Accelerating Medicines Partnership® Schizophrenia Observational Study: Psychosis Risk Evaluation, Data Integration, and Computational Technologies -Data Processing, Analysis, and Coordination Center and Coordination Center
Conditions: Clinical High Risk, Psychosis, Remission, Conversion
Sponsor: Brigham and Women's Hospital

Cover Page -  AMP SCZ® Observational Study 
Accelerating Medicines Partnership® Schizophrenia Observational Study 
Document Date: 11/17/2021
Content: 
Study Protocol for Trajectories and Predictors in the Clinical High Risk for 
Psychosis Population: Prediction Scientific Global Consortium (PRESCIENT). 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
1 of 79 | Pages  
 
 
STUDY PROTOCOL 
 
 
Trajectories and Predictors in the  
Clinical High Risk for Psychosis Population:  
Prediction Scientific Global Consortium (PRESCIENT) 
 
 
Protocol Number: HREC 2021. 166 
 
Sponsor: ORYGEN 
35 Poplar Road, Parkville, VIC, 3052 
AUSTRALIA 
Telephone: +61 3 9966 9100 
 
Coordinating / 
Chief Investigator: 
Professor Barnaby Nelson 
Barnaby.Nelson@orygen.org.au 
 
Version: 2.0 
Version Date: Wednesday, 17 November 2021 
 
 
CONFIDENTIALITY STATEMENT 
This document contains proprietary and confidential information belonging to Orygen. Its contents may not be disclosed or used without the 
express permission of Orygen. This document is solely for the use of personnel involved in the conduct of the above mentioned study. 
This document may be disclosed to an ethics committee for the purpose of obtaining approval to conduct a clinical study. Additional uses must 
be approved in writing. 
 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
2 of 79 | Pages  
 
INVESTIGATOR SIGNATURE AND PROTOCOL AGREEMENT: 
I agree to conduct this clinical study in accordance with the design and specific provisions of this 
protocol, Good Clinical Practice, the Declaration of Helsinki, and all applicable laws and 
regulations.   
 
I understand that I may terminate or suspend enrolment of the study at any time if it becomes 
necessary to protect the best interests of the study participants. 
This study may be terminated by Orygen with or without cause. 
 
I agree to personally conduct or supervise this investigation and to ensure that all associates, 
colleagues, and employees assisting in the conduct of this study are informed about their 
obligations in meeting these commitments. 
 
I will ensure that the requirements of the Human Research Ethics Committee (HREC) review and 
approval are met.  I will provide Orygen with any material which is provided to the HREC for 
Ethical approval. 
I agree to promptly report to the HREC any changes in the research activity and all unanticipated 
problems involving risks to human subjects or others.  Additionally, I will not make any changes 
in the research without HREC approval, except where necessary to ensure the safety of study 
participants. 
I commit to involving young people at different levels in the development, conduct and 
communication of the study in a meaningful way, and providing sufficient support to study 
participants. 
 
I agree to maintain adequate and accurate records, and to make those records available for audit 
and inspection in accordance with relevant regulatory requirements. 
 
 
Sponsor Representative 
John Moran  
Chief Operating Officer 
__________________________ 
_________________ 
Name 
Title 
Signature 
Date (dd/mmm/yyyy) 
Coordinating Principal Investigator  
Barnaby Nelson 
Professor 
__________________________ 
_________________ 
Name 
Title 
Signature 
Date (dd/mmm/yyyy) 
Principal Investigator – Site Specific  
_[enter site PI]  
_______________ 
_[enter site PI title] 
________________ 
__________________________ 
_________________ 
Name 
Title 
Signature 
Date (dd/mmm/yyyy) 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
3 of 79 | Pages  
 
 
DOCUMENT HISTORY 
 
Version 
Date 
Summary of change 
1.0 
23/Jul/2021 
Original 
2.0 
17/Nov/2021 
1. Replacement of CAARMS and SIPS measures with 
the Positive Symptoms and Diagnostic Criteria for the 
CAARMS Harmonized with the SIPS (PSYCHS) 
measure.  
2. Removal of the Trauma and Distress Scale (TADS). 
3. Data transfer changes: The data collected across the 
PRESCIENT network will be transferred from Orygen 
(the network hub) directly to the NIMH NDA.  
4. Raw (unprocessed) geolocation data from the digital 
momentary assessments will be included in the data 
transfer to the NIMH NDA.  
5. Digital momentary assessments will now also be 
completed in the healthy control sample.  
6. The healthy control sample in the Melbourne site 
has been increased from 15 to 100 (increasing the total 
healthy control sample from 165 to 250 participants). 
7. The audiotaping of the PSYCHS interview: a) will 
be conducted at all follow up time points, not just at 
screening and month 2, b) it will no longer be an 
optional component.  
8. The Perth recruitment site has been replaced with a 
recruitment site at University of Cologne, represented 
by the University Hospital of Cologne (UHC), 
Germany.  
9. The laboratories for blood and saliva sample 
analysis have been replaced with a statement that the 
specific laboratories for these analyses are yet to be 
determined. 
10. The Psychosis Polyrisk Score (PPS) will be 
conducted at baseline (visit 2) instead of 1 month (visit 
3) in order to ensure full harmonisation with the 
ProNET Research Network. 
11. The Penn Computerised Neurocognitive Battery 
(PennCNB) will be conducted at week 8 (visit 4, 
month 2) instead of week 12 (visit 5, month 3). This 
was a typological error on page 47 of the original 
protocol submission.  
 
 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
4 of 79 | Pages  
 
1. Table of Contents 
1. 
Table of Contents ............................................................................................................ 4 
1.1. 
Tables and Figures ............................................................................................................... 7 
2. 
Study and Sponsor Contacts ......................................................................................... 8 
3. 
List of Abbreviations ...................................................................................................... 9 
4. 
Study Synopsis .............................................................................................................. 13 
5. 
Introduction ................................................................................................................... 18 
5.1. 
The Accelerating Medicines Partnership (AMP) ........................................................... 18 
5.1.1. 
The Need for New Therapies ...................................................................................... 18 
5.1.2. 
The AMP SCZ Approach........................................................................................... 19 
5.1.3. 
Harmonisation of Data collected across the Research Networks ........................ 19 
5.2. 
Clinical High Risk for Psychosis: Background and Significance................................. 20 
5.3. 
The Current Project: The PRESCIENT Research Network ........................................... 21 
5.4. 
Study Aims .......................................................................................................................... 28 
5.5. 
Study Endpoints and Outcome Measures ...................................................................... 29 
5.5.1. 
Primary outcome ........................................................................................................ 30 
5.5.2. 
Secondary outcomes .................................................................................................. 30 
6. 
Study Design .................................................................................................................. 30 
6.1. 
Description .......................................................................................................................... 30 
6.2. 
Study Setting ....................................................................................................................... 30 
6.3. 
Cohort .................................................................................................................................. 31 
6.4. 
Methodology and Design .................................................................................................. 31 
7. 
Participant Population.................................................................................................. 32 
7.1. 
Description .......................................................................................................................... 33 
7.2. 
Sample Size and Power ..................................................................................................... 33 
7.3. 
Recruitment ......................................................................................................................... 34 
7.4. 
Inclusion Criteria ................................................................................................................ 34 
7.5. 
Exclusion Criteria ............................................................................................................... 35 
7.6. 
Discontinuation and Withdrawal .................................................................................... 35 
7.6.1. 
Participant Discontinuation Criteria ....................................................................... 35 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
5 of 79 | Pages  
 
7.7. 
Study Discontinuation Criteria (Stopping Rules) .......................................................... 36 
7.8. 
Replacement of Participants ............................................................................................. 36 
7.9. 
Incorrectly enrolled Participants ...................................................................................... 36 
7.10. 
Withdrawal...................................................................................................................... 36 
8. 
Visits and Assessments ................................................................................................ 37 
8.1. 
Table 2 Schedule of Assessments  .................................................................................... 38 
8.2. 
Demographics, Medical and Psychiatric History .......................................................... 43 
8.3. 
Clinical Assessments .......................................................................................................... 43 
8.4. 
Self-Report Measures ......................................................................................................... 45 
8.5. 
Digital Momentary Assessments ..................................................................................... 46 
8.6. 
Neurocognitive Tasks ........................................................................................................ 46 
8.7. 
Neurophysiological Assessments (EEG Recordings) .................................................... 47 
8.8. 
Biospecimens ....................................................................................................................... 48 
8.9. 
Speech and facial expression samples ............................................................................. 49 
8.10. 
Neuroimaging ................................................................................................................. 50 
8.11. 
Treatment received ......................................................................................................... 51 
8.12. 
Engagement Phone Calls and Text Messages ............................................................ 51 
8.13. 
Data from other sources ................................................................................................ 51 
9. 
Safety Measures ............................................................................................................. 52 
9.1. 
Safety Measures .................................................................................................................. 52 
9.2. 
Definitions ........................................................................................................................... 52 
9.2.1. 
Serious Adverse Event (SAE) ................................................................................... 52 
9.3. 
AE and SAE Assessment ................................................................................................... 52 
9.3.1. 
Causality ...................................................................................................................... 52 
9.4. 
Recording of Adverse Events and Serious Adverse Events......................................... 53 
9.5. 
Expedited and Prompt Reporting of SAEs ..................................................................... 53 
9.6. 
Handling in Cases of Unresolved AEs and SAEs at Completion or Withdrawal .... 53 
9.7. 
Procedures in Case of Medical Emergency .................................................................... 53 
9.8. 
Clinically Significant Results ............................................................................................ 54 
10. 
Study Oversight ......................................................................................................... 55 
10.1. 
Data Safety and Monitoring Committee ..................................................................... 55 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
6 of 79 | Pages  
 
11. 
Ethical Considerations .............................................................................................. 55 
11.1. 
Review by an Ethics Committee .................................................................................. 55 
11.2. 
Ethical Conduct of the Study ........................................................................................ 56 
11.3. 
Consultations with the Youth Research Council ....................................................... 56 
11.4. 
Investigator Responsibilities ......................................................................................... 56 
11.5. 
Participant Data Protection ........................................................................................... 57 
12. 
Study Management ................................................................................................... 57 
12.1. 
Monitoring and Auditing .............................................................................................. 57 
12.2. 
Training of Staff .............................................................................................................. 58 
12.3. 
Changes to the Protocol ................................................................................................. 58 
12.4. 
Protocol Compliance ...................................................................................................... 58 
12.5. 
Study Termination ......................................................................................................... 59 
12.6. 
Data handling and record retention ............................................................................ 59 
13. 
Data Management ..................................................................................................... 60 
13.1. 
Documentation ............................................................................................................... 60 
13.2. 
Database management ................................................................................................... 61 
13.3. 
Protocol Deviations and Suspected/Serious Breaches ............................................. 62 
13.3.1 Protocol Deviations ......................................................................................................... 62 
13.3.2 Suspected Breaches ......................................................................................................... 62 
13.3.3 Serious Breaches .............................................................................................................. 62 
14. 
Statistical Methods .................................................................................................... 63 
15. 
Publication and Use of Study Findings .................................................................. 65 
16. 
Funding ....................................................................................................................... 67 
17. 
Outcomes and Significance ...................................................................................... 67 
18. 
References ................................................................................................................... 69 
 
 
 
 
 
 
 
 
 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
7 of 79 | Pages  
 
 
1.1.Tables and Figures 
Figure 1: The most common clinical trajectories…………………………………...……20 
Table 1: Minimum sample sizes for survival outcome……...………………………….33 
Table 2: Schedule of Assessments…………………………………………………….…..38 
 
 
 
 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
8 of 79 | Pages  
 
2. Study and Sponsor Contacts  
Full lists of sponsor representatives, investigators and project managers maintained 
within Sponsor Contact List and the Study Contact Lists.  
 
 
Contact details 
Sponsor Contacts  
John Moran  
Orygen  
35 Poplar Road   
Parkville, Victoria 3052 
Australia 
+ 61 3 9966 9100  
john.moran@orygen.org.au  
Coordinating 
Principal 
Investigator 
Barnaby Nelson 
Orygen  
35 Poplar Road   
Parkville, Victoria 3052 
Australia 
+ 61 3 9966 9100  
barnaby.nelson@orygen.org.au 
 
 
 
 
 
 
 
 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
9 of 79 | Pages  
 
3. List of Abbreviations 
Abbreviation 
Term in Full 
AE 
Adverse Event 
AEPCC 
Australian Early Psychosis Collaborative Consortium  
AEPRN 
Australian Early Psychosis Research Network 
AMC 
Academic Medical Centre 
ANOVA 
Analysis of Variance 
AQ 
Autism Spectrum Quotient 
AQoL-4D 
Assessment of Quality of Life  
ASSIST 
Alcohol, Smoking and Substance Involvement Screening 
Test 
AUC 
Area Under the Curve 
BLIPS 
Brief Limited Intermittent Psychotic Symptoms 
BOLD 
Blood-Oxygen Level Dependent Imaging 
BPRS 
Brief Psychiatric Rating Scale 
CAARMS 
Comprehensive Assessment of At Risk Mental States 
CC 
Clinical Control 
CHR 
Clinical High Risk for psychosis* 
CMI 
Client Management Interface 
CNP 
Center for Psychiatric Neuroscience 
CORE 
Copenhagen Research Center for Mental Health 
CR 
Clinical Registry 
CRF 
Case Report Form 
CS 
Clinically Significant 
CTTN 
Clinical Trial and Translation Network  
CYMHCTN 
Child and Youth Mental Health Clinical Trial Network  
DPACC 
Data Processing, Analysis and Coordination Center  
DSM-5 
Diagnostic and Statistical Manual for Psychiatric Disorders – 
Fifth Edition 
DSMC 
Data Safety Monitoring Committee 
DUP 
Duration of Untreated Psychosis 
EASY 
Early Assessment Service for Young people with psychosis  
eCRF 
electronic Case Report Form 
EEG 
Electroencephalography 
ELISA 
Enzyme-Linked Immunosorbent Assay 
EMA 
 
Ecological Momentary Assessment 
EPIP 
Early Psychosis Intervention Programme 
EU 
European Union 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
10 of 79 | Pages  
 
Abbreviation 
Term in Full 
FEP 
First Episode Psychosis 
FPFV 
First Patient First Visit 
FSIQ 
Full Scale Intelligence Quotient 
GAD-7 
Generalized Anxiety Disorder 7-item 
GCP 
Good Clinical Practice 
GETIT 
Gwangju Early Treatment & Intervention Team 
GUID 
Globally Unique Identifier  
GWAS 
Genome-Wide Association Studies 
HC 
Healthy Control 
HREC 
Human Research Ethics Committee or local equivalent 
Independent Review Board (IRB) or Institutional Ethics 
Committee (IEC) 
HEP 
headspace Early Psychosis programs 
ICH 
International Conference on Harmonisation 
IPASE 
Inventory of Psychotic-Like Anomalous Self-Experiences 
IQ 
Intelligence Quotient 
K-10 
Kessler Psychological Distress Scale 
LPLV 
Last Patient Last Visit 
MMN 
Mismatch Negativity 
MUFA 
Monounsaturated Fatty Acids 
NCS 
Not Clinically Significant 
NDA 
NIMH Data Archive 
NHGRI 
National Human Genome Research Institute 
NH&MRC 
National Health & Medical Research Council 
NIH 
National Institute of Health 
NIMH 
National Institute of Mental Health 
NRGR 
NIMH Repository and Genomics Resource 
OCTU 
Orygen Clinical Trials Unit 
OASIS 
Overall Anxiety Severity and Impairment Scale 
PGI-I 
Patient Global Impression of Improvement 
PI 
Principal Investigator 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
11 of 79 | Pages  
 
