Psychosis Risk Prediction

Peter Forster Best Practices, Diagnosis, Other Psychiatric Disorders 0 Comments

psychosis risk prediction

Accurate psychosis risk prediction might allow us to provide early intervention and prevention services to young people at risk of developing psychosis. However our current tools for identifying those at risk are not able to accurately predict and identify those who might benefit from these services.

A major step forward was the development of the concept of an At Risk Mental State (ARMS) by clinicians at The Pace Clinic in Melbourne, Australia. The ARMS concept has been internationally validated and did is able to identify young people at increased risk of developing psychotic disorders, mostly schizophrenia spectrum disorders, during the 2 to 3 years after assessment. It has been shown in randomized clinical trials that focused interventions offered to those who meet the criteria can effectively reduce the risk of future illness.

Questions have been raised, however, about whether these criteria are actually more useful than standard diagnostic criteria. The majority of people who develop psychosis do not meet ARMS criteria. So using just these criteria will miss a number of people who might benefit from early intervention services.

Researchers at the Department of Psychosis Studies in London report the development of a calculator that is available online for use by clinicians that may improve the prediction of those at risk. The calculator is designed to be used for any patient first accessing specialty mental health psychiatric care, once an initial diagnosis has been confirmed.

At Risk Psychosis Calculator

This calculator may be of broader usefulness than a similar calculator that was developed by Tyrone Cannon, et al, using data from the North American Prodromal Symptoms study, because that calculator was developed to identify those that increased risk, among a population who already had prodromal symptoms. This new at risk psychosis calculator merely requires that the patient be accessing specialty mental health care services for the first time. In other words, it may identify a larger group of individuals who would benefit from early intervention services.

References

Yung AR, McGorry PD, McFarlane CA, Jackson HJ, Patton GC, Rakkar A (1996). “Monitoring and care of young people at incipient risk of psychosis”. Schizophr Bull. 22 (2): 283–303. doi:10.1093/schbul/22.2.283. PMID 8782287.

Fusar-Poli P, Rutigliano G, Stahl D, Davies C, Bonoldi I, Reilly T, McGuire P. Development and Validation of a Clinically Based Risk Calculator for the Transdiagnostic Prediction of Psychosis. JAMA Psychiatry. 2017;74(5):493-500. doi:10.1001/jamapsychiatry.2017.0284

Lehembre-Shiah E, Leong W, Brucato G, Abi-Dargham A, Lieberman JA, Horga G, Girgis RR. Distinct Relationships Between Visual and Auditory Perceptual Abnormalities and Conversion to Psychosis in a Clinical High-Risk Population. JAMA Psychiatry. 2017;74(1):104-106. doi:10.1001/jamapsychiatry.2016.3055

An Individualized Risk Calculator for Research in Prodromal Psychosis. Tyrone D. Cannon, Changhong Yu, Jean Addington, Carrie E. Bearden, Kristin S. Cadenhead, Barbara A. Cornblatt, Robert Heinssen, Clark D. Jeffries, Daniel H. Mathalon, Thomas H. McGlashan, Diana O. Perkins, Larry J. Seidman, Ming T. Tsuang, Elaine F. Walker, Scott W. Woods, and Michael W. Kattan. American Journal of Psychiatry 2016 173:10, 980-988

 

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