Development of a stage-dependent prognostic model to predict psychosis in ultra-high-risk patients seeking treatment for co-morbid psychiatric disorders.

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Title: Development of a stage-dependent prognostic model to predict psychosis in ultra-high-risk patients seeking treatment for co-morbid psychiatric disorders.
Authors: Ising, H. K., Ruhrmann, S., Burger, N. A. F. M., Rietdijk, J., Dragt, S., Klaassen, R. M. C., van den Berg, D. P. G., Nieman, D. H., Boonstra, N., Linszen, D. H., Wunderink, L., Smit, F., Veling, W., van der Gaag, M.
Source: Psychological Medicine. Jul2016, Vol. 46 Issue 9, p1839-1851. 13p.
Subjects: Psychoses, Psychiatric treatment, Chi-squared test, Cognitive therapy, Confidence intervals, Fisher exact test, Help-seeking behavior, Longitudinal method, Neuropsychological tests, Probability theory, Psychological tests, Questionnaires, Regression analysis, Research funding, Psychological stress, T-test (Statistics), Mathematical variables, Comorbidity, Randomized controlled trials, Predictive tests, Proportional hazards models, Data analysis software, Descriptive statistics, Mann Whitney U Test, Prognosis
Geographic Terms: Netherlands
Abstract: Background. Current ultra-high-risk (UHR) criteria appear insufficient to predict imminent onset of first-episode psychosis, as a meta-analysis showed that about 20% of patients have a psychotic outcome after 2 years. Therefore, we aimed to develop a stage-dependent predictive model in UHR individuals who were seeking help for co-morbid disorders. Method. Baseline data on symptomatology, and environmental and psychological factors of 185 UHR patients (aged 14-35 years) participating in the Dutch Early Detection and Intervention Evaluation study were analysed with Cox proportional hazard analyses. Results. At 18 months, the overall transition rate was 17.3%. The final predictor model included five variables: observed blunted affect [hazard ratio (HR) 3.39, 95% confidence interval (CI) 1.56-7.35, p < 0.001], subjective complaints of impaired motor function (HR 5.88, 95% CI 1.21-6.10, p = 0.02), beliefs about social marginalization (HR 2.76, 95% CI 1.14-6.72, p = 0.03), decline in social functioning (HR 1.10, 95% CI 1.01-1.17, p = 0.03), and distress associated with suspiciousness (HR 1.02, 95% CI 1.00-1.03, p = 0.01). The positive predictive value of the model was 80.0%. The resulting prognostic index stratified the general risk into three risk classes with significantly different survival curves. In the highest risk class, transition to psychosis emerged on average 58 months earlier than in the lowest risk class. Conclusions. Predicting a first-episode psychosis in help-seeking UHR patients was improved using a stage-dependent prognostic model including negative psychotic symptoms (observed flattened affect, subjective impaired motor functioning), impaired social functioning and distress associated with suspiciousness. Treatment intensity may be stratified and personalized using the risk stratification. [ABSTRACT FROM AUTHOR]
Copyright of Psychological Medicine is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Development of a stage-dependent prognostic model to predict psychosis in ultra-high-risk patients seeking treatment for co-morbid psychiatric disorders.
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  Data: Background. Current ultra-high-risk (UHR) criteria appear insufficient to predict imminent onset of first-episode psychosis, as a meta-analysis showed that about 20% of patients have a psychotic outcome after 2 years. Therefore, we aimed to develop a stage-dependent predictive model in UHR individuals who were seeking help for co-morbid disorders. Method. Baseline data on symptomatology, and environmental and psychological factors of 185 UHR patients (aged 14-35 years) participating in the Dutch Early Detection and Intervention Evaluation study were analysed with Cox proportional hazard analyses. Results. At 18 months, the overall transition rate was 17.3%. The final predictor model included five variables: observed blunted affect [hazard ratio (HR) 3.39, 95% confidence interval (CI) 1.56-7.35, p &lt; 0.001], subjective complaints of impaired motor function (HR 5.88, 95% CI 1.21-6.10, p = 0.02), beliefs about social marginalization (HR 2.76, 95% CI 1.14-6.72, p = 0.03), decline in social functioning (HR 1.10, 95% CI 1.01-1.17, p = 0.03), and distress associated with suspiciousness (HR 1.02, 95% CI 1.00-1.03, p = 0.01). The positive predictive value of the model was 80.0%. The resulting prognostic index stratified the general risk into three risk classes with significantly different survival curves. In the highest risk class, transition to psychosis emerged on average 58 months earlier than in the lowest risk class. Conclusions. Predicting a first-episode psychosis in help-seeking UHR patients was improved using a stage-dependent prognostic model including negative psychotic symptoms (observed flattened affect, subjective impaired motor functioning), impaired social functioning and distress associated with suspiciousness. Treatment intensity may be stratified and personalized using the risk stratification. [ABSTRACT FROM AUTHOR]
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  Data: &lt;i&gt;Copyright of Psychological Medicine is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
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