Abbreviation 
Term in Full 
PICF 
Participant Information & Consent Form 
PNS 
Persistent Negative Symptoms 
PSYCHS 
Positive Symptoms and Diagnostic Criteria for the CAARMS 
Harmonized with the SIPS 
PUFA 
Polyunsaturated Fatty Acids 
RGO 
Research Governance Office 
RSWG 
Remission in Schizophrenia Working Group  
PDQ-6 
Perceived Deficits Questionnaire 
PRS 
Polygenic Risk Score 
RA 
Research Assistant 
RDoC 
Research Domain Criteria 
RFA 
Research Funding Announcement 
ROC 
Receiver Operating Characteristic 
SAE 
Serious Adverse Event 
SAE 
Serious Adverse Event 
SCID-5 
Structured Clinical Interview for DSM-5 
SIPS 
Structured Interview for Psychosis Risk Syndromes  
SIS 
Suicidal Ideation Screen 
SMART 
Sequential Multiple Assignment Randomized Trial 
SNP 
Single-Nucleotide Polymorphism 
SOFAS 
Social and Occupational Functioning Scale 
SOP 
Standard Operating Procedure 
SUSAR 
Suspected Unexpected Serious Adverse Reaction 
UHR 
Ultra High Risk for psychosis* 
WASI-II 
Wechsler Abbreviated Scale of Intelligence 
YRC 
Youth Research Council 
*Note: Clinical High Risk (CHR) is the terminology used in the US. Ultra High Risk 
(UHR) is used in Australia. For the purpose of protocol harmonisation with the US-
based research network (ProNET), the term ‘CHR’ is used in this document. 
However, the term ‘UHR’ will be used in participant facing materials in order to 
maintain consistency with clinical service language.  
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
12 of 79 | Pages  
 
 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
13 of 79 | Pages  
 
 
 
4. Study Synopsis 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
14 of 79 | Pages  
 
Item Description 
Study Type Non-interventional  
Study Population The study cohort will consist of young people aged 12 to 30 years 
(inclusive) who are (1) at clinical-high risk of psychosis (CHR) or (2) 
healthy control participants (HC). 
Sample Size The overall sample size is N=1,187. This includes 937 CHR and 250 
HC participants. The participants will be recruited across a network 
of Australian and international clinics.  
Total No. of Study Centres 11 study centres: nine international sites and two Australian hubs. 
Additional recruitment sites may be added or removed as required.  
Study Design Non-interventional study examining clinical trajectories and 
predictors of outcome in the CHR clinical population. The CHR 
cohort will be followed longitudinally for 24 months and will receive 
treatment as usual. The HC cohort will be assessed at baseline. A 
subset of the HC cohort will receive repeat assessments at 2-month 
follow up. HC’s will also be contacted by Research Assistants at 
Months 12 and 24 to determine possible onset of CHR status or a 
psychiatric diagnosis. 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
15 of 79 | Pages  
 
Study Context & Rationale Detection and intervention before psychosis develops, when 
individuals are at clinical high risk for psychosis (CHR), could 
attenuate, postpone, or even prevent the conversion to psychosis and 
improve individuals’ clinical and functional outcomes. The 
Accelerating Medicines Partnership in Schizophrenia (AMP SCZ) is a 
US-based public-private program with the overall aim of generating 
tools that will considerably improve success in developing early stage 
interventions for patients who are at risk of developing schizophrenia and 
other psychotic disorders. The current AMP SCZ partners include 
government partners (NIH, FDA, European Medicines Agency), 
industry partners (Boehringer Ingelheim, Janssen, Otsuka), and non-
profit partners (American Psychiatric Association Foundation, 
National Alliance on Mental Illness, One Mind, Schizophrenia and 
Psychosis Action Alliance, Wellcome). AMP SCZ aims to develop 
measures that further define early stages of risk and predict the 
likelihood of progression to psychosis and other clinical outcomes 
(e.g., non-remission of CHR status, functioning, anxiety, depression, 
and substance use disorders), and define targets for treatment 
development. Such tools will enable clinical trials to test new 
pharmacological interventions that may prevent or delay the onset of 
psychosis. 
In order to realise the aims of AMP SCZ, NIMH released a Research 
Funding Announcement (RFA) in December 2019 to fund CHR 
Research Networks to collect multimodal data in large samples of 
CHR 
patients. 
Two 
international 
networks 
were 
funded: 
PRESCIENT, led by researchers based at Orygen (PI Nelson), and 
ProNET, led by US-based researchers (PI Woods). The current 
Human Research and Ethics Committee submission relates to the 
PRESCIENT Research Network. Additionally, a Data Processing, 
Analysis, and Coordinating Center (DPACC; PI Shenton, Harvard 
University) was funded, with the purpose of integrating and 
analysing data from new and key existing clinical high risk cohorts, 
including the AMP SCZ cohort.  
Findings from AMP SCZ will enable researchers to develop 
algorithms that predict the course of illness for clinical high risk 
individuals, allowing for early intervention and testing of treatments 
that may prevent the development of schizophrenia and other 
psychotic disorders and reduce their impact. All AMP SCZ data and 
analyses will be made publicly available through the NIMH Data 
Archive. Through rapid data sharing and integrated, collaborative 
research, AMP SCZ will enable proof-of-principle clinical trials to test 
tools and hypotheses that emerge from the initiative. 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
16 of 79 | Pages  
 
Primary Objectives 1. CHR Network Consolidation: Use the Australian Early Psychosis 
Collaborative Consortium (AEPCC) national platform to consolidate 
a network of CHR recruitment centres organised according to a ‘hub 
and spoke’ model, with Orygen functioning as the central hub with 1 
Australian and 9 non-Australian clinics as spokes. The network will: 
recruit a large sample of CHR patients (n=937) and a healthy control 
(n=250) sample; implement repeated multimodal assessments; map 
trajectories and outcomes over a 2 year period (conversion to 
psychotic disorder, persistent and incident non-psychotic disorders, 
non-remission of CHR status, persistent negative symptoms, 
psychosocial functioning, full recovery). This network of CHR 
recruitment centres will provide the clinical research infrastructure 
for future treatment trials in this clinical population informed by 
findings from the current program of work. 
 
2. Prediction: In collaboration with the NIMH Steering Committee 
and the DPACC, the PRESCIENT dataset will be used to:  
2a. Test the external validity of existing and forthcoming prediction 
models in the field (e.g., NAPLS, EU-GEI, PRONIA, PSYSCAN). 
2b. Implement the model with strongest performance as an online 
risk calculator that can be calibrated for service setting (primary vs 
specialist settings) and availability of type of data (e.g. clinical data 
alone, clinical data plus neurophysiological data, polygenic risk 
score, etc). 
2c. Use the full AMP SCZ dataset (combined PRESCIENT and 
ProNET data) to develop new, more refined prediction models and 
risk calculators using recent theoretical and methodological advances 
(e.g., dynamic prediction, probabilistic multimodal modelling) and a 
range of biomarkers. These tools will be of clinical utility in decision 
making about stepping interventions up/down as risk is assessed 
over time (clinical trajectory, treatment response) and in response to 
incoming biomarker information, as well as guide stratification of 
patients in future clinical trials. 
 
3. Validation: Internally and externally validate the prediction 
models generated using the AMP SCZ dataset. This will test the 
robustness, replicability and generalisability of the models’ 
performance. 
 
The national and international network of sites and research 
specialisation will provide the clinical research infrastructure for 
future treatment trials in this clinical population informed by 
findings of the current program of work. 
Study Endpoints Clinical data will be collected up to the 24-month follow-up time 
point. See the assessment schedule (section 8.1) for each component 
end-point.  

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
17 of 79 | Pages  
 
Inclusion Criteria ALL 
1. Aged 12-30 years inclusive  
2. Understand and sign informed consent/assent   
3. Meet either CHR or HC criteria  
CHR 
Meet diagnostic criteria for CHR (Vulnerability Group; Attenuated 
Psychotic Symptoms Group; Brief Limited Intermittent Psychotic 
Symptoms Group) as determined using the PSYCHS.  
HC 
Healthy control participants will be recruited from the community. 
HC must not meet any of the exclusion criteria and must not:  
1. Meet CHR criteria or have a current or past Cluster A personality 
disorder. 
2. Be 
receiving 
any 
current 
treatment 
with 
psychotropic 
medication. 
3. Have a family history (in first-degree relatives) of psychotic 
spectrum disorders. 
Exclusion Criteria 1. Antipsychotic medication exposure equivalent to a total lifetime 
haloperidol dose of >50 mg, estimated based on available 
information (e.g., medical file documentation, patient, and family 
report). 
2. Documented history of intellectual disability. 
3. Past or current clinically relevant central nervous system 
disorder. When necessary, Research Assistants will consult with 
study team investigators (including medical personnel) to 
determine if the central nervous system disorder is deemed to be 
clinically relevant.  
4. Traumatic brain injury that is rated as 7 or above on the 
Traumatic Brain Injury screening instrument. 
5. Current or past psychotic disorder, verified using the SCID. 
Data Sources Demographic, 
clinical, 
neurocognitive, 
neurophysiological, 
neuroimaging, digital, speech and biospecimen data will be collected.  
Control Group Healthy controls 
Study Duration November 2021-December 2025 
First Patient First Visit  November 2021 
First Patient Last Visit  November 2023 
Last Patient Last Visit November 2025 
Data Analysis A range of statistical analyses and machine learning approaches will 
be deployed to test study aims. The NIMH-funded US-based Data 
Processing and Analysis Coordination Centre (DPACC) will lead 
data analysis, with input from PRESCIENT and ProNET 
investigators. 
Funding Provided by National Institute of Mental Health (NIMH) 
 
 
 
 
 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
18 of 79 | Pages  
 
5. Introduction 
5.1. 
The Accelerating Medicines Partnership (AMP)  
 
The Accelerating Medicines Partnership (AMP) is a public-private partnership between 
the National Institutes of Health (NIH), the U.S. Food and Drug Administration (FDA), 
European Medicines Agency, and multiple public and private organizations. Managed 
through the Foundation for the NIH (FNIH), AMP aims to identify and validate the most 
promising biological targets for therapeutics. The ultimate goal is to facilitate successful 
development of pharmacological treatments for this early stage of psychotic illness.   
 
There have been a number of AMP projects focused on disorders such as Alzheimer’s 
Disease, Parkinson’s Disease, and diabetes1.  AMP Schizophrenia (AMP SCZ) marks the 
first AMP initiative focused on a neuropsychiatric disorder and the fifth AMP initiative 
overall. The overall aim of AMP Schizophrenia (SCZ) is to generate tools that will 
considerably improve success in developing early stage interventions for patients who are 
at risk of developing schizophrenia and other psychotic disorders (see full details here: 
https://www.nih.gov/research-training/accelerating-medicines-partnership-
amp/schizophrenia). The AMP SCZ current partners include government partners (NIH, 
FDA, European Medicines Agency), industry partners (Boehringer Ingelheim, Janssen, 
Otsuka), non-profit partners (American Psychiatric Association Foundation, National 
Alliance on Mental Illness, One Mind, Schizophrenia and Psychosis Action Alliance, 
Wellcome). The approach is pre-competitive, i.e., research conducted cooperatively 
without potential marketing activities or patenting, with the goal of accelerating and 
advancing research outcomes. The funding for AMP SCZ totals USD 99 million over a 5 
year period. 
5.1.1. The Need for New Therapies 
Detection and intervention before psychosis develops, when individuals are at clinical 
high risk for psychosis, could attenuate, postpone, or even prevent the conversion to 
psychosis and improve individuals’ clinical and functional outcomes. AMP SCZ aims to 
develop measures that further define early stages of risk and predict the likelihood of 
progression to psychosis and other clinical outcomes. Such tools will enable clinical trials 
to test new pharmacological interventions that may prevent or delay the onset of 
psychosis. 
AMP SCZ partners will work towards the shared mission of discovering promising 
biological markers that can help identify those at risk of developing schizophrenia as early 
as possible, track the progression of symptoms and other clinical outcomes, including 
anxiety, depression, and substance use disorders, and define targets for treatment 
development. 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
19 of 79 | Pages  
 
 
5.1.2. The AMP SCZ Approach 
Advancing preventive interventions for schizophrenia and other psychotic disorders 
requires a more complete understanding of the clinical and biological predictors in the 
early stages of the illness. AMP SCZ will harness the power of open science to accelerate 
the research and development process and advance promising therapies for individuals at 
risk of developing these disorders. By combining the expertise and resources of public and 
private partners, AMP SCZ will provide the support needed to determine which 
biomarkers show the greatest potential for predicting progression of the disease in clinical 
high risk individuals. 
A core component of AMP SCZ is establishing a research network focused on individuals 
who are at clinical high risk, identifying biological markers, clinical endpoints, and other 
measures that predict disease trajectory and outcomes in this clinical population.  
To this end, NIMH released a Research Funding Announcement (RFA) in December 2019 
to fund one or two CHR Research Networks. Two international networks were funded: 
PRESCIENT, led by researchers based at Orygen (PI Nelson), and ProNET, led by US-
based researchers (PI Woods). The current Human Research and Ethics Committee 
submission relates to the PRESCIENT Research Network.  Additionally, a Data Processing, 
Analysis, and Coordinating Center (DPACC; PI Shenton, Harvard University) was 
funded, with the purpose of integrating and analysing data from new and key existing 
clinical high risk cohorts, including the AMP SCZ cohort. Findings from these studies will 
enable researchers to develop algorithms that predict the course of illness for clinical high 
risk individuals, allowing for early intervention and testing of treatments that may prevent 
the development of schizophrenia and other psychotic disorders and reduce their impact. 
All AMP SCZ data and analyses will be made publicly available through the NIMH Data 
Archive. Through rapid data sharing and integrated, collaborative research, AMP SCZ will 
enable proof-of-principle clinical trials to test tools and hypotheses that emerge from the 
initiative. 
5.1.3. Harmonisation of Data collected across the Research Networks 
All of the assessment domains, instruments and measurement time points to be used in 
PRESCIENT were decided through an extensive process of team discussion involving 
representatives from NIMH, PRESCIENT, ProNET, the DPACC, and AMP SCZ partners. 
This discussion led to a consensus-based harmonised assessment battery, i.e., a common 
battery of assessment domains and measures that will be used across both recruitment 
networks (PRESCIENT and ProNET), allowing data to be pooled across both samples, 
increasing statistical power and generalisability of findings.   
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
20 of 79 | Pages  
 
 
5.2.Clinical High Risk for Psychosis: Background and Significance 
 
The ‘clinical high risk’ (CHR) for psychosis criteria prospectively identify young people at 
risk of psychotic disorders (i.e., individuals who may be in the prodromal phase of 
psychosis)1, 2. The CHR criteria have been well-validated, with approximately one third of 
CHR individuals converting to a psychotic disorder over a 3-year period, a rate 
considerably higher than in the general population and other clinical populations1, 3, 4. The 
CHR approach introduced a new paradigm to psychosis research and has been remarkably 
influential, with the Diagnostic and Statistical Manual of Mental Disorders-5 (DSM-5) 
including ‘Attenuated Psychosis Syndrome’, based on the CHR criteria, as a condition 
requiring further research5.  
There is substantial heterogeneity in clinical trajectories in the CHR population. For example, 
in a recent analysis of data from our multisite international trial of omega-3 fatty acids 
(‘Neurapro’6) we identified 17 different trajectories in this clinical group7 (see Fig 1 for the 
most common trajectories). The field is currently unable to reliably identify these 
trajectories early on, particularly at an individual patient level. The models to date (using 
clinical, neurocognitive, neuroimaging, neurobiological and genetic data) have yielded 
only modest predictive value for conversion to psychotic disorder and other outcomes3, 8, 
9. This presents a challenge for targeted intervention and developing robust aetiological 
models. There is also now increased recognition of the CHR phenotype as a syndrome in 
itself, rather than merely being a risk syndrome, supported by meta-analytic evidence that 
CHR patients are characterised by consistent and large impairments in functioning and 
reduction in quality of life similar to those in other coded psychiatric disorders10-12. In 
addition, there is strong evidence that CHR status is a marker of illness severity and poor 
prognosis transdiagnostically13-15. Therefore, enhancing prediction of the full spectrum of 
outcomes in the CHR population (conversion to psychotic disorder, persistent and incident 
non-psychotic disorders, non-remission of CHR status, poor functioning etc.) is of critical 
importance16, 17. Enhanced predictive accuracy of these outcomes would be a substantial 
step forward in facilitating treatment development and developing aetiological models of 
psychosis and psychiatric disorders more broadly.  
 
