Conclusions

Ongoing AD exposure at inception in CHR-P is associated to a reduced risk of transition to psychosis at follow up.

Keywords

Antidepressantantipsychoticsclinical high riskmeta-analysispsychosistransition
Type
Original Article
Information
Psychological Medicine , Volume 53 , Issue 10 , July 2023 , pp. 4550 - 4560
Check for updates
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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.)

References

Addington, J., Farris, M. S., Liu, L., Cadenhead, K. S., Cannon, T. D., Cornblatt, B. A., … Woods, S. W. (2021). Depression: An actionable outcome for those at clinical high-risk. Schizophrenia Research, 227, 38–43. https://doi.org/10.1016/j.schres.2020.10.001.CrossRefGoogle ScholarPubMed
Addington, J., Piskulic, D., Liu, L., Lockwood, J., Cadenhead, K. S., Cannon, T. D., … Woods, S. W. (2017). Comorbid diagnoses for youth at clinical high risk of psychosis. Schizophrenia Research, 190, 90–95. https://doi.org/10.1016/j.schres.2017.03.043.CrossRefGoogle ScholarPubMed
Andersen, H. G., Raghava, J. M., Svarer, C., Wulff, S., Johansen, L. B., Antonsen, P. K., … Ebdrup, B. H. (2020). Striatal volume increase after six weeks of selective dopamine D2/3 receptor blockade in first-episode, antipsychotic-naïve schizophrenia patients. Frontiers in Neuroscience, 14, 484. https://doi.org/10.3389/fnins.2020.00484.CrossRefGoogle Scholar
Barendregt, J. J., Doi, S. A., Lee, Y. Y., Norman, R. E., & Vos, T. (2013). Meta-analysis of prevalence. Journal of Epidemiology and Community Health, 67(11), 974–978. https://doi.org/10.1136/jech-2013-203104.CrossRefGoogle ScholarPubMed
Bearden, C. E., Wu, K. N., Caplan, R., & Cannon, T. D. (2011). Thought disorder and communication deviance as predictors of outcome in youth at clinical high risk for psychosis. Journal of the American Academy of Child and Adolescent Psychiatry, 50(7), 669–680. https://doi.org/10.1016/j.jaac.2011.03.021.CrossRefGoogle ScholarPubMed
Begg, C. B., & Mazumdar, M. (1994). Operating characteristics of a rank correlation test for publication bias. Biometrics, 50(4), 1088–1101.CrossRefGoogle Scholar
Borenstein, M. (2020). Research note: In a meta-analysis, the I2 index does not tell us how much the effect size varies across studies. Journal of Physiotherapy, 66(2), 135–139. https://doi.org/10.1016/j.jphys.2020.02.011.CrossRefGoogle Scholar
Borenstein, M., Hedges, L. V., Higgins, J. P., & Rothstein, H. R. (2010). A basic introduction to fixed-effect and random-effects models for meta-analysis. Research Synthesis Methods, 1(2), 97–111. https://doi.org/10.1002/jrsm.12.CrossRefGoogle ScholarPubMed
Bosman, R. C., Waumans, R. C., Jacobs, G. E., Oude Voshaar, R. C., Muntingh, A., Batelaan, N. M., & van Balkom, A. (2018). Failure to respond after reinstatement of antidepressant medication: A systematic review. Psychotherapy and Psychosomatics, 87(5), 268–275. https://doi.org/10.1159/000491550.CrossRefGoogle ScholarPubMed
Bowie, C. R., McLaughlin, D., Carrión, R. E., Auther, A. M., & Cornblatt, B. A. (2012). Cognitive changes following antidepressant or antipsychotic treatment in adolescents at clinical risk for psychosis. Schizophrenia Research, 137(1-3), 110–117. https://doi.org/10.1016/j.schres.2012.02.008.CrossRefGoogle ScholarPubMed
