Personalized Prediction of Psychosis: External Validation of the NAPLS-2 Psychosis Risk Calculator With the EDIPPP Project

Carrión, Ricardo; Cornblatt, Barbara A.; Burton, Cynthia; Tso, Ivy F.; Auther, Andrea M.; Adelsheim, Steven; Calkins, Roderick; Carter, Cameron S.; Niendam, Tara A.; Sale, Tamara; Taylor, Stephan F.; McFarlane, William R.

doi:10.1176/appi.ajp.2016.15121565

Cited by 150 publications

(134 citation statements)

References 47 publications

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“…The predictive model was well calibrated, and the NAPLS 2 calculator provided a reasonable estimation of psychosis risk when considering the risk prediction generated by the validation model and the actual observed outcomes. In addition, when applied to the external EDIPPP sample, the NAPLS 2 calculator showed sensitivity and specificity values comparable to those found in the NAPLS 2 sample across different levels of model predicted risk (i.e., as in Table 3) (31). …”

Section: Discussionmentioning

confidence: 87%

“…In a companion paper (31), Carrión et al perform such a replication test of the NAPLS 2 risk calculator in an independent sample from the Early Detection, Intervention, and Prevention of Psychosis Program (EDIPPP) that included 176 CHR cases diagnosed using the SIPS and followed clinically to monitor conversion. Only the stress and trauma variables – found to be negligible in predicting conversion here – were not collected and were therefore omitted from the replication testing.…”

Section: Discussionmentioning

confidence: 99%

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An Individualized Risk Calculator for Research in Prodromal Psychosis

Cannon¹,

Yu²,

Addington³

et al. 2016

AJP

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487

415

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Objective About 20–35% of individuals aged 12–30 years who meet criteria for a prodromal risk syndrome convert to psychosis within two years. However, this estimate ignores the fact that clinical high-risk (CHR) cases vary considerably in risk. Here we sought to create a risk calculator that can ascertain the probability of conversion to psychosis in individual patients based on profiles of risk indicators. The high risk category predicted by this calculator can inform research criteria going forward. Method Subjects were 596 CHR participants from the second phase of the North American Prodrome Longitudinal Study (NAPLS 2) who were followed up to the time of conversion to psychosis or last contact (up to 2 years). Our scope was limited to predictors supported by prior studies and readily obtainable in general clinical settings. Time-to-event regression was used to build a multivariate model predicting conversion, with internal validation using 1000 bootstrap resamples. Results The 2-year probability of conversion to psychosis in this sample was 16%. Higher levels of unusual thought content and suspiciousness, greater decline in social functioning, lower verbal learning and memory performance, slower speed of processing, and younger age at baseline each contributed to individual risk for psychosis, while stressful life events, traumas, and family history of schizophrenia were not significant predictors. The multivariate model achieved a Concordance index of 0.71, and was validated in an independent external dataset. The results are instantiated in a web-based risk prediction tool envisioned to be most useful in research protocols involving the psychosis prodrome. Conclusions A risk calculator comparable in accuracy to those for cardiovascular disease and cancer is available to predict individualized conversion risks in newly ascertained CHR cases. Given that the risk calculator can only be validly applied for patients who screen positive on the Structured Clinical Interview for Psychosis Risk Syndromes, which requires training to administer, it's most immediate uses will be in research on psychosis risk factors and in research driven clinical (prevention) trials.

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Section: Discussionmentioning

confidence: 87%

Section: Discussionmentioning

confidence: 99%

An Individualized Risk Calculator for Research in Prodromal Psychosis

Cannon¹,

Yu²,

Addington³

et al. 2016

AJP

Self Cite

487

415

View full text Add to dashboard Cite

show abstract

“…Based on the results of this meta-analysis, early intervention in schizophrenic patients is believed to result in a clinically significant reduction in the risk of relapse and re-hospitalization. This greatly increases the chances of improving the outcome of treatment and better social functioning [97].The NALPS study [98] looked for effective methods for assessing the risk of psychosis, allowing for early intervention and personalized treatment.…”

Section: Therapeutic Implicationsmentioning

confidence: 99%

“…Tym samym znacznie zwiększa szansę na poprawę wyników leczenia osób chorych oraz lepsze ich funkcjonowanie społeczne [97]. Badanie NALPS [98] poszukiwało skutecznych metod oceny ryzyka rozwoju psychozy, umożliwiających wczesną interwencję i spersonalizowane leczenie.…”

Section: Implikacje Terapeutyczneunclassified

Review paper. Neuropsychological dimension of schizophrenia - evaluation possibilities and therapeutic implications

Makarewicz

Karakuła-Juchnowicz

Łobejko

2017

Current Problems of Psychiatry

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Introduction: In the last decades, researchers' attention has been focused on cognitive dysfunction in schizophrenia. Numerous studies indicate the existence of neurodegenerative deficits in schizophrenia including, but not limited to, motor functions, learning and memory, executive functions, attention, language, spatial skills and general intelligence.Method: A review of available literature on the topic of the past two decades, available in the Pubmed, EBSCO, SCOPUS databases has been made using the keywords: schizophrenia, cognition, early intervention.Results: Cognitive dysfunction is an important feature of the prodromal phase and the first episode of schizophrenia. Researchers have thus proposed to initiate early therapeutic interventions for people with so-called risky mental conditions. The article includes the reference to research on neurocognitive disorders essence in schizophrenia, the definition and review of methods used to identify specific cognitive deficits and issues related to risk of developing psychosis and early therapeutic intervention in high-risk states.Conclusions: Researchers report the importance of detecting cognitive disorders in the early stages of schizophrenia. This broadens the range of therapeutic interventions and enables early intervention in the increased risk of psychosis.

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“…At least in principle, identifying predictors and mechanisms of transition to AD or to psychosis among individuals showing signs of incipient neurocognitive disorders are critical steps in the search for preventive or early intervention strategies (Woodberry, Shapiro, Bryant, & Seidman, 2016). Interest in early detection and prevention of schizophrenia and other psychotic disorders has led to more than a decade of work studying young people who may be at risk of developing a psychotic illness, and advances have been made in prediction of transition to psychosis from a CHR stage (Cannon et al, 2008(Cannon et al, , 2016Carrion et al, 2016), including the usage of neuropsychological measures (Giuliano et al, 2012;Seidman, Giuliano, & Walker, 2010;Seidman et al, 2016).…”

mentioning

confidence: 99%