 
Figure 1. The most 
common clinical 
trajectories identified in a 
CHR sample (n=202) over 
a 12-month period7. 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
21 of 79 | Pages  
 
 
The current study aims to recruit a large sample of CHR patients in order to develop 
refined prediction models for stratification of patients in clinical trials and as tools for use 
in clinical practice. This will lead to substantial benefits for clinical care (e.g., using 
dynamic risk calculators to estimate the risk for a range of outcomes for individual 
patients, inform personalized treatment strategy, and serve as measures of early treatment 
effects), healthcare services (informing decision-making regarding allocation of resources), 
and for research in this field (stratification of samples for treatment trials, directing the 
engagement of treatment targets, and refining aetiological models).  
 
Specifically, we will:  
1. Use an existing nationwide clinical infrastructure and nine international clinics (the 
PRESCIENT network) to support recruitment and follow up of a large cohort of CHR 
young people (n=937) and a healthy control group (n=250). Recruitment will occur over 2 
years and participants will be followed for a 2-year period with repeat assessments over 
this timeframe. Biomarker assessments will be repeated 2 months after baseline in CHR 
participants and in a subset of healthy control participants. 
2. Use this dataset to: a) validate existing and forthcoming prediction models and b) draw 
on the full AMP SCZ dataset to develop new, more refined prediction models using recent 
methodological advances and exploratory biomarkers. 
3. Externally validate the prediction models generated in the AMP SCZ dataset using a 
subsample of the cohort. This will test the replicability of the model’s performance and the 
generalisability of the findings to diverse healthcare settings. 
 
5.3.The Current Project: The PRESCIENT Research Network 
 
5.3.1 Nationwide network of early psychosis services and youth mental health 
services 
 
In 2015, Orygen established the Australian Early Psychosis Research Network as a 
collaborative venture linked to the new development of the Federal government funded 
headspace Youth Early Psychosis Program (HEP) service platform, which we designed and 
advocated for18. The aim of this network was to bring together key researchers from a 
diverse range of services in Australia including the HEPs, with an interest in clinical 
research in early or emerging psychosis. In 2019, the Australian Early Psychosis 
Collaborative Consortium (AEPCC) was established, with funding support from the 
Wellcome Trust, introducing a national platform for a Clinical Registry (CR) and Clinical 
Trial and Translation Network (CTTN). The AEPCC lead investigators are represented in 
the current application. The foundation members of AEPCC include all HEP services 
across Australia and Orygen clinical services, which provides comprehensive mental 
health care to 15-25 years olds in Northwestern Melbourne (see Fig 2a). This reflects the 
uniformity of purpose and potential for momentum and uptake in the Australian early 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
22 of 79 | Pages  
 
psychosis sector. The assessment and treatment provided in these services has been subject 
to a stringent fidelity process directed by Orygen. The AEPCC CR and CTTN is set to 
realise the potential of the Australian Early Psychosis Research Network (AEPRN) and 
lead to activation of a proposed national Child and Youth Mental Health Clinical Trial 
Network (CYMHCTN).  
Over the last fifteen years, the research team and other members of the Orygen clinical 
academic leadership have developed a youth mental health service model that has been 
implemented nationally through the headspace platform. Headspace is an innovative system 
reform and development that received policy commitment, funding and national roll-out 
by the Australian Federal Government, starting in 2006. It has involved the creation and 
upscaling of a nationwide platform of care, which has already enabled access to care for 
over 524,800 young Australians with emerging mental ill health19, with evidence of clear 
positive impact20. Headspace is essentially a ‘one stop shop’, universal access stigma-free 
model of care for young people and families experiencing early stage mental disorders21-
25. Orygen conceived, designed and implemented this reform which has now expanded 
across the country to 110 centres with 150 being active by 2022 (see Fig 2b). The headspace 
centres provide the case detection and referral platform for the co-located HEPs, resulting 
in a low stigma and high volume pathway into specialist early psychosis services.  
The current network (PRESCIENT) will recruit across Orygen specialist programs and 
clinical services, one national HEP program, as well as nine international sites. Orygen 
clinical services consist of two tiers of care that are seamless and fully integrated: one tier 
consists of broad, primary care youth mental health services (5 headspace clinics in 
Northwestern Melbourne) and a secondary care tier that provides specialist early 
psychosis services across the same region (Orygen Specialist Program, Melbourne Health). 
The PRESCIENT network has partnered with international centres across Europe and Asia 
for the current program of work.  
 
5.3.2 Leveraging the nationwide network for CHR recruitment (aim 1) 
The clinical infrastructure described above provides clinical services for young people 
with a range of clinical presentations. In the 2018-2019 financial year, approximately 3,000 
young people accessed HEP services, 1000 young people accessed Orygen Specialist 
Program, and over 5,000 young people accessed the 5 headspace clinics involved in the 
network (i.e., 6000 across the clinics directly operated by Orygen)19. Data on CHR status of 
this pool of patients is available from a range of sources including our cohort studies26, 27, 
the Staged Treatment in Early Psychosis (STEP) study28, and clinical service records. These 
data sources indicate that 15% of HEP patients, 15% of Orygen Specialist Program patients, 
and ~30% of headspace patients meet CHR criteria. In raw numbers, this translates to ~2,000 
CHR patients/year. Therefore, our recruitment target of 468 CHR patients per year over a 
two-year period (937 in total) equates to recruiting <25% of the pool of eligible patients. 
This is highly feasible, given that recruitment rates to current CHR studies being 
conducted by our group (across the same clinics) consist of 50% of eligible patients.   
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
23 of 79 | Pages  
 
5.3.3 Extending minimal data sets in order to test and develop prediction models 
Both the headspace and HEP clinics provide a sampling frame with linked minimal data 
sets. Our network of headspace clinics collect a minimal data set as part of routine clinical 
practice25, 29. The AEPCC will establish a clinical registry for all early psychosis patients, 
including CHR patients. While these minimal data sets are invaluable for better 
characterizing this clinical population and standardizing assessment and routine data 
collection practice, they are not sufficient for building and testing prediction models with high 
levels of accuracy, which is required in this research field. 
The minimal data set of headspace patients includes: reason for presentation, Kessler 
Psychological Distress Scale (K10), stage of illness, diagnosis, and functioning25. The HEP 
minimal data set includes demographics, referral pathways, prior treatment, stage of 
psychotic illness (CHR or FEP, determined using the Comprehensive Assessment of At 
Risk Mental States [CAARMS]), general distress (K10), functioning (Social and 
Occupational Functioning Assessment Scales [SOFAS]) and quality of life, and details of 
treatment received, including medication, inpatient admissions, psychosocial treatment, 
and patient and family satisfaction with treatment.  
In the current study, we will work with the Data Processing, Analysis, and Coordination 
Center (DPACC) to build on these minimal data sets to collect a far more comprehensive 
data set, supported by a number of conceptual and analytical advances in the field, but 
also balanced with issues of feasibility and awareness of participant burden. We briefly 
summarise these conceptual and analytical advances below.  
Dynamic prediction, early warning signs and network theory: Over recent years, in 
collaboration with European colleagues, we have approached modelling and predicting 
onset and evolution of psychotic disorder and other mental disorders through a dynamic 
(i.e., time-dependent or time-variable) lens in order to supplement the standard static 
prediction approach that relies exclusively on baseline (clinic or study entry) data30-36. This 
draws on approaches that have proven to be useful in other areas of psychiatry (e.g., 
predicting relapse in depression37, 38) and which have yielded greater predictive accuracy 
in other areas of medicine, such as cardiovascular research39 and oncology40, as well as in 
other disciplines that model complex systems, such as ecology41, 42 and economics43. 
Consistent with our clinical staging model44-46, this dynamic approach to prediction is well-
suited for incorporating the highly changeable and mercurial nature of psychopathology, 
particularly in the early stages of disorder34. Analytical tools to operationalise these 
dynamic approaches include various forms of time series analysis, joint modelling, and 
network analysis.  
Time series analysis involves analysis of a series of data points indexed in time order. 
Patterns in the data that emerge over time can be used for the purpose of forecasting future 
values. This approach has been more widely deployed in other areas of psychiatry, e.g. 
depression and transdiagnostic prediction36, 38, 47, 48, than in psychosis prediction. In these 
other areas, particular temporal patterns in the data, including increase in emotional state 
correlating with itself over time (‘temporal autocorrelation’) and increased variance and 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
24 of 79 | Pages  
 
change in the association between emotions over time have proven valuable as ‘early 
warning signs’ of an imminent change in mental state (e.g., ‘tipping point’ into a 
depressive episode)38, 48, 49. In the area of psychosis and psychosis risk, the focus has instead 
been on the proximal relationship between everyday events/contexts and momentary 
fluctuations in mental state, such as stress sensitivity assessed using ecological momentary 
assessment (EMA), rather than on prediction of clinical outcomes50-53.  
Joint modelling is an emerging statistical methodology that uses longitudinal, repeat 
assessment of variables (‘time-dependent predictors’) to predict outcomes with variable 
time frames. It is therefore a useful means of adjusting prognosis for patients as relevant 
variables are assessed repeatedly over time, yielding dynamic risk calculation. Our group, 
led by Associate Investigator Yuen, has already introduced this approach to CHR 
prediction research30-33. In this work, a joint model using repeat monthly assessments 
yielded superior prediction statistics for conversion to psychosis compared to static 
baseline assessment in the same CHR cohort31, 33. Comparing the receiver operating 
characteristic (ROC) curves, the area under the curve (AUC) of the joint model was 
significantly greater than that of the baseline model (p-value=0.019). Also of note is that, 
for the point closest to the ideal point (0,100), the joint model showed substantially higher 
sensitivity (83% vs. 69%) and similar specificity as the baseline model (72% vs. 74%), 
indicating that the joint model was able to detect more converted cases yet with little 
increase in false positive rate. The strong predictive performance of this approach has 
recently been confirmed by another group in an independent data set54.  
Network theory posits that symptoms are not all explained by a shared underlying cause, 
as in the traditional latent disease model (e.g., lung cancer being the underlying common 
cause of various symptoms such as shortness of breath, chest pain, and coughing up 
blood)55. Rather, mental disorders are seen as complex dynamic systems in which 
symptoms and psychological, biological and social components have autonomous causal 
power to influence and trigger each other56, 57. If symptoms form patterns of mutual 
reinforcement and feedback loops, the system as a whole may become trapped or ‘locked’ 
in a state of extended symptom activation, a point at which a mental disorder may be 
diagnosed (e.g., conversion to psychosis). Network analysis models the pairwise 
relationship (‘edges’) between symptoms (‘nodes’) cross-sectionally and dynamically over 
time (using time series), showing interactions between symptoms55. It is plausible that this 
‘locked’ state is more likely to occur in biologically vulnerable people; however, this 
process may be interrupted by psychosocial and biological early intervention strategies. 
These possibilities can be assessed in the current dataset by examining interactions 
between data modalities over time (e.g., digital momentary assessments and biomarkers), 
as well as modelling impact of treatment exposure.   
Importantly, these approaches are well suited for modelling the natural course of disorder 
(e.g., increasing symptomatology) and the impact of time-varying exposures (e.g., adverse 
life events) as well as treatment. They can be applied to any type of data. Although 
phenotypic data has been the principal type of data used in these analytical approaches to 
date, they can also be applied to biomarker data. For example, persistent language 
disturbance58, accelerated grey matter loss59 or decreases over time in EEG-assessed 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
25 of 79 | Pages  
 
mismatch negativity60 or N-1 suppression scores61 would all be appropriate for statistical 
modelling using these approaches. These dynamic analytical approaches will be applied 
to the data collected in the current network, in collaboration with the DPACC.  
Multimodal prediction: In addition to dynamic prediction approaches, multimodal (using 
multiple assessment domains or levels of analysis) have also proven valuable in enhancing 
predictive accuracy. An example of this approach is probabilistic multimodal modelling 
using the odds ratio form of Bayes’ Rule to develop probabilistic models of outcome (e.g., 
conversion to psychosis) based on data from combining different modalities (e.g., clinical 
data alone vs clinical data plus neuroimaging data vs clinical data plus neurocognitive 
plus neuroimaging data)62, 63. Recent empirical work by the research team has indicated 
that this approach can improve on prediction based on data from one domain alone63. For 
example, we recently showed that a probabilistic multimodal model combining clinical 
history, symptoms, and fatty-acid biomarkers identified over 70% of CHR cases who 
converted to psychosis within one year, compared with 28% identified by standard CHR 
criteria32, 63. This approach in fact models, and can be used to further refine, real clinical 
decision-making regarding the need for further types of diagnostic assessments based on 
outcomes of each step in assessment, accounting for the baseline risk of conversion in the 
population from which the individual derives (e.g., help-seeking in a specialist clinic vs 
general population samples). This can directly inform indicated treatment based on level 
of risk established. Similarly, in the EU-based PRONIA study64, supplementing clinical 
ratings with structural imaging (MRI) was found to increase predictive accuracy for 
functional outcome in CHR patients from 77% (clinical measures alone) to 83% (clinical 
measures + MRI). However, adding different data types has not always been found to 
increase predictive accuracy substantially. For example, Perkins et al65 recently found that 
adding a polygenic risk score (PRS) to a risk calculator based on patient history, clinical 
variables and neurocognitive variables only modestly improved psychosis risk prediction. 
There is, therefore, a need to further identify the types of data that provide the greatest 
predictive accuracy, which types of assessments to prioritize, and in what context (e.g. 
specialized vs primary health care settings) multimodal prediction approaches are feasible 
and useful in predicting outcomes for individual patients. These issues will be addressed 
in the work of the current network.  
 
5.3.4 Rationale for PRESCIENT assessment domains and measures  
All of the assessment domains and measures to be used in PRESCIENT were decided 
through an extensive process of team discussion involving representatives from NIMH, 
PRESCIENT, ProNET, the DPACC, and AMP SCZ partners. This discussion led to a 
consensus harmonised assessment battery, i.e., a common battery of assessment domains 
and measures to be used across both recruitment networks (PRESCIENT and ProNET), 
allowing data to be pooled across both samples. A 2-month time point was chosen for the 
repeat biomarker assessments because: 1) the trajectory of change from baseline to 2 
months has been found to be most useful for predictive modelling in existing data and 2) 
this time period can be used to inform the design of future clinical trials.  

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
26 of 79 | Pages  
 
Clinical measures: Key considerations in the choice of clinical measures was to capture 
variables that have been found to be relevant to CHR outcomes, to capture the broad range 
of transdiagnostic symptomology present in this clinical population, and to minimise 
participant and assessor burden. As per previous studies, these measures will be 
integrated into a seamless clinical interview schedule.  
Digital momentary assessments: Digital momentary assessments provide an ideal way of 
collecting data for digital phenotyping that can be used in dynamic prediction approaches. 
The most widely used and validated approaches for collecting these types of data are: i) 
intensive longitudinal EMA, the repeated (daily) sampling of a participant’s experiences 
and behaviours in its natural environment over an extended period of time using a 
smartphone app and ii) passive sensing in the form of monitoring gross motor activity 
(wearable accelerometer) and movement patterns (phone-based GPS data). Both 
approaches will be used in the current study.  
Neurocognition: The neurocognitive assessment domains that have been included in the 
current study are those that have been found to be most relevant in previous CHR 
prediction research. The criteria considered in designing the battery included: being 
relatively culturally unbiased, computerised automated scoring, automated quality 
control and databasing, deployable in resource limited settings, reliability and validity, 
being repeatable, time efficient, amenable to advanced psychometrics, sensitive to sex as a 
biological factor and age effects, offering targets for treatment, being open source/public 
domain, amenable to remote administration, and offering genomic biomarkers.  
Neurophysiology: EEG-based event-related potential and event-related oscillation 
measures are relatively inexpensive to acquire and provide direct measurements of 
summated neurophysiological activity with millisecond temporal precision.  The rationale 
for inclusion of the paradigms and measures is summarized in the table below60, 61, 66, 67. 
 