Brucato, G., Masucci, M. D., Arndt, L. Y., Ben-David, S., Colibazzi, T., Corcoran, C. M., … Girgis, R. R. (2017). Baseline demographics, clinical features and predictors of conversion among 200 individuals in a longitudinal prospective psychosis-risk cohort. Psychological Medicine, 47(11), 1923–1935. https://doi.org/10.1017/S0033291717000319.CrossRefGoogle Scholar
Bykowsky, O., Harrisberger, F., Schmidt, A., Smieskova, R., Hauke, D. J., Egloff, L., … Borgwardt, S. (2019). Association of antidepressants with brain morphology in early stages of psychosis: An imaging genomics approach. Scientific Reports, 9(1), 8516. https://doi.org/10.1038/s41598-019-44903-y.CrossRefGoogle ScholarPubMed
Capaldi, V. F. II., & Carr, R. B. (2010). Citalopram-induced hallucinations and delusions in a young adult. General Hospital Psychiatry, 32(6), 648.e1–648.e6483. https://doi.org/10.1016/j.genhosppsych.2010.07.008.CrossRefGoogle ScholarPubMed
Chouinard, G., Samaha, A. N., Chouinard, V. A., Peretti, C. S., Kanahara, N., Takase, M., & Iyo, M. (2017). Antipsychotic-induced dopamine supersensitivity psychosis: Pharmacology, criteria, and therapy. Psychotherapy and Psychosomatics, 86(4), 189–219. https://doi.org/10.1159/000477313.CrossRefGoogle ScholarPubMed
Collin, G., Seidman, L. J., Keshavan, M. S., Stone, W. S., Qi, Z., Zhang, T., … Whitfield-Gabrieli, S. (2020). Functional connectome organization predicts conversion to psychosis in clinical high-risk youth from the SHARP program. Molecular Psychiatry, 25(10), 2431–2440. https://doi.org/10.1038/s41380-018-0288-x.CrossRefGoogle ScholarPubMed
Cornblatt, B. A., Lencz, T., Smith, C. W., Olsen, R., Auther, A. M., Nakayama, E., … Correll, C. U. (2007). Can antidepressants be used to treat the schizophrenia prodrome? Results of a prospective, naturalistic treatment study of adolescents. The Journal of Clinical Psychiatry, 68(4), 546–557. https://doi.org/10.4088/jcp.v68n0410.CrossRefGoogle ScholarPubMed
Cosci, F., & Chouinard, G. (2020). Acute and persistent withdrawal syndromes following discontinuation of psychotropic medications. Psychotherapy and Psychosomatics, 89(5), 283–306. https://doi.org/10.1159/000506868.CrossRefGoogle ScholarPubMed
Daneault, J. G., Maraj, A., Lepage, M., Malla, A., Schmitz, N., Iyer, S. N., … Shah, J. L. (2019). Medication adherence in first episode psychosis: The role of pre-onset subthreshold symptoms. Acta Psychiatrica Scandinavica, 139(4), 336–347. https://doi.org/10.1111/acps.13011.CrossRefGoogle ScholarPubMed
DeVylder, J. E., Muchomba, F. M., Gill, K. E., Ben-David, S., Walder, D. J., Malaspina, D., & Corcoran, C. M. (2014). Symptom trajectories and psychosis onset in a clinical high-risk cohort: The relevance of subthreshold thought disorder. Schizophrenia Research, 159(2–3), 278–283. https://doi.org/10.1016/j.schres.2014.08.008.CrossRefGoogle Scholar
Drake, R. J., Husain, N., Marshall, M., Lewis, S. W., Tomenson, B., Chaudhry, I. B., … Birchwood, M. (2020). Effect of delaying treatment of first-episode psychosis on symptoms and social outcomes: A longitudinal analysis and modelling study. The Lancet. Psychiatry, 7(7), 602–610. https://doi.org/10.1016/S2215-0366(20)30147-4.CrossRefGoogle ScholarPubMed
Egger, M., Davey Smith, G., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. BMJ (Clinical research ed.), 315(7109), 629–634. https://doi.org/10.1136/bmj.315.7109.629.CrossRefGoogle ScholarPubMed
