Predicting outcomes for young people at high risk for psychosis
Trajectories and Predictors in the Clinical High Risk for Psychosis Population: Prediction Scientific Global Consortium (PRESCIENT)
This project uses clinical information, brain scans, thinking tests, and blood or genetic markers to help predict which young people at high risk for psychosis will develop illness or recover.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Melbourne NIH-funded |
| Lab location | 1 site (Melbourne, Australia) |
| Project ID | NIH-11373932 on NIH RePORTER |
What this research studies
You may be asked to share your symptoms and daily functioning, complete cognitive tests, provide a blood sample for biological and genetic tests, and have a brain scan at a participating clinic. The research team will combine data from many sites around the world and use advanced statistical and machine-learning methods to build models that estimate individual outcomes like developing psychosis, ongoing symptoms, or recovery. They will check these models against independent patient groups to make sure they work reliably. Validated prediction tools will be created so clinicians can use them in routine care to guide early decisions.
Who could benefit from this research
Good fit: Ideal candidates are young people identified as Clinical High Risk for psychosis—those with recent or worsening subthreshold psychotic symptoms, a drop in functioning, or referrals to CHR clinics.
Not a fit: People without early warning signs of psychosis, those with long-standing established psychotic disorders, or those unable or unwilling to attend clinic visits, scans, or blood draws may not benefit or be eligible.
Why it matters
Potential benefit: If successful, this could help clinicians identify who is most likely to become psychotic or who will recover, so treatments can be offered earlier and more precisely.
How similar studies have performed: Previous smaller studies using clinical, cognitive, and brain imaging data produced only modest prediction accuracy, so this larger, pooled multimodal approach aims to improve on past results.
Where this research is happening
Melbourne, Australia
- University of Melbourne — Melbourne, Australia (Active)
Researchers
- Principal investigator: Nelson, Christopher Barnaby — University of Melbourne
- Study coordinator: Nelson, Christopher Barnaby
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.