Measure 
Abnormal 
in 
schizophrenia 
Abnormal 
in CHR 
Predicts 
conversion to 
psychosis 
Predicts 
CHR 
remission 
Moderate 
to 
Strong 
Test-Retest 
Reliability 
Altered by 
NMDA 
blockers in 
pharm 
challenge 
studies 
Analog 
in rodent 
models 
MMN 
++ 
+/- 
++ 
- 
+ 
+ 
+ 
RP 
+/- 
+ 
+ 
- 
? 
? 
+ 
Auditory Target P3b 
++ 
+ 
++ 
+ 
+ 
+ 
- 
Auditory Novel P3a 
+ 
+ 
- 
+/- 
+ 
+ 
+ 
Aud Alpha Desynch 
+ 
+ 
+ 
- 
? 
? 
? 
Visual Target P3b 
+ 
+ 
+ 
+/- 
+ 
+ 
- 
Visual Novel P3a 
+ 
+ 
+ 
+/- 
+ 
+ 
+ 
40 Hz ASSR ITC 
+ 
+ 
-/+ 
- 
+ 
+ 
+ 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
27 of 79 | Pages  
 
Resting State EEG 
Power Spectra, 1/f 
+ 
+/- 
+/- 
+/- 
+ 
+ 
+ 
 
Biospecimens (blood and saliva samples): The biospecimens chosen are based on 
commonly reported and novel biomarkers, and those that have shown prospective 
associations with illness trajectories, both of psychosis68, 69 and mood and anxiety 
disorders70. Alterations of the levels of several immune proteins and oxidative stress 
markers have been described in patients with psychotic and mood disorders, and such 
patterns may be indicative of trait or state characteristics71-73. Serological studies suggest 
that some cases of schizophrenia and bipolar disorder may be associated with exposure to 
microbial infections74. New ‘omic technologies now allow cost-effective screens of lipids, 
metabolites, proteins. Recent findings implicate the complement and coagulation pathway 
in predicting psychotic experiences and psychotic disorder75-77, and are therefore also 
included in the current battery. The genetic studies of the last decade have demonstrated 
that psychiatric disorders are highly polygenic and pleiotropic. Polygenic risk scores (PRS) 
can leverage the genetic information from the large genome-wide association studies 
(GWAS) to predict genetic risk in clinical samples. PRS are not accurate diagnostic tools, 
but can be considered as biomarkers that can become part of the predictive algorithm65. 
Currently, the AUC associated with schizophrenia PRS is about 0.75, and those in the top 
10% of a population distribution have an increased risk approximately equivalent to the 
risk of having an affected first degree relative. Blood samples will be used to isolated DNA 
for generation of PRS.  
Evidence from two CHR cohorts suggests that the stress mediator cortisol is associated 
with conversion to psychosis68, 78, 79.We have recently shown that a multisystem biomarker 
index reflecting immune activation, stress signalling and energy metabolism is associated 
with increased risk for persistent poor functioning in the CHR population80. Given that 
both systemic inflammation and HPA-axis function are implicated not only in psychosis 
but also in mood disorders81, it is highly likely that such processes represent 
transdiagnostic risk mechanisms for emerging mental disorders, a target of investigation 
in the current study. Therefore, we will supplement the measurement of inflammatory 
response and oxidative stress via a saliva sample.  
Speech and facial expression samples: Language production (e.g., indices of semantic 
coherence and syntactic complexity) has shown promise as a marker of psychosis risk82, 83. 
A benefit of speech samples is that they are easily obtained and highly acceptable to 
patients. We are currently successfully collecting a large database of speech samples in 
CHR and first episode psychosis patients (supported through NIMH grant R01MH115332-
01) and will extend this pool of data in the current assessment battery. Speech samples will 
be collected both in the context of an interview with a Research Assistant and in the course 
of daily life via a phone-based audio diary (see 8.5). In addition, disruption in facial 
expressivity84 has been found to predict conversion to psychosis in CHR samples, and has 
therefore been incorporated into the current battery via video recordings during the open-
ended speech collection interview.  

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
28 of 79 | Pages  
 
Neuroimaging: Neuroimaging studies over the past twenty years have demonstrated 
significant associations between alterations in brain structure and connectivity and 
subsequent conversion to psychosis, with clear indications that these measures can 
improve individual prediction85. There is also evidence that neuroimaging can provide 
predictive utility for outcomes other than conversion64. The neuroimaging measures 
included in the current battery provide a comprehensive coverage of anatomy (brain 
volume, cortical thickness, etc.), microstructure (white matter), and both structural and 
functional connectivity. Measures derived from these acquisitions have been implicated in 
previous studies as abnormal in CHR populations and show dynamic changes between 
CHR and later stages of psychosis. The selection of measures and their particular 
parameters is optimized for the current state of the art analyses. Tier 1 is also expected to 
be relevant for analysis development over the next 5 years. 
5.4.Study Aims 
 
1. CHR Network Consolidation: Use the Australian Early Psychosis Collaborative 
Consortium (AEPCC) national platform to consolidate a network of CHR recruitment 
centres organised according to a ‘hub and spoke’ model, with Orygen functioning as the 
central hub with one Australian and nine non-Australian clinics as spokes. The network 
will: recruit a large sample of CHR patients (n=937) and a healthy control (n=250) sample; 
implement repeated multimodal assessments; map trajectories and outcomes over a 2 year 
period (conversion to psychotic disorder, persistent and incident non-psychotic disorders, 
non-remission of CHR status, persistent negative symptoms, psychosocial functioning, full 
recovery). This network of CHR recruitment centres will provide the clinical research 
infrastructure for future treatment trials in this clinical population informed by findings 
from the current program of work. 
 
2. Prediction: In collaboration with the NIMH Steering Committee and the DPACC, the 
PRESCIENT dataset will be used to:  
2a. Test the external validity of existing and forthcoming prediction models in the field 
(e.g., NAPLS, EU-GEI, PRONIA, PSYSCAN). 
2b. Implement the model with strongest performance as an online risk calculator.  
2c. Use the full AMP SCZ dataset to develop new, more refined prediction models and risk 
calculators drawing on recent theoretical and methodological advances (e.g., dynamic 
prediction, probabilistic multimodal modelling) and a range of biomarkers. These tools 
will guide stratification of patients in future clinical trials and may have clinical utility in 
decision making about stepping interventions up/down as risk is assessed over time 
(clinical trajectory, treatment response) and in response to incoming biomarker 
information, as well as guide stratification of patients in future clinical trials. 
 
3. Validation: Internally and externally validate the prediction models generated in the 
AMP SCZ dataset. This will test the robustness, replicability and generalisability of the 
models’ performance. 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
29 of 79 | Pages  
 
 
The purpose of recruiting a sample of healthy control participants is primarily to model 
site effects of biomarker measurement, particularly for neuroimaging data. However, this 
cohort also serves the purpose of: providing benchmark ‘normal’ levels on the various 
measures included in the schedule of assessments; modelling age effects; and assessing the 
stability of the biomarkers in healthy individuals. 
 
5.5.Study Endpoints and Outcome Measures 
Participants will be followed up at regular intervals over a 24-month period (see 
assessment schedule in 8.1). The primary outcome timepoint of interest is the 24-month 
follow point. Outcomes of interest are listed below: 
Conversion to psychotic disorder. This is operationalised, as: 
(A) At least one full threshold positive psychotic symptom as operationalised using the 
PSYCHS for one week or longer occurring (i) for more than an hour a day, 3-6 days 
per week OR (ii) daily for less than one hour  
OR 
(B) At least one full threshold positive psychotic symptom with the above frequency but 
lasting less than one week in the context of newly prescribed or newly increased 
antipsychotic medication 
OR 
(C)  At least one full threshold positive psychotic symptom that is immediately dangerous 
– as assessed by the treating psychiatrist. 
The projected number of converted cases across AMP SCZ is 300 (15% conversion rate)7. 
Remission of CHR status7. The definition of remission from CHR status has previously been 
published87 and is currently being used in our ongoing intervention trial28. It is modelled 
on the schizophrenia course definitions presented by the Remission in Schizophrenia 
Working Group (RSWG)88 and was agreed upon using a consensus process amongst CHR 
clinical and research experts. It requires no longer having attenuated psychotic symptoms 
in the CHR range, as assessed using the PSYCHS. For the Trait and State Risk Factor and 
Brief Limited Intermittent Psychotic Symptoms (BLIPS) groups, remission is defined as 
having achieved good functioning and no longer meeting criteria for schizotypal 
personality disorder (if present at baseline) and not having had onset of attenuated 
psychotic symptoms in the CHR range. 
Recovery from CHR status7. Remission maintained for at least six months. 
Relapse of CHR status7. Presence of CHR status after recovery (i.e., meeting PSYCHS 
severity, frequency and duration criteria for CHR status after recovery has been achieved).  
Persistent non-psychotic disorders. A non-psychotic disorder which is present both at study 
entry and at outcome time point and from which full remission has not been achieved over 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
30 of 79 | Pages  
 
the interim. This will be determined using the Structured Clinical Interview for DSM-5 
(SCID-5).  
Incident non-psychotic disorders. A non-psychotic disorder present over the follow up period 
but not present at study entry. This will be determined using the SCID-5. 
Persistent negative symptoms (PNS). As per our previous research89, and consistent with the 
definition of Buchanan90, PNS are defined as the presence of at least one Negative 
Symptoms Inventory (NSI) global subscale score ≥3 at baseline and at follow up, a 
combined total score of 6 or less on the Brief Psychiatric Rating Scale (BPRS) subscales of 
depression, guilt and suicidality (corresponding to an average of “very mild” or less on 
each item), and a combined total score of 16 or less on the BPRS psychotic subscales of 
conceptual disorganisation, hallucinations, suspiciousness and unusual thought content 
(corresponding to an average of “moderate” or less on each item).  
Psychosocial functioning. SOFAS score at outcome time points.  
 
5.5.1. Primary outcome 
The primary outcome of interest is conversion to psychotic disorder by 24 month follow 
up (definition in 5.4). 
5.5.2. Secondary outcomes 
Secondary outcomes of interest are: remission, recovery and relapse of CHR status, 
psychosocial functioning, persistent and incident non-psychotic disorders, and persistent 
negative symptoms.   
 
6. Study Design 
6.1.Description 
This is a non-interventional study examining clinical trajectories and predictors of 
outcomes in the CHR clinical population. The CHR cohort will be followed over a 24-
month period and will receive study assessments at regular intervals. CHR participants 
will receive ‘treatment as usual’ (i.e., treatment will not be controlled). The HC cohort will 
be assessed at baseline. A subset of the HC cohort will receive repeat assessments at 2-
month follow up. 
6.2.Study Setting 
The study will recruit across the following sites: 
1. 
Melbourne - Orygen Specialist Programs, Melbourne 
2. 
Melbourne - headspace Glenroy  
3. 
Melbourne - headspace Werribee  
4. 
Melbourne - headspace Sunshine 
5. 
Melbourne - headspace Craigieburn 
6. 
Melbourne - headspace Melton 
7. 
Melbourne Orygen Clinical Trials Unit, Parkville 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
31 of 79 | Pages  
 
8. 
Adelaide – headspace Adelaide and Adelaide HEP (headspace Early Psychosis 
program) 
9. 
Gwangju Early Treatment & Intervention Team (GETIT) Clinic, Gwangju, South 
Korea   
10. Early Psychosis Intervention Programme (EPIP) Clinic, Buangkok, Singapore   
11. Academic Medical Centre (AMC), Amsterdam, The Netherlands  
12. Copenhagen Research Center for Mental Health (CORE), Copenhagen, Denmark  
13. The University Hospital Jena, Department of Psychiatry, Jena, Germany   
14. University of Cologne, represented by the University Hospital of Cologne (UHC), 
Cologne, Germany 
15. Treatment and Early Intervention in Psychosis Program (TIPP) & Center for 
Psychiatric Neuroscience (CNP), Department of Psychiatry, Lausanne University 
Hospital, Lausanne, Switzerland   
16. Forward Thinking Birmingham, Birmingham, UK  
17. Department of Psychiatry, University of Hong Kong 
 
The non-Australian CHR sites have been selected on the basis of proven capacity to recruit 
CHR participants, previous collaborations with the coordinating centre, high-quality 
assessment practices, and expertise with the proposed assessment battery.  
6.3.Cohort 
CHR: 937 CHR patients as determined using standardised PSYCHS diagnostic criteria 
(see 7.4).  
Healthy control (HC) participants: 250 healthy controls will be recruited from the 
community.   
6.4.Methodology and Design 
Participants from both samples will be assessed at Baseline. Refer to Section 8.0 for a full 
list of the measures and their explanation. The CHR sample will be followed up at regular 
intervals (see 8.0) for a total period of two years. A two year follow up period has been 
found to capture most CHR cases who convert to psychotic disorder91. Contact will be 
made with CHR participants between assessment time points (via phone calls, text 
messages or emails) in order to maintain engagement and address any technological 
troubleshooting issues with the digital momentary assessments. It is intended that if CHR 
participants are unable to be re-interviewed, their diagnostic status at last clinical contact 
will be sourced from their medical record files and state medical records (the client 
management interface [CMI] database for Victoria, Australia or local equivalent). HC 
participants will be assessed at baseline, at 2-month follow up, and at 12-month and 24-
month follow up (see section 8.0). 
 
The screening visit will take approximately 2 hours to complete. The full baseline 
assessments will take approximately 9–10 hours to complete (3-4 hours for clinical 
assessments, 1 hour for neurocognitive assessment, 2 hours for neurophysiological 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
32 of 79 | Pages  
 
assessments, 1.5 hours for neuroimaging, 20 minutes for free speech recording, and 30 
minutes for blood). A saliva sample will be also be collected during one of the baseline 
visits. The baseline assessments may be completed over multiple sessions in order to 
minimise participant fatigue. There will also be a 30-min induction/information session at 
baseline for the digital momentary assessment component. The approximate duration of 
follow up assessments are as follows: 
• Months 1 and 3: (90 minutes for clinical assessment) 
• Months 2: 7.5 -8.5 (2-3 hours for clinical assessment, 45 minutes for neurocognitive 
assessment, 2 hours for neurophysiological assessment, 20 minutes for free speech 
recording, 30 minutes for blood, and 1.5 hours for neuroimaging) 
• Months 4, 5, 7, 8, 9, 10 and 11: 20 minutes (BPRS clinical assessment only) 
• Month 6: 2.5 hours (2 hours for clinical assessment and 30 minutes for neurocognitive 
assessment) 
• Month 12: 3.5–4 hours (2.5-3 hours for clinical assessment, and 30 minutes for 
neurocognitive assessment) 
• Month 18: 2 hours (clinical assessment) 
• Month 24:  3.5   hours (2.5–3 hours for clinical assessment and 45 minutes for 
neurocognitive assessment)  
As an acknowledgement of the time and effort involved in taking part in the study, 
participants will be reimbursed as outlined below:   
 
• $60 for the baseline clinical interview 
• $40 for each follow up clinical assessment time-point 
• $40 for each neurocognitive assessment 
• $50 for each MRI 
• $50 for each EEG assessment 
• $30 for each free speech interview  
• $30 for each blood test 
• $30 for a saliva sample time-point which includes 3x samples over 2 hours 
• Up to $150 (depending on how much the participant completes) for the digital 
assessment component. This will be paid pro rata in monthly instalments.  
In order to acknowledge the contributions of participants who complete all assessment 
components and time points as part of the study (excluding the digital assessment 
component), a ‘completion payment’ of $100 ($50 for healthy controls not selected for the 
2-month follow up) will also be provided to the participant at the end of the study along 
with their month 24 follow up clinical assessment payment.   
 