Egger, M., Juni, P., Bartlett, C., Holenstein, F., & Sterne, J. (2003). How important are comprehensive literature searches and the assessment of trial quality in systematic reviews? Empirical study. Health Technology Assessment (Winchester, England), 7(1), 1–76.CrossRefGoogle ScholarPubMed
Fava, G. A. (2020). May antidepressant drugs worsen the conditions they are supposed to treat? The clinical foundations of the oppositional model of tolerance. Therapeutic Advances in Psychopharmacology, 10, 2045125320970325. https://doi.org/10.1177/2045125320970325.CrossRefGoogle ScholarPubMed
Fava, G. A., Benasi, G., Lucente, M., Offidani, E., Cosci, F., & Guidi, J. (2018). Withdrawal symptoms after serotonin-noradrenaline reuptake inhibitor discontinuation: Systematic review. Psychotherapy and Psychosomatics, 87(4), 195–203. https://doi.org/10.1159/000491524.CrossRefGoogle ScholarPubMed
Fava, G. A., Gatti, A., Belaise, C., Guidi, J., & Offidani, E. (2015). Withdrawal symptoms after selective serotonin reuptake inhibitor discontinuation: A systematic review. Psychotherapy and Psychosomatics, 84(2), 72–81. https://doi.org/10.1159/000370338.CrossRefGoogle ScholarPubMed
Ferguson, C. J., & Brannick, M. T. (2012). Publication bias in psychological science: Prevalence, methods for identifying and controlling, and implications for the use of meta-analyses. Psychological Methods, 17(1), 120–128. https://doi.org/10.1037/a0024445.CrossRefGoogle ScholarPubMed
Fleiss, J. L. (1993). The statistical basis of meta-analysis. Statistical Methods in Medical Research, 2(2), 121–145. https://doi.org/10.1177/096228029300200202.CrossRefGoogle ScholarPubMed
Fornaro, M., Anastasia, A., Novello, S., Fusco, A., Pariano, R., De Berardis, D., … Carvalho, A. F. (2019). The emergence of loss of efficacy during antidepressant drug treatment for major depressive disorder: An integrative review of evidence, mechanisms, and clinical implications. Pharmacological Research, 139, 494–502. https://doi.org/10.1016/j.phrs.2018.10.025.CrossRefGoogle ScholarPubMed
Fowler, D., Hodgekins, J., Garety, P., Freeman, D., Kuipers, E., Dunn, G., … Bebbington, P. E. (2012). Negative cognition, depressed mood, and paranoia: A longitudinal pathway analysis using structural equation modeling. Schizophrenia Bulletin, 38(5), 1063–1073. https://doi.org/10.1093/schbul/sbr019.CrossRefGoogle ScholarPubMed
Francesconi, M., Minichino, A., Carrión, R. E., Delle Chiaie, R., Bevilacqua, A., Parisi, M., … Cadenhead, K. (2017). Psychosis prediction in secondary mental health services. A broad, comprehensive approach to the “at risk mental state” syndrome. European Psychiatry, 40, 96–104. https://doi.org/10.1016/j.eurpsy.2016.09.002.CrossRefGoogle Scholar
Freeman, M. F., & Tukey, J. W. (1950). Transformations related to the angular and the square root. Annals of Mathematical Statistics, 21(4), 607–611.CrossRefGoogle Scholar
Fusar-Poli, P., Frascarelli, M., Valmaggia, L., Byrne, M., Stahl, D., Rocchetti, M., … McGuire, P. (2015). Antidepressant, antipsychotic and psychological interventions in subjects at high clinical risk for psychosis: OASIS 6-year naturalistic study. Psychological Medicine, 45(6), 1327–1339. https://doi.org/10.1017/S003329171400244X.CrossRefGoogle ScholarPubMed
