Scientists have developed a new probability model that has shown 70% accuracy in predicting patients, who are at greatest risk of having their first psychotic episode within 12 months, compared with the 28% accuracy of the current criteria.
The new model combines medical history, the latest bedside clinical assessment and biomarkers of fatty acids to determine a patient’s risk of psychosis.
In this preliminary study, the researchers used data from 40 European patients.
Lead author of the research Scott Clark said: “Of those patients, who are considered to be ‘ultra-high risk’, only about 30% of them go on to experience a psychotic episode in the long-term. A more reliable and flexible method of prediction is needed to tailor care appropriately for the people who need it most. Our model represents an enrichment of the diagnostic process,” said Clark.
“Currently all patients in the ultra-high risk group are considered to have a similar chance of a future psychotic episode, however we have been able to identify high, intermediate and low-risk groups. The model may help clinicians to decide when a patient’s risk of psychosis outweighs any side effects of treatment,” he added.
The probability model developed by the team takes into account the critical role of fatty acids as well as mental health assessments.
“Fatty acids such as omega-3 and nervonic acid are critical for the normal functioning of the brain, and low levels have been associated with the development of psychosis in high-risk groups,” he said.
Adding, “In our model, fatty acid levels provided improved accuracy of prediction when patients were at intermediate risk following clinical assessment.”
The study was published in the Nature journal Translational Psychiatry.