7. Participant Population 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
33 of 79 | Pages  
 
7.1.Description 
CHR patients and HC patients aged between 12-30 (inclusive). For further information 
about study group criteria refer to Section 7.4. 
7.2.Sample Size and Power 
The size of the CHR sample is primarily determined by the aim of developing a prediction 
model for conversion to psychosis by 24 months (the primary outcome of interest). This 
will be achieved by combining data from the PRESCIENT and ProNET networks (i.e., the 
AMP SCZ dataset as whole), given that the protocols and schedule of assessments have 
been harmonised across the two networks. The projected CHR sample size for PRESCIENT 
is 937 and for ProNET 1,040 (combined n of 1,977). There is no uniform method for 
determining an adequate sample size for developing a prediction model92. In this sample 
size calculation, the method recently described by Riley et al93 was used. Minimum sample 
size calculations required for various scenarios are provided in table 1. below. Specifically, 
the sample sizes were derived for the scenarios of having low, medium or high prediction 
performance and also for the number of parameters in the model being 10, 20, 30, 40 or 50. 
Conversion to psychosis is a time-to-event outcome and therefore a survival model such 
as Cox regression is appropriate. The table below shows the sample sizes for the survival 
outcome, assuming a conversion rate of 15% over 2 years (number of events=300).  
 
Table 1. Minimum sample sizes for survival outcome. 
  
Number of parameters in model 
10 
20 
30 
40 
50 
Predictive 
performance 
low 
422 
843 
1265 
1686 
2108 
medium 
398 
796 
1193 
1591 
1989 
high 
366 
732 
1098 
1464 
1830 
It is undesirable to have the number of parameters above 30 as this would result in a 
prediction model that is overly cumbersome in real-world settings. As indicated in the 
table, the minimum sample size for a model with 30 parameters is estimated to be between 
1100 and 1300. However, as in all medical research, larger sample sizes lead to more robust 
models and it would therefore be desirable to achieve a sample size larger than this 
minimum recommendation. Therefore, we aim to assemble as large a sample as possible 
given the constraints of the length of the recruitment period and the number of recruitment 
sites. The sample size calculations presented in the table indicate that the overall AMP SCZ 
sample size of 1,977 is adequate for developing a prediction model with ~30 parameters 
that has high predictive performance, while still allowing a subset of the data to be ‘held 
back’ for external validation purposes (see section 14). 
In addition, a simulation analysis was performed testing the performance of a linear kernel 
support-vector machine (SVM) to separate an event sample (converted cases) from a non-
event population (non-converted cases) using 5-fold cross-validation. Results indicated 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
34 of 79 | Pages  
 
that with the proposed sample, SVM produces a favourable BAC>70% for an event rate of 
>0.2 and 10% moderately predictive features in a data space of up to 5000 features. 
The size of the HC sample was determined primarily to control for site effects, particularly 
for neuroimaging data. Based on simulation analyses in the PRONIA study dataset64, 15 
HC per MRI scanner is recommended to control for site effects. 11 MRI scanners will be 
used across the recruitment network (Melbourne sites 1–7 will use the same scanner). 
Therefore, the 250 HCs to be recruited across the PRESCIENT network is sufficient. A 
subset of these HC participants (70 in total: 20 from Melbourne, 5 from each of the other 
sites) will receive 2 month follow up assessments in order to model stability of biomarkers. 
A larger HC sample will be recruited at the Melbourne hub (n=100) compared to other 
PRESCIENT sites (n=15 per site) because a larger sample of CHR participants will be 
recruited in Melbourne compared to other sites and, therefore, a larger HC sample is 
required at that site in order to accurately match HC to CHR on relevant variables (see 7.4). 
 
7.3.Recruitment 
Research Assistants (RAs) within their respective clinical service will recruit help-seeking 
clients who are being cared for and supported within clinical services. The RAs will 
identify young people who potentially meet eligibility criteria via reviewing medical 
records of new referrals, consulting with clinicians working in the recruiting clinics and/or 
sitting in on clinical review at the respective recruitment sites or other site-appropriate 
study recruitment activities. This method closely aligns with other studies recruiting this 
clinical population. Initial suitability will be established by the fact that the young person 
appears to meet CHR criteria, falls within the targeted age range, appears competent to 
consent to the study, and there is no obvious indication that he/she meets exclusion 
criteria. Healthy control participants will be recruited from the community using a variety 
of methods, including social media posts and word of mouth as well as from an existing 
list of HC participants in previous studies who have indicated they would like to 
participate in future research projects. 
 
7.4.Inclusion Criteria 
Only participants who meet all of the inclusion and none of the exclusion criteria will be 
eligible to participate in the study. 
  
Inclusion criteria for all participants (CHR and HC):  
A participant will be considered eligible for inclusion in this study only if all of the 
following criteria apply: 
(1) Aged 12-30 years inclusive  
(2) Understand and sign informed consent/assent   
(3) Meet either CHR or HC criteria (see below for more details) 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
35 of 79 | Pages  
 
 
 
Specific inclusion criteria for CHR participants:  
The participant must be help-accepting and meet diagnostic criteria for CHR 
(Vulnerability Group; Attenuated Psychotic Symptoms Group; Brief Limited Intermittent 
Psychotic Symptoms Group), as defined using the PSYCHS.  
 
Specific inclusion criteria for HC participants: 
HC will be matched with the sex, age, parental socioeconomic status and parental 
education level of CHR participants enrolled at each site. HC participants must not meet 
any of the exclusion criteria and must not:  
1. Meet CHR criteria or have a current or past Cluster A personality disorder 
2. Be receiving any current treatment with psychotropic medication 
3. Have a family history (in first-degree relatives) of psychotic spectrum disorders, 
operationalised using the FIGS. 
 
7.5.Exclusion Criteria 
1. Antipsychotic medication exposure equivalent to a total lifetime haloperidol dose of 
>50 mg (see Appendix A for haloperidol equivalents), estimated based on available 
information (e.g., medical file documentation, patient and family report). If potential 
participants are on antipsychotic medication at the time of study screening, they can be 
titrated off this medication prior to study enrolment.  
2. Documented history of intellectual disability. 
3. Past or current clinically relevant central nervous system disorder. When necessary, 
Research Assistants will consult with study team investigators (including medical 
personnel) to determine if the central nervous system disorder is deemed to be 
clinically relevant.  
4. Traumatic brain injury that is rated as 7 or above on the Traumatic Brain Injury (TBI) 
screening instrument. 
5. Current or past treated or untreated psychotic episode, as determined using the 
PSYCHS. 
 
7.6.Discontinuation and Withdrawal 
 
7.6.1. Participant Discontinuation Criteria 
A participant will be discontinued when the PI, Sponsor or HREC have decided that the 
participant will not complete the study. The status ‘discontinued’ is required to be 
documented. Discontinuation could include:  
(1) Participation interferes with the appropriate clinical management of risk to self or 
others. 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
36 of 79 | Pages  
 
(2) An adverse event or serious adverse event leads to a request for discontinuation by an 
investigator or research member. These cases may be offered treatment as inpatients or 
via intensive community care, as per early psychosis guidelines. Data collected after 
meeting the discontinuation criterion will not be included in the primary analysis. 
 
7.7.Study Discontinuation Criteria (Stopping Rules) 
The study may be terminated at any time by the Sponsor. 
 
7.8.Replacement of Participants 
Participants who are withdrawn or discontinued from the study will not be replaced. 
 
7.9. Incorrectly enrolled Participants 
Incorrectly enrolled participants will be discussed by the Investigator and Orygen on a 
case-by-case basis, and a written decision will be made as to whether they should remain 
on study or be withdrawn. 
 
7.10. Withdrawal 
All participants have the right to revoke consent from the study at any time and this will 
be clearly stated (verbally and in writing) at the time of consent. Withdrawal from the 
study can be at the request of the participant.  Withdrawn participants will be informed 
that they will no longer continue with the study protocol and that their withdrawal from 
the study will not influence their treatment at clinical services. Participants who withdraw 
from the study will always be asked about the reason(s) for their withdrawal and about 
the presence of AEs. Adverse events that are possibly related to study procedures should 
be followed up until resolution, the adverse event stabilises or the participant is lost to 
follow up. The participant is not required to provide a reason of withdrawal. For a 
participant who withdraws their consent, their data collected up to the point of withdrawal 
will still be used for the purposes of the research unless explicitly stated by the participant 
that they wish their data removed from any applicable databases.   
Withdrawal can include passive withdrawal of consent (participant not lost to follow up, 
but not attending scheduled appointments). 
Every effort will be made to contact the participant, including use of all available contact 
details, and consulting with the relevant clinical teams. If the participant cannot be 
recontacted directly, it is intended that CMI (or the relevant local system) will be used to 
determine if the person has had contact with other mental health services.  The study team 
will also ask the participant to nominate at least one friend or relative who can be contacted 
in the event that the participant cannot be contacted.  
 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
37 of 79 | Pages  
 
 
8. Visits and Assessments 
The Schedule of Assessments is shown in Section 8.1. An explanation of each measure can 
be found in the sections that follow. The aims of the research study will be best achieved 
if participants take part in all assessment components, as we are interested in building 
multimodal prediction models. Hence, participants must agree to participate in all 
assessments for which they are eligible. However, if a participant is ineligible to participate 
in a biomarker assessment (e.g., if they have braces and hence cannot undergo the MRI 
scan), they will still be able to participate in the study. The digital momentary assessments 
are an optional component of the study - participants can opt out of this component 
without compromising their participation in the overall study. The study visits may be 
split into multiple visits if this is preferred by the participant or the participant and their 
parent/legal guardian.  

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0 15th November 2021 
CONFIDENTIAL 
38 of 79 | Pages  
 
8.1.Table 2 Schedule of Assessments  
 
✓ = CHR participants 
C = HC participants (70 HCs – 20 from Melbourne, 5 from each of the other sites/hubs, will receive the repeat assessments at month 2 follow up) 
 
 
 
V1 
V2 
V3 
V4 
V5 
V6 
V7 
V8 
V9 
V10 
V11 
V12 
V13 
V14 
V15 
V16 
Conversion 
Informed consent  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Domain 
Instrument/ 
Specimen 
Screening 
 
M0 
M1 
M2 
M3 
M4 
M5 
M6 
M7 
M8 
M9 
M10 
M11 
M12 
M18 
M24 
 
CLINICAL  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Inclusion/Exclusion 
criteria 
PSYCHS/SOFAS/SCID5-
PD-Schizotypal /FIGS 
(abbreviated version)/ 
TBI/medication use 
(PharmaTreat) 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
C* 
 
C* 
 
Medical & psychiatric 
history 
Health and Medical 
Conditions Questionnaires 
✓C 
✓ 
✓ 
✓C 
✓ 
✓ 
✓ 
✓ 
✓ 
✓ 
✓ 
✓ 
✓ 
✓C 
✓ 
✓C 
 
Demographics 
Demographics 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Premorbid functioning  
PAS 
 
 
✓ 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Adverse events 
Adverse Events 
 
✓C 
✓C 
✓C 
✓C 
✓C 
✓C 
✓C 
 
✓C 
✓C 
✓C 
✓C 
✓C 
✓C 
✓C 
✓C 
 
Attenuated psychotic 
symptoms, associated 
distress, and conversion 
to psychosis  
PSYCHS  
 
✓C 
✓ 
✓C 
✓ 
 
 
✓ 
 
 
 
 
 
✓ C* 
✓ 
✓ C* 
✓C 
General 
psychopathology 
BPRS94 
 
 
✓C 
✓ 
✓C 
✓ 
✓ 
✓ 
✓ 
✓ 
✓ 
✓ 
✓ 
✓ 
✓ 
✓ 
✓ 
 
Depression 
CDSS 
 
✓C 
✓ 
✓C 
✓ 
 
 
✓ 
 
 
 
 
 
✓ 
✓ 
✓ 
 
Anxiety 
OASIS95 
 
✓C 
✓ 
✓C 
✓ 
 
 
✓ 
 
 
 
 
 
✓ 
✓ 
✓ 
 
Suicidality 
CSSRS 
 
✓C 
 
✓C 
 
 
 
✓ 
 
 
 
 
 
✓ 
✓ 
✓ 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0 15th November 2021 
CONFIDENTIAL 
39 of 79 | Pages  
 
 
 
V1 
V2 
V3 
V4 
V5 
V6 
V7 
V8 
V9 
V10 
V11 
V12 
V13 
V14 
V15 
V16 
Conversion 
Sleep disturbance 
PROMIS-SD 
 
✓C 
 
✓C 
 
 
 
✓ 
 
 
 
 
 
✓ 
✓ 
✓ 
 
Substance use 
ASSIST96 
 
✓C 
 
✓✓ 
 
 
 
✓ 
 
 
 
 
 
✓ 
✓ 
✓ 
 
DSM diagnoses 
SCID-5-RVs97 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
✓C* 
✓ 
✓C* 
✓C 
Patient global impression 
of severity 
PGI-S 
 
✓C 
✓ 
✓C 
✓ 
 
 
✓ 
 
 
 
 
 
✓ 
✓ 
✓ 
 
Psychosocial functioning 
SOFAS98, GF Social, GF 
Role 
 
 
✓C 
✓ 
✓C 
✓ 
 
 
✓ 
 
 
 
 
 
✓ C* 
✓ 
✓ C* 
✓C 
Perceived Stress Scale 
PSS 
 
✓C 
✓ 
✓C 
✓ 
 
 
✓ 
 
 
 
 
 
✓ 
✓ 
✓ 
 
Perceived Discrimination 
Questionnaire 
PDQ 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Pubertal development 
Scale 
PDS 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Psychosis Polyrisk Score  
PPS99 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
DIGITAL 
MOMENTARY 
ASSESSMENTS 
 
 
Daily changes in mental 
state and context 
EMA 
 
✓C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
 
 
 
Physical activity, sleep-
wake cycles, travel 
patterns 
Passive sensing (actigraphy, 
geolocation) 
 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
 
 
 
NEUROCOGNITION 
 
 
Premorbid IQ 
WRAT 5 Reading Accuracy 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
V1 
V2 
V3 
V4 
V5 
V6 
V7 
V8 
V9 
V10 
V11 
V12 
V13 
V14 
V15 
V16 
Conversion 
Current IQ 
WASI-II - 2-subtest version 
(Vocab & MR)100 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 
✓ 
 
Processing speed 
Digit-Symbol Substitution 
Test 
 
✓C 
 
✓C 
 
 
 
✓ 
 
 
 
 
 
✓ 
 
✓ 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0 15th November 2021 
CONFIDENTIAL 
40 of 79 | Pages  
 
 
 
V1 
V2 
V3 
V4 
V5 
V6 
V7 
V8 
V9 
V10 
V11 
V12 
V13 
V14 
V15 
V16 
Conversion 
Attention 
Continuous Performance 
Test 
 
✓C 
 
✓C 
 
 
 
✓ 
 
 
 
 
 
✓ 
 
✓ 
 
Working memory 
Letter N-Back 
 
✓C 
 
✓C 
 
 
 
✓ 
 
 
 
 
 
✓ 
 
✓ 
 
Relational Memory 
Digit-Symbol Substitution 
Test 
 
✓C 
 
✓C 
 
 
 
✓ 
 
 
 
 
 
✓ 
 
✓ 
 
Spatial memory 
Visual Object Learning Test 
 
✓C 
 
✓C 
 
 
 