Fusar-Poli, P., Nelson, B., Valmaggia, L., Yung, A. R., & McGuire, P. K. (2014). Comorbid depressive and anxiety disorders in 509 individuals with an at-risk mental state: Impact on psychopathology and transition to psychosis. Schizophrenia Bulletin, 40(1), 120–131. https://doi.org/10.1093/schbul/sbs136.CrossRefGoogle ScholarPubMed
Grent-’t-Jong, T., Gajwani, R., Gross, J., Gumley, A. I., Krishnadas, R., Lawrie, S. M., … Uhlhaas, P. J. (2021). 40-Hz auditory steady-state responses characterize circuit dysfunctions and predict clinical outcomes in clinical high-risk for psychosis participants: A magnetoencephalography study. Biological Psychiatry, 90(6), 419–429. https://doi.org/10.1016/j.biopsych.2021.03.018.CrossRefGoogle Scholar
Häfner, H., Maurer, K., Trendler, G., van der Heiden, W., Schmidt, M., & Könnecke, R. (2005). Schizophrenia and depression: Challenging the paradigm of two separate diseases – a controlled study of schizophrenia, depression and healthy controls. Schizophrenia Research, 77(1), 11–24. https://doi.org/10.1016/j.schres.2005.01.004.CrossRefGoogle Scholar
Hedges, L. V., & Vevea, J. L. (1998). Fixed- and random-effects models in meta-analysis. Psychological Methods, 3(4), 486–504.CrossRefGoogle Scholar
Huedo-Medina, T. B., Sánchez-Meca, J., Marín-Martínez, F., & Botella, J. (2006). Assessing heterogeneity in meta-analysis: Q statistic or I2 index? Psychological Methods, 11(2), 193–206. https://doi.org/10.1037/1082-989X.11.2.193.CrossRefGoogle ScholarPubMed
Jackson, D., & Turner, R. (2017). Power analysis for random-effects meta-analysis. Research Synthesis Methods, 8(3), 290–302. https://doi.org/10.1002/jrsm.1240.CrossRefGoogle ScholarPubMed
Jacob, M. K., & Ash, P. (2009). Venlafaxine-induced complex visual hallucinations in a 17-year-old boy. Journal of Clinical Psychiatry, 70(4), 601–603. https://doi.org/10.4088/jcp.08l04627.CrossRefGoogle Scholar
Kay, S. R., Fiszbein, A., & Opler, L. A. (1987). The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophrenia Bulletin, 13(2), 261–276. https://doi.org/10.1093/schbul/13.2.261.CrossRefGoogle ScholarPubMed
Kline, E. R., Seidman, L. J., Cornblatt, B. A., Woodberry, K. A., Bryant, C., Bearden, C. E., … Addington, J. (2018). Depression and clinical high-risk states: Baseline presentation of depressed vs. non-depressed participants in the NAPLS-2 cohort. Schizophrenia Research, 192, 357–363. https://doi.org/10.1016/j.schres.2017.05.032.CrossRefGoogle ScholarPubMed
Knapp, G., & Hartung, J. (2003). Improved tests for a random effects meta-regression with a single covariate. Statistics in Medicine, 22(17), 2693–2710. https://doi.org/10.1002/sim.1482.CrossRefGoogle ScholarPubMed
Krabbendam, L., Myin-Germeys, I., Bak, M., & van Os, J. (2005). Explaining transitions over the hypothesized psychosis continuum. Australian and New Zealand Journal of Psychiatry, 39(3), 180–186. https://doi.org/10.1080/j.1440-1614.2005.01541.x.CrossRefGoogle ScholarPubMed
Kristensen, T. D., Glenthøj, L. B., Ambrosen, K., Syeda, W., Ragahava, J. M., Krakauer, K., … Ebdrup, B. H. (2021). Global fractional anisotropy predicts transition to psychosis after 12 months in individuals at ultra-high risk for psychosis. Acta Psychiatrica Scandinavica, 11(5), 448–463. https://doi.org/10.1111/acps.13355.CrossRefGoogle Scholar
