Cited by 1,269Schizophrenia research and treatmentPsychopathy, Forensic Psychiatry, Sexual OffendingBipolar Disorder and Treatment

Prediction of Psychosis in Youth at High Clinical Risk: A Multisite Longitudinal Study in North America

Open access
Cannon, Tyrone D., Cadenhead, Kristin, Cornblatt, Barbara, Woods, Scott W., Addington, Jean, Walker, Elaine, Seidman, Larry J., Perkins, Diana +3 more·2008·Archives of General Psychiatry

Abstract

CONTEXT: Early detection and prospective evaluation of individuals who will develop schizophrenia or other psychotic disorders are critical to efforts to isolate mechanisms underlying psychosis onset and to the testing of preventive interventions, but existing risk prediction approaches have achieved only modest predictive accuracy. OBJECTIVES: To determine the risk of conversion to psychosis and to evaluate a set of prediction algorithms maximizing positive predictive power in a clinical high-risk sample. DESIGN, SETTING, AND PARTICIPANTS: Longitudinal study with a 2 1/2-year follow-up of 291 prospectively identified treatment-seeking patients meeting Structured Interview for Prodromal Syndromes criteria. The patients were recruited and underwent evaluation across 8 clinical research centers as part of the North American Prodrome Longitudinal Study. MAIN OUTCOME MEASURE: Time to conversion to a fully psychotic form of mental illness. RESULTS: The risk of conversion to psychosis was 35%, with a decelerating rate of transition during the 2 1/2-year follow-up. Five features assessed at baseline contributed uniquely to the prediction of psychosis: a genetic risk for schizophrenia with recent deterioration in functioning, higher levels of unusual thought content, higher levels of suspicion/paranoia, greater social impairment, and a history of substance abuse. Prediction algorithms combining 2 or 3 of these variables resulted in dramatic increases in positive predictive power (ie, 68%-80%) compared with the prodromal criteria alone. CONCLUSIONS: These findings demonstrate that prospective ascertainment of individuals at risk for psychosis is feasible, with a level of predictive accuracy comparable to that in other areas of preventive medicine. They provide a benchmark for the rate and shape of the psychosis risk function against which standardized preventive intervention programs can be compared.

Integrity signals

Registry

Crossref · 10.1001/archgenpsychiatry.2007.3

Cites

69 of 69 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Given that unusual beliefs and thought content constitute risk for psychosis conversion, the reduction of self-referencing might be another rationale for mindfulness-based psychosis prevention.

    “Given that unusual beliefs and thought content constitute risk for psychosis conversion (Cannon et al., 2008), the reduction of self-referencing might be another rationale for mindfulness-based psychosis prevention.”
  • Suspiciousness/paranoia carries high predictive power for conversion to psychosis in high-risk individuals, alongside genetic risk and unusual thought content.

    “b) suspiciousness/paranoia carries a high predictive power for conversion to psychosis in high risk individuals, alongside genetic risk and unusual thought content (Cannon et al., 2008)”

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Cannon, T. D., Cadenhead, K., Cornblatt, B., Woods, S. W., Addington, J., Walker, E., Seidman, L. J., Perkins, D., Tsuang, M., McGlashan, T., & Heinssen, R.
Affiliations
  • University of California, Los Angeles (US)
  • University of California San Diego (US)
  • Zucker Hillside Hospital (US)
  • Yale University (US)
  • University of Toronto (CA)
  • Emory University (US)
  • Harvard University (US)
  • University of North Carolina at Chapel Hill (US)
  • National Institute of Mental Health (US)
Venue
Archives of General Psychiatry
Published
2008-01-01
Volume
65
Issue
1
Pages
28
ISSN
0003-990X (ISSN-L)
OpenAlex
W2140824803
Cited by
1,269
References
68
Citations by year
2026: 14 · 2025: 22 · 2024: 19 · 2023: 30 · 2022: 32 · 2021: 52 · 2020: 51 · 2019: 72 · 2018: 50 · 2017: 80 · 2016: 91 · 2015: 98 · 2014: 93 · 2013: 115 · 2012: 109
FWCI
78.94
Type
journal article
Language
en
Open access
Locations
  • Archives of General Psychiatry (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Institutes of Health (UL1TR000454)
  • National Institute of Mental Health (K24MH076191, K23MH001905, U01MH082022, R01MH060720, U01MH082004, U01MH081944)
  • National Center for Advancing Translational Sciences
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
  • Social Sciences › Psychology › Clinical Psychology › Psychopathy, Forensic Psychiatry, Sexual Offending
  • Health Sciences › Medicine › Psychiatry and Mental health › Bipolar Disorder and Treatment
Keywords
psychosis prediction, clinical high risk for psychosis, schizophrenia, transition to psychosis, risk prediction algorithm, unusual thought content, social dysfunction, substance abuse, North American Prodrome Longitudinal Study
MeSH terms
Adolescent, Adult, Algorithms, Cognition, Female, Humans, Longitudinal Studies, Male, Paranoid Disorders, Predictive Value of Tests, Prognosis, Psychotic Disorders, Risk Factors, Schizophrenia, Social Behavior, Syndrome, Antipsychotic Agents, Substance-Related Disorders, Genetic Predisposition to Disease, Kaplan-Meier Estimate

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review