✓ 
 
 
 
 
 
✓ 
 
✓ 
 
Verbal learning 
List Learning Test 
 
✓C 
 
✓C 
 
 
 
✓ 
 
 
 
 
 
✓ 
 
✓ 
 
Emotion recognition 
Emotion Recognition Test 
 
✓C 
 
✓C 
 
 
 
✓ 
 
 
 
 
 
✓ 
 
✓ 
 
Motor 
Finger Tapping Test 
 
✓C 
 
✓C 
 
 
 
✓ 
 
 
 
 
 
✓ 
 
✓ 
 
Sensorimotor speed 
Motor Praxis* 
 
✓C 
 
✓C 
 
 
 
✓ 
 
 
 
 
 
✓ 
 
✓ 
 
NEUROPHYSIOLOGY 
(EEG) 
 
 
Mismatch 
negativity/visual oddball 
Mismatch negativity and 
visual oddball 
 
✓C 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 
Auditory oddball 
Auditory target/novelty 
P300 
Auditory target/novel 
alpha desynchronisation 
 
✓C 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 
40 HZ auditory steady 
state response 
40Hz inter-trial phase 
coherence, baseline inter-
stimulus interval gamma 
power 
 
✓C 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 
Resting state (eyes 
open/closed) 
Power spectra 
1/f slope 
 
✓C 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 
BIOSPECIMENS 
 
 
Vital signs 
Elevated body mass index, 
blood pressure, 
temperature 
 
✓C 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0 15th November 2021 
CONFIDENTIAL 
41 of 79 | Pages  
 
 
 
V1 
V2 
V3 
V4 
V5 
V6 
V7 
V8 
V9 
V10 
V11 
V12 
V13 
V14 
V15 
V16 
Conversion 
Current health status and 
activity 
Current illnesses and recent 
activity 
 
✓C 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 
Elevations in white blood 
cells 
Blood sample – CBC with 
differential 
 
✓C 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 
Immune system, 
coagulation system, 
complement system, and 
oxidative stress 
Blood sample – plasma, 
serum (multiplex, 
ELISA/mass spectrometry) 
 
✓C 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 
DNA isolated for 
microarray/low-pass 
sequencing 
Blood sample – buffy coat 
 
✓C 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 
Functional assays for 
redox dysregulation and 
cell membranes for lipids 
(e.g. DHA/EPA/AA) 
Whole blood sample 
(functional assays, mass 
spectrometry, gas 
chromatography) 
 
✓C 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 
Cortisol 
Saliva Collection (ELISA) 
 
✓C 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 
SPEECH and FACIAL 
EXPRESSION 
 
 
Language content and 
structure 
Speech acoustics 
Free speech recording 
(Zoom audio) 
 
✓C 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
PSYCHS interview 
recording  
 
✓C 
✓C 
✓C 
✓C 
 
 
✓C 
 
 
 
 
 
✓C 
✓C 
✓C 
✓C 
 
Audio diaries recorded via 
smartphone as component 
of EMA (2 mins daily) 
 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
✓ C 
 
 
 
Facial expression  
Free speech recording 
(Zoom video) 
 
✓C 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 
NEUROIMAGING 
(MRI) 
 
 
Structural/functional 
(incl resting state) 
T1, T2, diffusion MRI, 
resting state functional MRI 
(BOLD) 
 
✓C 
 
✓C 
 
 
 
 
 
 
 
 
 
 
 
 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0 15th November 2021 
CONFIDENTIAL 
42 of 79 | Pages  
 
 
 
V1 
V2 
V3 
V4 
V5 
V6 
V7 
V8 
V9 
V10 
V11 
V12 
V13 
V14 
V15 
V16 
Conversion 
TREATMENT AND 
HEALTH SERVICE 
UTILISATION 
Psychosocial/ 
pharmacological 
treatment/service use 
 
✓C 
✓ 
✓C 
✓ 
 
 
✓ 
 
 
 
 
 
✓C 
✓ 
✓C 
 
Notes: 
1. The Baseline visit needs to be conducted within 3 weeks of the screening visit. If not, the screening visit will need to be repeated. The study team will endeavour to schedule all other visits up 
to month 12 within +/- 1 week of their due date. For example, a Month 6 visit can occur up to 1 week prior to or after its due date. Month 18 and 24 will have a visit window of +/- 2 weeks. 
Assessments conducted outside these windows will be discussed with the local study team and the decision whether or not to utilize the data in analyses will be documented accordingly.  
2. Converted cases will be followed up as per the schedule of assessments. This will also be the case for participants who commence antipsychotic medication after study enrolment.  
3. Neurocognition tasks: Reading task in English speaking sites will be the WRAT5 Reading subtest; in non-English speaking countries the local version of the NART will be used. Apart from 
Premorbid and Current IQ, all other cognitive domains will be measured using the Web version of the Penn Computerised Neurocognitive Battery (PennCNB). 
4. The TBI will only be completed for participants where clinically indicated (i.e., participants who have had a traumatic brain injury, as reported by the participant or family or as determined 
from the participant’s medical history). 
5. If conversion to psychosis is suspected based on the monthly BPRS assessment, then the PSYCHS and SCID will be conducted to check conversion status.  
6. Study participants will be contacted in between the formal assessments for the purposes of engagement and safety follow-up (see 8.12). 
* HC’s will be contacted by Research Assistants at Months 12 and 24 and asked about their mood, behaviour, emotions, and other experiences since their last assessment (to determine possible 
onset of CHR status or psychiatric diagnosis). They will also be asked about any contact they may have had with mental health services since last visit. These check-ins will be completed using 
the PSYCHS, SOFAS, SPD, and the SCID 5 screening questions. If the SCID 5 screening questions indicate presence of a DSM 5 diagnosis, the relevant section of the SCID 5 will be 
completed. A full conversion to psychosis assessment will be administered if the PSYCHS indicates onset of psychotic disorder. These assessments will be conducted remotely (via phone or video 
call) and will take around 20-30 minutes. The Research Assistant can also provide a face-to-face visit if this is the preferred option.  
 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
43 of 79 | Pages  
 
8.2.Demographics, Medical and Psychiatric History 
Demographic information (age, sex, gender, race, ethnicity, socioeconomic status, 
employment, educational attainment and age and education of biological parents) and 
medical and psychiatric history will be collected. Prior treatment (pharmacological 
and psychosocial treatment and health service utilisation) will also be captured, based 
on information collected from the participant and, as required, medical files, family 
and/or pharmacist.  
 
8.3.Clinical Assessments 
Informed by the recent advances in the field (see section 5.2), the study aims to collect 
multimodal data (clinical, biological, genetic, neurocognitive, neurophysiological, 
neuroimaging), baseline and repeat assessments over time (‘macro’ level monthly 
assessments) and ‘micro-level’ momentary (day-to-day) data collected through digital 
platforms (EMA and passive sensing). The ‘macro’ level repeat assessments are critical 
for both dynamic prediction of outcomes and also accurate characterization of clinical 
trajectories over time.  
The battery of assessments are listed in 8.1 and described below. The selection of 
measures is informed by the Neurobiology in Youth Mental Health Partnership101, a 
national effort led by Orygen to standardize research assessments in order to create 
large datasets, guided by principles of feasibility, participant and clinical service 
burden, transdiagnostic relevance and translatability into clinical practice.  
 
The following measures will be administered by RAs as part of an integrated clinical 
interview: 
 
The Positive Symptoms and Diagnostic Criteria for the CAARMS Harmonized with 
the SIPS (PSYCHS) is a semi-structured interview which assesses symptoms 
associated with the prodromal phase of psychosis, and which is used to define the 
CHR criteria and onset of first-episode psychosis (FEP). The attenuated psychotic 
symptoms (positive symptoms) section of the PSYCHS will be assessed at all major 
assessment timepoints. This will be a rating of the worst period of each symptom 
either (1) over the last year (at Screener) or (2) since the participant’s last research 
assessment.  
The Structured Clinical Interview for DSM-5 (SCID-5) is a semi structured interview 
guide for determining DSM-5 diagnoses. The SCID-5-Research Version (RV)97 will be 
used to assess DSM diagnostic criteria for Mood and Substance Use disorders and the 
SCID-5 Personality Disorders (PD)102 will be used to assess Schizotypal Personality 
disorder. If the participant converts to psychotic disorder, as determined using the 
PSYCHS, then the Psychotic Disorder section of the SCID-5-RV will be administered 
to determine type of DSM psychotic disorder. The language and diagnostic coverage 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
44 of 79 | Pages  
 
make the SCID-5 most appropriate for use with adults (age 18 and over); with slight 
modification to the wording of questions it may be used with adolescents. 
Family Interview for Genetic Studies (FIGS)103: The FIGS, developed by NIMH, is 
an instrument that gathers diagnostic information on families in genetic and family 
studies on mental disorders, such as schizophrenia and bipolar disorders. It offers 
diagnostic information on each family member of the study participant. The FIGS has 
been found to be valid and reliable and has been used extensively in previous 
research. An abbreviated version will be used in the current study, limiting 
assessment of family history of mental disorder to psychotic, mood and substance use 
disorders.  
The Social and Occupational Functioning Assessment Scale (SOFAS)98 is a numeric 
scale (1 through 100) used to rate social and occupational functioning. The SOFAS 
focuses exclusively on the individual's level of social and occupational functioning, 
not symptom severity. 
The Global Functioning: Social and Role scales (GF:S and GF:R)104 will also be used 
to rate social and role functioning.  
Premorbid Adjustment Scale (PAS): The PAS will be used to assess premorbid 
functioning across developmental periods and across a number of domains. Each 
domain is rated on a 0 to 6 point scale, with 0 indicating normal adjustment and 6 
indicating severe impairment. The “premorbid” period for PAS purposes is the period 
ending six months prior to the participant first meeting CHR criteria.  
The Brief Psychiatric Rating Scale (BPRS)94  is a rating scale in which 24 items relating 
to different types of psychopathology are rated on a continuum of not present to 
extremely severe. This measure will provide an overall measure of general 
psychopathology. 
The Negative Symptom Inventory-Psychosis Risk (NSI-PR)105. The NSI-PR was 
designed specifically for measuring negative psychotic symptoms in the CHR 
population, taking into account aspects of behaviour and socialization that are 
common to this age range.  
The Overall Anxiety Severity and Impairment Scale (OASIS)95 is a valid and reliable 
measure of anxiety severity and related impairment. It is a brief (five-item) continuous 
measure, which can be used across anxiety disorders, with multiple anxiety disorders, 
and with subthreshold anxiety symptoms. The total OASIS score is calculated by 
adding together the scores for the five questions. A score of 8 or above suggests 
clinically significant anxiety. 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
45 of 79 | Pages  
 
The Patient Reported Outcomes Measurement Information System-Sleep 
Disturbance (PROMIS-SD)106 is a brief (8 item) measure of self-reported perceptions 
of sleep quality, depth, and restoration within the past seven days. This includes 
perceived difficulties falling asleep and staying asleep, as well as sleep satisfaction.  
 
The Calgary Depression Scale for Schizophrenia (CDSS) is a nine item structured 
interview scale designed specifically to assess depression independently of symptoms 
of psychosis in schizophrenia107. It has been validated in CHR samples108. 
 
The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST)96, will 
be used to measure substance use. This measure is widely used and endorsed for the 
assessment of drug and alcohol use by the World Health Organisation.  
 
The Columbia Suicide Severity Rating Scale (CSSRS)109 assesses suicide risk 
through a series of simple, plain-language questions. The answers identify whether 
someone is at risk for suicide, assess the severity and immediacy of that risk, and 
gauge the level of support that the person needs. The evidence-supported C-SSRS is 
recommended by the Food and Drug Administration and often referred to as the gold 
standard for suicide risk assessment. The C-SSRS has been validated in adolescent and 
adults. 
 
8.4.Self-Report Measures  
The following measures will be rated by participants themselves on a tablet:  
 
The Patient Global Impression of Severity (PGI-S) is a single item self-report 
measure assessing a patient’s impression of severity of their symptoms over the last 7 
days.   
 
Perceived Stress Scale (PSS)111: The PSS is the most widely used psychological 
instrument for measuring the perception of stress. It is a measure of the degree to 
which situations in one’s life are appraised as stressful. Items were designed to tap 
how unpredictable, uncontrollable, and overloaded respondents find their lives. 
 
Perceived Discrimination Scale (PDS): Perceived discrimination will be assessed 
using an adapted self-report measure from Jannsen et al (2003)112. Participants answer 
‘yes’ or ‘no’ to whether they had experienced discrimination in their lifetime because 
of their skin colour; ethnicity; gender; age; appearance; disability; sexual orientation; 
religion; or other reason. Total perceived discrimination is calculated as the total 
number of “types of discrimination” that are endorsed. 
 
Pubertal Development Scale (PDS)113: This is a self-assessment instrument composed 
of five questions pertaining to growth spurt, body hair, and changes in skin for both 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
46 of 79 | Pages  
 
sexes, rated on 5-point scales: “not yet started” (scored as one point), “barely started” 
(two points)”, “definitely started” (three points)”, “seems complete” (four points), “I 
don’t know” (treated as missing values). On a similar scale, males also rate their 
development regarding changes in voice and facial hair growth, while females rate 
breast growth. Females also state whether they have begun to menstruate.  
 
Psychosis Polyrisk Score (PPS)99: This scale was developed based on meta-analyses 
of environmental risk factors for psychosis. It generates a single score indexing 
exposure to a range of environmental risk factors associated with psychosis. This 
single score can be included as a variable in the development of prediction models.  
 
8.5.Digital Momentary Assessments 
The digital momentary assessments are an optional component of the study. A 
decision not to take part in this component will not preclude involvement in the 
overall study. 
There are three components:  
1)  Ecological Momentary Assessment (EMA)114 via an existing smartphone app 
(‘mindLAMP’, available for Android and iOS). EMA will repeatedly measure 
symptoms and behaviour in vivo. The app will prompt participants to complete a short 
1-2 minute survey once/day for 12 months assessing daily stress levels, affective 
states, anomalous experiences and behaviour. Using the same app, short 2 minute 
audio recordings (an audio diary) will be made on a daily basis. These consist of the 
participant being prompted to record speech about their recent experiences, events 
and context. 
2)  Passive Sensing: The ‘mindLAMP’ app is capable of automatically (‘passively') 
logging context information by via mobile phone sensors. The geolocation (GPS) and 
accelerometer sensors will be used. The GPS sensor provides a location estimate for 
the participant’s current location. The accelerometer sensor measures acceleration.   
3)  Actigraphy: Participants will wear Axivity AX3 (Newcastle upon Tyne, UK) 
watches (accelerometers assessing 24h gross motor activity) during the first year to 
measure rest-activity patterns and physical/sedentary behaviours.  
Passive sensing and actigraphy data will be analysed using computer programs and 
algorithms. Variables extracted for analysis will include: roaming/movement 
patterns (e.g., distance travelled, maximum distance between two locations), location 
(e.g., ‘home time’, time spent outdoors), and regularity of movement (e.g., location 
entropy, diurnal movement index).  
 
8.6.Neurocognitive Tasks 
The neurocognitive tasks will be administered via computer, apart from the IQ tests.  
  

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
47 of 79 | Pages  
 
The WRAT 5 Reading subtest is a short reading task used to estimate premorbid IQ. 
This task will only be administered at baseline. 
  
The Wechsler Abbreviated Scale of Intelligence (WASI-II162) is a general intelligence, 
or IQ, test designed to assess specific and overall cognitive capabilities and is 
individually administered to children, adolescents and adults. Only the Full Scale IQ 
(FSIQ)-2 section will be completed. We will use the two subtest version to generate a 
Full Scale IQ. The WASI-II will be administered at baseline and 2 year (104 weeks) 
follow-up. As the WASI-II is not available in non-English speaking countries, non-
English speaking sites will administer the Vocabulary and Matrix Reasoning subtests 
of the Wechsler Adult Intelligence Scale–V (WAIS-V) for participants aged 16 and 
above and the Wechsler Intelligence Scale for Children–V (WISC-V) for participants 
under the age of 16. 
  