Labad, J., Stojanovic-Pérez, A., Montalvo, I., Solé, M., Cabezas, Á, Ortega, L., … Gutiérrez-Zotes, A. (2015). Stress biomarkers as predictors of transition to psychosis in at-risk mental states: Roles for cortisol, prolactin and albumin. Journal of Psychiatric Research, 60, 163–169. https://doi.org/10.1016/j.jpsychires.2014.10.011.CrossRefGoogle ScholarPubMed
Li, M., Chen, Z., Deng, W., He, Z., Wang, Q., Jiang, L., … Li, T. (2012). Volume increases in putamen associated with positive symptom reduction in previously drug-naive schizophrenia after 6 weeks antipsychotic treatment. Psychological Medicine, 42(7), 1475–1483. https://doi.org/10.1017/S0033291711002157.CrossRefGoogle ScholarPubMed
Lim, J., Rekhi, G., Rapisarda, A., Lam, M., Kraus, M., Keefe, R. S., & Lee, J. (2015). Impact of psychiatric comorbidity in individuals at ultra high risk of psychosis – findings from the Longitudinal Youth at Risk Study (LYRIKS). Schizophrenia Research, 164(1–3), 8–14. https://doi.org/10.1016/j.schres.2015.03.007.CrossRefGoogle ScholarPubMed
McGlashan, T. H. (2001). Structured Interview for Prodromal Symptoms (SIPS). New Haven, Connecticut: Yale University.Google Scholar
Merritt, K., Luque Laguna, P., Irfan, A., & David, A. S. (2021). Longitudinal structural MRI findings in individuals at genetic and clinical high risk for psychosis: A systematic review. Frontiers in Psychiatry, 12, 620401. https://doi.org/10.3389/fpsyt.2021.620401.CrossRefGoogle ScholarPubMed
Modinos, G., Richter, A., Egerton, A., Bonoldi, I., Azis, M., Antoniades, M., … McGuire, P. (2021). Interactions between hippocampal activity and striatal dopamine in people at clinical high risk for psychosis: Relationship to adverse outcomes. Neuropsychopharmacology, 46(8), 1468–1474. https://doi.org/10.1038/s41386-021-01019-0.CrossRefGoogle ScholarPubMed
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & PRISMA Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. BMJ (Clinical research ed.), 339, b2535. https://doi.org/10.1136/bmj.b2535.CrossRefGoogle ScholarPubMed
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ (Clinical research ed.), 372, n71. https://doi.org/10.1136/bmj.n71.Google ScholarPubMed
Pawełczyk, A., Łojek, E., Żurner, N., Kotlicka-Antczak, M., & Pawełczyk, T. (2021). Higher order language impairments can predict the transition of ultrahigh risk state to psychosis-An empirical study. Early Intervention in Psychiatry, 15(2), 314–327. https://doi.org/10.1111/eip.12943.CrossRefGoogle ScholarPubMed
Planchez, B., Surget, A., & Belzung, C. (2020). Adult hippocampal neurogenesis and antidepressants effects. Current Opinion in Pharmacology, 50, 88–95. https://doi.org/10.1016/j.coph.2019.11.009.CrossRefGoogle ScholarPubMed
Preti, A., Raballo, A., Meneghelli, A., Cocchi, A., Meliante, M., Barbera, S., … Percudani, M. (2021). Antipsychotics are related to psychometric conversion to psychosis in ultra-high-risk youth. Early Intervention in Psychiatry, 16(4), 342–351. https://doi.org/10.1111/eip.13158.CrossRefGoogle ScholarPubMed
Raballo, A., & Poletti, M. (2019). Overlooking the transition elephant in the ultra-high-risk room: Are we missing functional equivalents of transition to psychosis? Psychological Medicine, 52(1), 184–187. https://doi.org/10.1017/S0033291719003337.CrossRefGoogle Scholar
Raballo, A., Poletti, M., & Preti, A. (2020a). Meta-analyzing the prevalence and prognostic effect of antipsychotic exposure in clinical high-risk (CHR): When things are not what they seem. Psychological Medicine, 50(16), 2673–2681. https://doi.org/10.1017/S0033291720004237.CrossRefGoogle ScholarPubMed
