Jordan E DeVylder1, Felix M Muchomba2, Kelly E Gill3, Shelly Ben-David4, Deborah J Walder5, Dolores Malaspina6, Cheryl M Corcoran7. 1. New York State Psychiatric Institute at Columbia University, 1051 Riverside Drive, New York, NY, USA; Columbia University School of Social Work, New York, NY, USA. Electronic address: jdevylder@ssw.umaryland.edu. 2. Columbia University School of Social Work, New York, NY, USA. Electronic address: Fmm2116@columbia.edu. 3. New York State Psychiatric Institute at Columbia University, 1051 Riverside Drive, New York, NY, USA. Electronic address: Kegill13@gmail.com. 4. New York State Psychiatric Institute at Columbia University, 1051 Riverside Drive, New York, NY, USA. Electronic address: shellybendavid@gmail.com. 5. Brooklyn College, Department of Psychology, Brooklyn, NY, USA; The Graduate Center of the City University of NY (CUNY), New York, NY USA. Electronic address: DWalder@brooklyn.cuny.edu. 6. Creedmoor Psychiatric Center, New York Office of Mental Health, New York, NY, USA; NYU Department of Psychiatry, New York, NY, USA. Electronic address: Dolores.malaspina@nyumc.org. 7. New York State Psychiatric Institute at Columbia University, 1051 Riverside Drive, New York, NY, USA. Electronic address: corcora@nyspi.columbia.edu.
Abstract
BACKGROUND: Prior studies have implicated baseline positive and negative symptoms as predictors of psychosis onset among individuals at clinical high risk (CHR), but none have evaluated latent trajectories of symptoms over time. This study evaluated the dynamic evolution of symptoms leading to psychosis onset in a CHR cohort. METHOD: 100 CHR participants were assessed quarterly for up to 2.5 years. Latent trajectory analysis was used to identify patterns of symptom change. Logistic and proportional hazards models were employed to evaluate the predictive value for psychosis onset of baseline symptoms and symptom trajectories. RESULTS: Transition rate to psychosis was 26%. Disorganized communication (i.e., subthreshold thought disorder) presented an increased hazard for psychosis onset, both at baseline (Hazard Ratio (95% CI)=1.4 (1.1-1.9)) and as a trajectory of high persistent disorganized communication (Hazard Ratio (95% CI)=2.2 (1.0-4.9)). Interval clinical data did not improve the predictive value of baseline symptoms for psychosis onset. CONCLUSIONS: High baseline disorganized communication evident at ascertainment tended to persist and lead to psychosis onset, consistent with prior behavioral and speech analysis studies in similar cohorts. Remediation of language dysfunction therefore may be a candidate strategy for preventive intervention.
BACKGROUND: Prior studies have implicated baseline positive and negative symptoms as predictors of psychosis onset among individuals at clinical high risk (CHR), but none have evaluated latent trajectories of symptoms over time. This study evaluated the dynamic evolution of symptoms leading to psychosis onset in a CHR cohort. METHOD: 100 CHR participants were assessed quarterly for up to 2.5 years. Latent trajectory analysis was used to identify patterns of symptom change. Logistic and proportional hazards models were employed to evaluate the predictive value for psychosis onset of baseline symptoms and symptom trajectories. RESULTS: Transition rate to psychosis was 26%. Disorganized communication (i.e., subthreshold thought disorder) presented an increased hazard for psychosis onset, both at baseline (Hazard Ratio (95% CI)=1.4 (1.1-1.9)) and as a trajectory of high persistent disorganized communication (Hazard Ratio (95% CI)=2.2 (1.0-4.9)). Interval clinical data did not improve the predictive value of baseline symptoms for psychosis onset. CONCLUSIONS: High baseline disorganized communication evident at ascertainment tended to persist and lead to psychosis onset, consistent with prior behavioral and speech analysis studies in similar cohorts. Remediation of language dysfunction therefore may be a candidate strategy for preventive intervention.
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