A number of tasks from the web-based Penn Computerised Neurocognitive Battery 
(PennCNB) will be administered at baseline, 8 weeks, 26-weeks, 52-weeks and 104 
weeks. They will include measures of attention (Continuous Performance Test), 
working memory (Letter N-Back), processing speed (Digit-Symbol Substitution Test), 
relational memory (Digit Symbol Recall), verbal learning (List Learning Test), spatial 
memory (Visual Object Learning Test), emotion recognition (Emotion Recognition 
Test), motor function (Finger Tapping Test) and sensorimotor speed (Motor Praxis).  
  
The battery has an estimated administration time of 50 minutes at baseline, 28 minutes 
at weeks 8, 26 and 52, and 43 minutes at week 104. 
 
8.7.Neurophysiological Assessments (EEG Recordings) 
EEG will be acquired during 4 paradigms:   
1. 
Mismatch Negativity (MMN)/Visual Oddball Paradigm. The participant 
performs a visual oddball target detection task while ignoring the auditory tone 
stimuli presented.   
a. MMN Paradigm:  Measures include 
i. Mismatch Negativity (MMN) amplitude - Pitch+Duration “Double 
Deviant tones”. 
ii. Repetition Positivity (RP) amplitude - difference between late and 
early appearing standards within a local series of standards in MMN 
paradigm. 
b. Visual Oddball Paradigm: Measures include 
i. Visual Target P300 (P3b) amplitude  
ii. Visual Novelty P300 (P3a) amplitude  
2. Auditory Oddball Paradigm: Measures include 
a. Auditory Target P300 (P3b) amplitude  
b. Auditory Novelty P300 (P3a) amplitude  

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
48 of 79 | Pages  
 
c. Auditory Target and Novel Alpha Desynchronization  
3. 40 Hz Auditory Steady State Response: Measures include 
a. 40 Hz Inter-trial Phase Coherence (ITC) 
b. Baseline inter-stimulus interval Gamma Power  
4. Resting state EEG (eyes open/eyes closed): Measures include 
a. Power spectra: delta, theta, alpha, beta, gamma 
b. 1/f slope: Thought to reflect excitation/inhibition balance. 
Frequency: EEG data will be acquired at baseline and at 2 month follow up. The 
protocol for baseline and follow up is identical. The purpose of the follow up 
assessment is to assess change trajectories predictive of CHR outcomes. Each EEG 
session will require between 90 minutes and 2 hours from set-up to clean-up. 
Instruments: Identical 64-channel ActiChamp High Impedance EEG systems and an 
air-gapped acquisition computer and stimulus presentation device will be leased from 
a private vendor (NeuroSig) and installed at all sites. 
 
8.8.Biospecimens 
Biomarkers that can be quantified from peripheral tissue (such as plasma, blood cells 
or hair) are promising indicators of the pathophysiological processes that underlie 
mental disorders115. As such, peripheral biomarkers may serve multiple purposes, 
including indicating risk for onset or progression to a more advanced stage, 
delineating diagnostic entities or informing treatment choice. For this study, we 
selected biomarkers with an established association with risk and clinical outcomes, 
relevance to the pathophysiology of mental disorders (psychosis in particular), 
minimising participant burden, and limiting the invasiveness of specimen collection.  
 
A blood sample (approximately 40ml or 2.5 tablespoons) will be collected to measure: 
elevations in white blood cells, as current illness may confound numerous biomarkers; 
biomarkers of immune system, coagulation system, complement system, and 
oxidative damage (from plasma, serum); DNA for polygenic risk score; and functional 
assays for redox dysregulation and cell membranes for lipids, e.g., DHA, DPA, AA 
(from whole blood).  
 
The blood samples will be collected by a qualified phlebotomist at two separate study 
time points (baseline and month 2). One of the blood tubes (3ml EDTA) will be 
transferred to a local pathology service for immediate testing. These initial research 
analytical samples will be destroyed upon analysis according to the standard 
operating procedures of the respective pathology service. The remaining blood 
samples will be processed and stored in an -80 Celsius freezer at the Florey Institute 
of Neuroscience and Mental Health in Melbourne, Australia. PRESCIENT sites 
outside of Melbourne will store blood samples locally until transporting their bloods 
to the Florey Institute. 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
49 of 79 | Pages  
 
The samples will be shipped from the Florey Institute to a to-be-determined 
laboratory/ies for analysis. The blood samples and any paperwork accompanying 
them will be identified by a unique, study-specific code and hence no participant 
identifying information will be associated with the sample. The code will only be 
accessible by researchers and relevant study staff involved in the study and the code 
to link this will be stored securely.  
 
Following the completion of analyses for the study, the remaining blood samples will 
be shipped to the NIMH Repository and Genomics Resource (NRGR). Samples will 
be stored in the repository indefinitely and made available to other researchers upon 
application for future research purposes.   
 
At baseline and month 2, saliva samples will be collected to measure cortisol levels, 
indicative of stress response. At both baseline and month 2, two vials will be collected 
at time 1, two vials at time 2 (1 hour later), and two vials at time 3 (two hours from 
time 1). All saliva samples will be shipped to NRGR. NRGR will then ship 1 vial per 
time point (i.e., 3 baseline vials and 3 month 2 vials) for each participant to a to be 
determined commercial lab such as Salimetrics in the US for analysis and store the 
remaining samples for future research. 
 
Additionally, data from the FIGS (family history of psychiatric disorder) may be used 
to inform genetic analyses; recorded history of health conditions may inform 
biomarker analysis; vital signs, current illness and recent physical activity will be 
captured as they may confound biomarker measurement. 
 
The type of genetic analysis being conducted in this study is not expected to result in 
information about individual participants’ future health, future treatment or risk of 
having children with a genetic disorder, or information that may be relevant to the 
health of family members who are not part of the project. 
 
8.9.Speech and facial expression samples 
For the central assessment, audio and video will be recorded using a web-based 
meeting platform (Zoom). This will consist of an open-ended conversation 
(approximately 20 minutes in length) to elicit free natural speech, following methods 
applied previously by our group. RAs use qualitative interviewing methods to elicit 
description of subjective experience. RAs will be trained to minimize interruption, and 
use clarifying questions to promote speech production. Open-ended questions were 
chosen for their ability to encourage introspection and longer speech samples, 
enabling the analysis of speech coherence and spontaneous content. Moreover, open-
ended questions may help to reduce attrition by encouraging rapport building 
between the administrator and the participant. Two additional speech assessments 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
50 of 79 | Pages  
 
will be performed: audio recordings of the PSYCHS semi-structured interviews and 
daily audio diaries collected during ecological momentary assessment (EMA).  
 
The audio recordings will be used to collect speech content/structure (semantics and 
syntax) and speech acoustics. For the open-ended interviews, video recordings will be 
used to collect facial expressions. Audio files from the open-ended and PSYCHS 
interviews will be sent to a transcription service (TranscribeMe) to obtain pseudo-
anonymised transcripts that have been diarized and timestamped for further analysis. 
The software package OpenSmile will be used to extract information about speech 
acoustics from the open-ended interviews, the PSYCHS interviews, and the audio 
diary. The software package OpenFace will be used to extract information about facial 
expressions from the open-ended interview. Transcription of the audio diaries from 
EMA (see 8.5) will be processed by automated transcription.  
 
8.10. Neuroimaging 
The MRI protocol will collect 4 measurements:  
1. T1 (7 min) – A Magnetization Prepared Rapid Acquisition Gradient Echo 
(MPRAGE) with high spatial resolution (1mm or better) that provides an excellent 
contrast between gray and white matter. This measure is required for anatomical 
segmentation of the brain.  
2. T2 (6 min) – A fast spin echo acquisition with flip angle evolution (SPACE) acquired 
at the same spatial resolution as the T1. This measures is required to provide 
complementary anatomical information to the T1. 
3. Diffusion MRI (11 min) – A multi-shell multi-band spin echo acquisition sensitive 
to water molecule displacement. This provides microstructural information (most 
robustly in white matter) as well as macroscopic structural brain connectivity 
measures. Multi-shell enables sensitivity to different displacement scales, enabling 
more complex biological models. Multi-band allows simultaneous acquisition of slices 
at different brain locations, shortening the length of the acquisition. 
4. Resting-state functional MRI (21 min) – A multi-band gradient echo acquisition 
sensitive to blood oxygen levels (BOLD) most robustly in gray matter. This measure 
provides an estimate of functional connectivity within and between particular brain 
networks. 
The protocol for baseline and follow up is identical. The follow up scan will be useful 
for incorporating into prediction models based on changes over time.  
Instruments: All 3T magnets. Due to the variety of MRI systems across the different 
sites two tiers will be used:  
1. High end tier (tier 1) – will use Siemens Prisma machines that are currently 
available or to be installed at most sites across PRESCIENT and ProNET. All 
Prisma sites will use identical protocols.  
2. Lower end tier (tier 2) – for all other scanners across PRESCIENT and ProNET. 
These scanners include Siemens Skyra (3 sites), GE MR750 (4 sites), Siemens Vida 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
51 of 79 | Pages  
 
(2 sites), and Philips Achieva DDAS (1 site). The main differences between tier 1 
and tier 2 will be in the diffusion scan, where tier 2 will not have the highest shell 
of diffusion weighting and may use lower spatial resolution. Due to the high 
instrument variability, the tier 2 protocol will not be identical across sites, although 
it will minimize differences as much as possible.  
PRESCIENT will recruit up to 5 healthy volunteers per site to test the collection and 
data transfer procedures for the MRI. These pilot/technical scans will be conducted 
for each machine prior to the commencement of the participant research scans. A total 
of 250 demographically matched healthy controls; all sites also have considerable 
experience recruiting adolescent and young adult typically developing control 
subjects. 
 
8.11. Treatment received 
At each follow up assessment, treatment received since last assessment will be 
recorded. This will consist of both pharmacological and psychosocial treatment and 
service use. This information will be extracted from the participant interview and, as 
required, medical files, family and/or pharmacist. Participants who are started on an 
antipsychotic medication over the course of the study, regardless of whether they 
meet conversion to psychosis criteria, will be followed up as per the schedule of 
assessments.  
 
8.12. Engagement Phone Calls and Text Messages 
Study participants will be contacted in between the formal assessments for the 
purposes of engagement and safety follow-up. Potential safety data will be recorded, 
including any reported adverse events (AE) and serious adverse events (SAEs), and 
escalated in accordance with safety reporting procedures. These phone calls and texts 
will be used as a tool to increase engagement and potentially decrease participant 
attrition, as in other CHR studies being led by the research team. Participants can 
nominate which mode of contact they would prefer (e.g. phone call, text message etc.). 
As with all studies, participation is voluntary and all contact attempts will be ceased 
upon request.  
 
8.13. Data from other sources 
If CHR participants are unable to be re-interviewed for the follow up assessments, 
their diagnostic status at last clinical contact will be sourced from alternative sources, 
such as medical record files and state medical records (e.g., the CMI database for 
Victoria, Australia).   
 
 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
52 of 79 | Pages  
 
9. Safety Measures  
9.1. 
Safety Measures 
As this study is a non-interventional study, the primary interest of this study centres 
around the definition of the participant’s CHR symptomatology.  This will be tracked 
using the PSYCHS assessments which will include an assessment of symptom 
severity, but not assessment of causality or seriousness (or allocation to a specific 
diagnosis other than CHR status).  Similarly, relevant medical history will be deemed 
as that reported during the baseline assessment. Further relevant medical history and 
adverse events will not be reported unless adverse events reported by the participant 
and/or other study team members are deemed to possibly having been caused by 
study activities (e.g., distress during interview, or because of interaction with study 
team). 
 
The PI is responsible for ensuring that all study staff are aware of the following 
definitions and procedures:   
 
9.2.Definitions 
There will be no adverse events recorded in this study other than those outlined in the 
section above.  Only the reports of those adverse events which are reported by the 
participant and/or study team member(s) as possibly having been caused by the 
study activities (e.g. distress during interview, or because of interaction with study 
team) will include separate individual assessment of seriousness and causality (all 
others: managed using the study assessments). If any of these self- or team-reported 
adverse events – causally or possibly causally related – meet standard seriousness 
criteria, they will be recorded and tracked as serious adverse events as per the Safety 
Management Plan. 
 
9.2.1. Serious Adverse Event (SAE) 
Hospital admissions which are related to an exacerbation in CHR symptomatology 
will not be reported as adverse events unless deemed to be causally related to the 
research activity.   
 
9.3.AE and SAE Assessment 
9.3.1. Causality 
The causality of AEs (i.e., their relationship with study assessments) must be assessed 
by a suitably qualified Investigator at the study site.  Assessing causality requires 
considering whether there was a reasonable possibility that the event may have been 
caused by study participation. 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
53 of 79 | Pages  
 
While in most cases, it is very difficult to categorically rule out a causal relationship, 
where terms such as “related,” “possibly related” and “not related” are used they will 
be interpreted as follows: 
“related” -  the reviewer is confident of the causal relationship (e.g. temporal 
association, existing safety knowledge of the product, clinical judgement); 
“possibly related” – the reviewer is not confident of the causal relationship but 
tends to deem there is a positive causal relationship; 
“not related” – the reviewer has no reason to believe there is a causal 
relationship at the time of the assessment (or tends to deem there is not a positive 
causal relationship). 
Causality of an event may be re-evaluated by the reviewer at any time, e.g. 
when further evidence becomes available to confirm or refute an assessment of 
causality.  The reviewer may be any person on the study team who has been delegated 
this responsibility by the Investigator. 
 
9.4.Recording of Adverse Events and Serious Adverse Events 
Adverse events will be recorded and reported as per the per the Safety Management 
Plan (source documentation will include the study visit assessments, the Adverse 
Event Log and/or the Serious Adverse Event form).  
 
9.5.Expedited and Prompt Reporting of SAEs 
Any serious adverse event (causally related, as defined above) occurring during the 
course of the study must be reported to the Sponsor (Orygen) within 24 hours of the 
Investigator or designee becoming aware of the SAE. As much information as 
possible, as is available at the time of recording, is to be provided. The Investigator 
should always provide an assessment of causality at the time of the initial report. A 
follow-up report should be completed when outstanding information becomes 
available, when there is a significant change in the event or when the event resolves. 
The Investigator will maintain an SAE Log including all SAEs. SAEs will be reported 
to the governing Human Research Ethics Committee (HREC) and/or governance 
institutions in accordance with HREC and institutional requirements and Orygen’s 
Safety Management Plan.  
 
9.6.Handling in Cases of Unresolved AEs and SAEs at Completion or 
Withdrawal 
Where possible, all study related AEs and all SAEs must be followed up until 
resolution unless, in the Investigator’s opinion, the condition is unlikely to resolve. 
 
9.7.  Procedures in Case of Medical Emergency 
The Principal Investigator is responsible for ensuring that procedures and expertise 
are available to manage medical emergencies during the study at the premises 
participants attend for study assessments.  

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
54 of 79 | Pages  
 
 
9.8. 
Clinically Significant Results 
The type of testing being conducted in this study is not designed to result in 
information about an individual participant or their family member’s health. We will 
not provide participants with any individual results from analysis of the research 
samples. While we do not expect to identify clinically significant results in the 
samples, it is possible that findings of clinical significance to an individual’s or their 
family member’s health are incidentally identified.   
 
Normal ranges for blood samples collected as part of this study are determined based 
on international consensus and population based studies. An allocated medically 
trained investigator will review the results and determine if they are clinically 
significant.  
 
A radiologist will review all MRI scans and provide a report to an allocated medically 
trained investigator at each site, who will decide whether the scan may have clinical 
significance. 
 