Raballo, A., Poletti, M., & Preti, A. (2020b). Attenuated psychosis syndrome or pharmacologically attenuated first-episode psychosis?: An undesirably widespread confounder. JAMA Psychiatry, 77(12), 1213–1214. https://doi.org/10.1001/jamapsychiatry.2020.1634.CrossRefGoogle Scholar
Raballo, A., Poletti, M., & Preti, A. (2021a). Individualized diagnostic and prognostic models for psychosis risk syndromes: Do not underestimate antipsychotic exposure. Biological Psychiatry, 90(6), e33–e35. https://doi.org/10.1016/j.biopsych.2021.01.020.CrossRefGoogle Scholar
Raballo, A., Poletti, M., & Preti, A. (2021b). Negative prognostic effect of baseline antipsychotic exposure in Clinical High Risk for psychosis (CHR-P): Is pre-test risk enrichment the hidden culprit? International Journal of Neuropsychopharmacology, 24(9), 710–720. https://doi.org/10.1093/ijnp/pyab030.CrossRefGoogle ScholarPubMed
Raballo, A., Poletti, M., & Preti, A. (2021c). Antipsychotic treatment in clinical high risk for psychosis: Protective, iatrogenic or further risk flag? Australian and New Zealand Journal of Psychiatry, 55(5), 442–444. https://doi.org/10.1177/0004867420984836.CrossRefGoogle ScholarPubMed
R Core Team. (2020). R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.Google Scholar
Riecher-Rössler, A., Aston, J., Ventura, J., Merlo, M., Borgwardt, S., Gschwandtner, U., & Stieglitz, R. D. (2008). Das Basel Screening Instrument für Psychosen (BSIP): Entwicklung, aufbau, reliabilität und validität [The Basel Screening Instrument for Psychosis (BSIP): Development, structure, reliability and validity]. Fortschritte der Neurologie-Psychiatrie, 76(4), 207–216. https://doi.org/10.1055/s-2008-1038155.CrossRefGoogle ScholarPubMed
Rosen, M., Betz, L. T., Schultze-Lutter, F., Chisholm, K., Haidl, T. K., Kambeitz-Ilankovic, L., … PRONIA Consortium. (2021). Towards clinical application of prediction models for transition to psychosis: A systematic review and external validation study in the PRONIA sample. Neuroscience and Biobehavioral Reviews, 125, 478–492. https://doi.org/10.1016/j.neubiorev.2021.02.032.CrossRefGoogle ScholarPubMed
Rutigliano, G., Valmaggia, L., Landi, P., Frascarelli, M., Cappucciati, M., Sear, V., … Fusar-Poli, P. (2016). Persistence or recurrence of non-psychotic comorbid mental disorders associated with 6-year poor functional outcomes in patients at ultra high risk for psychosis. Journal of Affective Disorders, 203, 101–110. https://doi.org/10.1016/j.jad.2016.05.053.CrossRefGoogle ScholarPubMed
Ryan, R. (2016). Cochrane Consumers and Communication Review Group. Heterogeneity and subgroup analyses in Cochrane Consumers and Communication Group reviews: planning the analysis at protocol stage. https://cccrg.cochrane.org/sites/cccrg.cochrane.org/files/public/uploads/heterogeneity_subgroup_analyses_revising_december_1st_2016.pdf. Accessed on August 2021.Google Scholar
Sanfelici, R., Dwyer, D. B., Antonucci, L. A., & Koutsouleris, N. (2020). Individualized diagnostic and prognostic models for patients with psychosis risk syndromes: A meta-analytic view on the state of the art. Biological Psychiatry, 88(4), 349–360. https://doi.org/10.1016/j.biopsych.2020.02.009.CrossRefGoogle ScholarPubMed
Schultze-Lutter, F., Klosterkötter, J., & Ruhrmann, S. (2014). Improving the clinical prediction of psychosis by combining ultra-high risk criteria and cognitive basic symptoms. Schizophrenia Research, 154(1-3), 100–106. https://doi.org/10.1016/j.schres.2014.02.010.CrossRefGoogle ScholarPubMed
Schwarzer, G., Carpenter, J. R., & Rücker, G. (2015). Meta-Analysis with R. Berlin, Germany: Springer.CrossRefGoogle Scholar
Shah, J. L., Scott, J., McGorry, P. D., Cross, S., Keshavan, M. S., Nelson, B., … International Working Group on Transdiagnostic Clinical Staging in Youth Mental Health. (2020). Transdiagnostic clinical staging in youth mental health: A first international consensus statement. World Psychiatry, 19(2), 233–242. https://doi.org/10.1002/wps.20745.CrossRefGoogle ScholarPubMed
Taipale, H., Niederkrotenthaler, T., Tanskanen, A., Cullen, A. E., Helgesson, M., Berg, L., … Mittendorfer-Rutz, E. (2021). Persistence of antidepressant use among refugee youth with common mental disorder. Journal of Affective Disorders, 294, 831–837. https://doi.org/10.1016/j.jad.2021.07.096.CrossRefGoogle ScholarPubMed
Taylor, C., Fricker, A. D., Devi, L. A., & Gomes, I. (2005). Mechanisms of action of antidepressants: From neurotransmitter systems to signaling pathways. Cellular Signalling, 17(5), 549–557. https://doi.org/10.1016/j.cellsig.2004.12.007.CrossRefGoogle ScholarPubMed
Upthegrove, R., Marwaha, S., & Birchwood, M. (2017). Depression and schizophrenia: Cause, consequence, or trans-diagnostic issue? Schizophrenia Bulletin, 43(2), 240–244. https://doi.org/10.1093/schbul/sbw097.Google ScholarPubMed
van Os, J., & Reininghaus, U. (2016). Psychosis as a transdiagnostic and extended phenotype in the general population. World Psychiatry, 15(2), 118–124. https://doi.org/10.1002/wps.20310.CrossRefGoogle ScholarPubMed
van Tricht, M. J., Nieman, D. H., Koelman, J. H., van der Meer, J. N., Bour, L. J., de Haan, L., & Linszen, D. H. (2010). Reduced parietal P300 amplitude is associated with an increased risk for a first psychotic episode. Biological Psychiatry, 68(7), 642–648. https://doi.org/10.1016/j.biopsych.2010.04.022.CrossRefGoogle ScholarPubMed
Verdoux, H., van Os, J., Maurice-Tison, S., Gay, B., Salamon, R., & Bourgeois, M. L. (1999). Increased occurrence of depression in psychosis-prone subjects: A follow-up study in primary care settings. Comprehensive Psychiatry, 40(6), 462–468. https://doi.org/10.1016/s0010-440x(99)90091-3.CrossRefGoogle ScholarPubMed
Veroniki, A. A., Jackson, D., Viechtbauer, W., Bender, R., Bowden, J., Knapp, G., … Salanti, G. (2016). Methods to estimate the between-study variance and its uncertainty in meta-analysis. Research Synthesis Methods, 7(1), 55–79. https://doi.org/10.1002/jrsm.1164.CrossRefGoogle ScholarPubMed
Viechtbauer, W. (2005). Bias and efficiency of meta-analytic variance estimators in the random-effects model. Journal of Educational and Behavioral Statistics, 30(3), 261–293. https://doi.org/10.3102%2F10769986030003261.CrossRefGoogle Scholar
Viechtbauer, W. (2010). Conducting meta-analyses in R with the metaphor package. Journal of Statistical Software, 36(3), 1–48. http://dx.doi.org/10.18637/jss.v036.i03.CrossRefGoogle Scholar
Walker, E. F., Brennan, P. A., Esterberg, M., Brasfield, J., Pearce, B., & Compton, M. T. (2010). Longitudinal changes in cortisol secretion and conversion to psychosis in at-risk youth. Journal of Abnormal Psychology, 119(2), 401–408. https://doi.org/10.1037/a0018399.CrossRefGoogle ScholarPubMed
Walker, E. F., Cornblatt, B. A., Addington, J., Cadenhead, K. S., Cannon, T. D., McGlashan, T. H., … Heinssen, R. (2009). The relation of antipsychotic and antidepressant medication with baseline symptoms and symptom progression: A naturalistic study of the North American Prodrome Longitudinal Sample. Schizophrenia Research, 115(1), 50–57. https://doi.org/10.1016/j.schres.2009.07.023.CrossRefGoogle ScholarPubMed
Woods, S. W., Addington, J., Bearden, C. E., Cadenhead, K. S., Cannon, T. D., Cornblatt, B. A., … McGlashan, T. H. (2013). Psychotropic medication use in youth at high risk for psychosis: Comparison of baseline data from two research cohorts 1998-2005 and 2008-2011. Schizophrenia Research, 148(1-3), 99–104. doi: 10.1016/j.schres.2013.05.019CrossRefGoogle ScholarPubMed
Woods, S. W., Addington, J., Cadenhead, K. S., Cannon, T. D., Cornblatt, B. A., Heinssen, R., … McGlashan, T. H. (2009). Validity of the prodromal risk syndrome for first psychosis: Findings from the North American prodrome longitudinal study. Schizophrenia Bulletin, 35(5), 894–908. https://doi.org/10.1093/schbul/sbp027.CrossRefGoogle Scholar
Yoviene Sykes, L. A., Ferrara, M., Addington, J., Bearden, C. E., Cadenhead, K. S., Cannon, T. D., … Woods, S. W. (2020). Predictive validity of conversion from the clinical high risk syndrome to frank psychosis. Schizophrenia Research, 216, 184–191. https://doi.org/10.1016/j.schres.2019.12.002.CrossRefGoogle Scholar
Yung, A. R., Yuen, H. P., McGorry, P. D., Phillips, L. J., Kelly, D., Dell'Olio, M., … Buckby, J. (2005). Mapping the onset of psychosis: The comprehensive assessment of at-risk mental states. Australian and New Zealand Journal of Psychiatry, 39(11–12), 964–971. https://doi.org/10.1080/j.1440-1614.2005.01714.x.CrossRefGoogle ScholarPubMed
Zarogianni, E., Storkey, A. J., Borgwardt, S., Smieskova, R., Studerus, E., Riecher-Rössler, A., & Lawrie, S. M. (2019). Individualized prediction of psychosis in subjects with an at-risk mental state. Schizophrenia Research, 214, 18–23. https://doi.org/10.1016/j.schres.2017.08.061.CrossRefGoogle ScholarPubMed
Zhang, T., Xu, L., Tang, X., Wei, Y., Hu, Q., Hu, Y., … Wang, J. (2020). Real-world effectiveness of antipsychotic treatment in psychosis prevention in a 3-year cohort of 517 individuals at clinical high risk from the SHARP (ShangHai At Risk for Psychosis). Australian and New Zealand Journal of Psychiatry, 54(7), 696–706. https://doi.org/10.1177/0004867420917449.CrossRefGoogle Scholar
Zhang, T., Xu, L., Wei, Y., Tang, X., Hu, Y., Cui, H., … Wang, J. (2021). When to initiate antipsychotic treatment for psychotic symptoms: At the premorbid phase or first episode of psychosis? Australian and New Zealand Journal of Psychiatry, 55(3), 314–323. https://doi.org/10.1177/0004867420969810.CrossRefGoogle ScholarPubMed
Ziermans, T. B., Schothorst, P. F., Sprong, M., & van Engeland, H. (2011). Transition and remission in adolescents at ultra-high risk for psychosis. Schizophrenia Research, 126(1-3), 58–64. https://doi.org/10.1016/j.schres.2010.10.022.CrossRefGoogle ScholarPubMed
Supplementary material: File

Raballo et al. supplementary material

Table S1 and Figures S2-S4

Download Raballo et al. supplementary material(File)
File 793.6 KB