With regard to genetic analysis, a standard set of guidelines developed by the 
University of Queensland in line with The Human Genetics Society of Australasia 
(HGSA) position statement will be followed when determining and reporting 
incidental 
findings 
from 
genetic 
analyses 
https://www.hgsa.org.au/documents/item/11030. 
 
Participants will be provided with the option of indicating if they would like to receive 
any incidental findings relating to their health or their family members’ health. The 
information generated from their biospecimen and the genetic analyses may in some 
instances have recognised interventions that can benefit or reduce risk of harm to the 
participant or family members.  
 
If an incidental finding is identified, the lab conducting the analysis or MRI scan will 
contact the research team so that the research team can link the participant’s sample 
code with their personal details, enabling the team to contact the participant and their 
clinical team.  The participant’s clinical team or a suitably qualified study team 
member (medically trained) will contact the participant, and their parent/guardian if 
applicable, to let them know that an incidental finding of clinical significance was 
found and to offer them the option of learning about these results. If the participant 
and/or parent/guardian would like to know the details of these findings, the study 
team member will discuss the findings with them and advise on any clinical follow 
up that may be required. The study team member will arrange referrals for further 
clinical follow up as appropriate.   
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
55 of 79 | Pages  
 
10. Study Oversight 
10.1. Data Safety and Monitoring Committee 
Due to the low-risk category of the study, as determined by the Sponsor, a formal Data 
Safety and Monitoring Committee will not be established. Safety and monitoring will 
be overseen by the Investigator team and Project Manager and managed in accordance 
with the Safety Management Plan as outlined in the Procedures Manual. Safety signals 
(AEs, SAEs, and suicidality data) will be regularly reviewed by study Project 
Manager/s and medically trained personnel.  If required, and in consultation with the 
Sponsor, safety data will be reviewed by an independent committee to protect the 
safety and interests of participants included in the study. 
 
 
 
 
11. Ethical Considerations 
11.1. Review by an Ethics Committee 
Prior to the commencement of the study, the protocol and any amendment(s), 
Participant Information and Consent Form, other information provided to 
participants (including advertising) and product information, will be submitted to the 
Institutional Human Research Ethics Committee (HREC). The approval letter should 
refer to the study by title, protocol number and version and dates of documentation 
reviewed and approved. A copy of the signed and dated letter of approval (on 
institutional letterhead) will be provided to the site and Orygen prior to study 
commencement. 
During the course of the study, the Principal Investigator (or delegate)/Sponsor (or 
delegate) is required to submit to the HREC/RGO the following:  amendments to the 
protocol and SAEs as per the committee’s requirements, site-specific updates as 
agreed to by the Investigator and respective HREC/RGO, progress reports according 
to local regulations and guidelines, Final Study Report if applicable and any 
additional information as required (e.g., SAEs reported by other investigative sites, 
amendments safety information and significant administrative changes to the 
protocol). 
Protocol amendments that may impact on participant safety or the validity of the 
study will be agreed upon by the PI and Sponsor and submitted to the reviewing 
HREC for approval prior to implementation. At conclusion of the study, the 
Investigator is required to inform the HREC in writing that the study has ended and 
no further activities regarding this protocol will be conducted at the site.   

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
56 of 79 | Pages  
 
The Investigator will ensure that the study is performed in accordance with ethical 
principles that have their origin in the Declaration of Helsinki and are consistent with 
International Conference on Harmonisation (ICH) Good Clinical Practice (GCP). The 
National Health and Medical Research Council (NHMRC) National Statement on 
Human Research will also be adhered to in Australia (as will the equivalent guidelines 
in other countries be adhered to be those nations’ investigator sites).  
 
11.2. Ethical Conduct of the Study 
This study will be carried out in accordance with the Principles of ICH-GCP (as 
adopted in Australian or the applicable local regulatory authorities) which build upon 
the ethical principles contained in the Declaration of Helsinki and the Australian 
NHMRC National Statement on Ethical Conduct in Human Research, and the 
NHMRC Australian Code for the Conduct of Research or relevant local equivalents. 
11.3. Consultations with the Youth Research Council 
At the sponsor level, regular meetings with the Orygen Youth Research Council will 
take place throughout the study as required. This will ensure ongoing engagement of 
youth in the study process. Feedback from the Youth Research Council will be 
recorded and considered for future amendments.  
 
11.4. Investigator Responsibilities 
The protocol and the informed consent form must be reviewed and approved by a 
properly constituted HREC before study start. A signed and dated letter that the 
protocol and informed consent have been approved by the HREC must be provided 
to Orygen before study initiation. Prior to study start, the investigator is required to 
sign the protocol signature page confirming his/her agreement to conduct the study 
in accordance with these documents and all of the instructions and procedures found 
in this protocol and to give access to all relevant data and records to Orygen monitors 
and auditors, HREC and regulatory authorities as required. If an inspection of the 
clinical site is requested by a regulator, the investigator must inform Orygen 
immediately that this request has been received.  
 
Prior to participation in the research study, each participant (or participant and 
parent/legal guardian for participants under 18 years of age) will undergo a complete 
consenting interview with the delegated study team members and provide consent on 
the relevant HREC approved form. The contents and process of obtaining informed 
consent will be in accordance with all applicable regulatory requirements including 
those required for the consenting of participants considered under legal adult age 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
57 of 79 | Pages  
 
according to local laws. Investigators in countries other than Australia will adapt 
consent processes accordingly to meet local requirements (including ages of majority). 
 
All eligible participants will have the study explained by the PI or the delegated 
Research Assistant or other study member. They will receive a full explanation, in lay 
terms of the aims of the study, the discomfort, risks and benefits in taking part as well 
as insurance and other procedures for compensation in case of injury. It will be 
explained that the study is for research purposes and may not provide benefit to the 
individual.  It will be pointed out that they can withdraw from the study at any time 
without prejudice. Each participant will acknowledge receipt of this information by 
giving informed consent for participation in the study. Informed consent may also be 
provided electronically. The participant will be given a copy of the signed or 
electronically acknowledged Participant Informed Consent Form (PICF) to retain. All 
study documents will be fully approved by the HREC prior to being used for 
consenting purposes. 
 
11.5. Participant Data Protection 
The PICF will explain that study data will be safely stored in computer databases as 
well as in paper form. The maintenance of confidentiality will be in accordance with 
national data and privacy legislation. Participants in this database are identified by a 
unique participant identification number and their initials. The PICF will also explain 
that for data verification purposes, authorized representatives of Orygen, regulatory 
authorities, HREC/IRBs or sites may require direct access to parts of the hospital or 
practice records relevant to the study, including medical history. 
 
 
12. Study Management 
12.1. Monitoring and Auditing 
Study monitoring will be performed in accordance with applicable regulations, ICH-
GCP, and Orygen Standard Operating Procedures (SOPs). The level of monitoring 
required for the study will be based on a risk assessment of the study by Orygen. 
 
During the course of the study, the Orygen monitor will regularly contact and may 
conduct remote visits to monitor study progress, confirm protocol, regulatory and 
ethical adherence, confirm data accuracy and provide information and support. The 
PI agrees to allow the monitor direct access to all relevant documents and to allocate 
their time and the time of their staff to the monitor to discuss findings and any relevant 
issues. Site staff will be provided with monitor and back up contact details in the event 
they have queries or require assistance. 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
58 of 79 | Pages  
 
An audit is a systematic and independent examination of study-related activities and 
documents to determine whether the approved study-related activities were 
conducted, and the data were recorded, analysed and accurately reported according 
to the protocol, Orygen SOPs and any applicable institutional requirement(s). 
Authorised representatives of Orygen, a regulatory authority, or the HREC may visit 
the site to perform audits or inspections.  The Investigator should contact Orygen or 
designee immediately if they are contacted by a regulator about an inspection at their 
site. If an audit or inspection occurs, the PI and institution agree to allow the 
auditor/inspector direct access to all relevant documents and allocate their time and 
the time of their staff to the auditor/inspector to discuss findings and any relevant 
issues. 
 
The Investigator will ensure that direct access to source data/documents for the 
purposes of monitoring, audits, HREC review and regulatory inspections is available 
throughout the study and during the record retention period. In addition, the 
Investigator will ensure that each study participant has consented, in writing, to their 
medical records for trial-related monitoring audits, HREC review and regulatory 
inspections. 
12.2. Training of Staff  
As per GCP, each individual involved in the conduct of a study will be qualified by 
education, training and experience to perform his or her respective task(s). The PI will 
maintain a record of all individuals involved in the study. The PI will ensure that 
appropriate training relevant to the study is given to staff, and that they will receive 
any new information of relevance to the performance of this study. 
12.3. Changes to the Protocol 
Study procedures will not be changed without the mutual agreement of the PI and the 
Sponsor. If it is necessary for the study protocol to be amended, the amendment or a 
new version of the study protocol must be approved by the HREC before 
implementation unless the safety of participants is at risk.  Local requirements must 
be followed. If a protocol amendment requires a change to the PICF, approval of the 
revised PICF by Orygen and by the HREC is required before the revised form can be 
used to consent potential participants. 
 
12.4. Protocol Compliance 
The study shall be conducted as described in the approved protocol. All revisions to 
the protocol must be discussed with Orygen. The investigator should not implement 
any deviation or change to the protocol without prior review and documented 
approval from the HREC of an amendment, except where necessary to eliminate an 
immediate hazard(s) to study participants. Any significant deviation must be 
documented in the source documentation. If a deviation or change to a protocol is 
implemented to eliminate an immediate hazard(s) prior to obtaining HREC approval 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
59 of 79 | Pages  
 
as soon as possible, the deviation or change will be submitted to the HREC for review 
and approval. 
 
12.5. Study Termination 
The planned start date for this study is the date of first patient first visit which we 
anticipate will be November 2021. The recruitment period will be for 2 years 
(November 2021- October 2022). The proposed completion date is the date of last 
patient last visit which we anticipate will be November 2025. The Sponsor, Orygen, 
reserves the right to terminate the study at any stage for any reason including funding 
considerations. 
 
12.6. Data handling and record retention 
Clinical data collected in the PRESCIENT research network will be entered in the 
secure online Orygen Research Project Management System (RPMS). The RPMS is 
login-protected and users can only access the section that pertains to their own 
recruitment site. Neurocognition data will be collected directly via the PennCNB 
website. MRI data, actigraphy data, speech samples, video recordings and EEG data 
will 
be 
stored 
in 
the 
University 
of 
Melbourne 
Mediaflux 
system 
(http://www.arcitecta.com/mediaflux/features/). Digital biomarker data will be 
recorded via the mindLAMP app and stored on an Orygen-based server.  
 
All coded data will be transferred from the Orygen servers/University of Melbourne 
Mediaflux system to a secure server at the NIMH NDA (NDA Staging Environment). 
A copy of the data will remain at the Sponsor site on the Orygen servers/University 
of Melbourne Mediaflux system. The NIMH NDA Staging Environment will only be 
accessible by the Data Processing Analysis and Coordinating Center (DPACC). 
DPACC will conduct data monitoring and quality assurance checks on the data on 
this server. In some circumstances, the DPACC may also require access to some coded 
participant data on Orygen/University of Melbourne servers for QC and monitoring 
purposes, prior to it being sent to the NDA Staging Environment (e.g., to check raw 
neurocognitive scores in addition to the calculated scores transferred to the NDA). 
Following the DPACC review, the coded data will be transferred to the NIMH NDA 
Collaboration Space, a data repository maintained and sponsored by the National 
Institutes of Health (NIH). AMP SCZ investigators, AMP SCZ partners, FNIH and 
NIH staff will have access to the data in the NIMH NDA Collaboration Space for 
monitoring and data analysis purposes (subject to execution of an NDA Data Access 
Agreement). Every six months the NIMH NDA will make the curated data available 
to the general research community (NDA Curated Releases). 
 
The raw audiovisual data will remain on the University of Melbourne Mediaflux 
system. Only processed audiovisual data (i.e., variables extracted from the raw data) 
will be transferred to the NIMH NDA. The raw passive sensing data, including 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
60 of 79 | Pages  
 
geolocation data, will be transferred to the NIMH NDA and included in the NDA 
Curated Releases. Investigators who access this raw passive sensing data via the 
NIMH NDA will require institutional ethics committee approval to do so (see 15.2). 
The reason for transferring raw geolocation data to the NIMH NDA is that such data 
holds significant promise for the development of novel environmental risk metrics. 
Providing this data to the general research community will aid the development of 
such measures for use in future studies, which may in turn contribute to the 
identification of risk and resilience factors in this high risk clinical population.  
 
All study documentation will be retained indefinitely (following completion of the 
study) including participant files and other essential documents (study protocol, 
signed informed consent forms, correspondence, and other documents pertaining to 
the conduct of the study). Should the Investigator wish to assign the study 
documentation to another party or move to another location, Orygen must be notified.  
In addition, the Investigator should notify Orygen prior to destruction of any study 
documentation, regardless of the timeframe lapsed. 
The Sponsor should notify the Investigator/Institution in writing if/when study-
related records are no longer required to be kept.  
 
13. Data Management 
13.1. Documentation 
A screening log of all potential participants specific to the recruitment site will be 
maintained by the site. This will include potential participants who were considered 
but later deemed ineligible due to meeting one of the exclusion criteria or due to 
investigator discretion. The reasons for exclusion or refusal will also be recorded 
against their ineligibility/refusal status. This log will be stored securely and locally by 
the recruitment site. All participants who are considered for or enrolled in the study 
will receive an individual identification number. The RA Procedures Manual provides 
more in-depth information regarding the screening log and enrolment of participants.  
Documentation regarding potential participants and participants enrolled in the study 
will only be accessible to site study team members who need this information for 
conducting the study. Confidentiality will further be maintained by assigning each 
subject a study-specific number, and coding all data collected with that number, using 
the NIH Globally Unique Identifier (GUID) tool. All data collection media will use the 
study-specific identification number to link the data to one individual. Data on the 
RPMS will only be accessible to study team members from the same site as the 
participant.  
 
Source data will be constituted as documents where the study data are first recorded. 
This will include the hard-copy questionnaires and measures, and raw data such as 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
61 of 79 | Pages  
 
EEG recordings and neurocognitive computer task responses. These data will be 
retained in a secure location at or by the recruitment site, accessible only to delegated 
study team members and relevant site staff. 
 
Electronic Case Report Forms (eCRFs) will also be used for documentation and 
reporting data to Orygen. For the measures in which the results are entered directly 
into the eCRF, the eCRF becomes the source documentation.  
 
Research Assistants or other appropriate delegates will be responsible for entering 
data into the eCRF.   
 
Study monitoring will be performed in accordance with the monitoring plan 
developed by Sponsor Operations in conjunction with the study team and the 
DPACC. This will be augmented by the study’s quality control plan.  
 
13.2. Database management 
Internet-based database applications will be used at Orygen and by international 
collaborators for the Case Report Form, with relevant data being entered online. The 
database applications will be modelled on previous studies that have adopted the 
eCRF data collection method. Data collected in the eCRF will be entered via a secure 
website. Access to the eCRF will be restricted to study personnel and the level of access 
will be set to maintain the privacy and confidentiality of participant information. Data 
is backed up on a regular basis and an audit trail of entered, amended or deleted data, 
as well as the staff member who made those changes, is retained. After any monitoring 
and data management queries are resolved and complete, the study database will be 
locked and the eCRF signed off by the PI for each participant. All data will be exported 
into the appropriate software to enable statistical analysis on secure Orygen or 
collaborator servers. All study team members will need to apply for access to the eCRF 
through the study’s Project Manager or coordinating investigator. These processes 
will be recorded and kept with the study essential documentation.  
This study has received funding from the National Institute of Health (NIH) in the 
USA, and as part of this funding agreement, pseudo-anonymised (coded) data will be 
submitted to the National Institute of Mental Health NIMH Data Archive (NDA) and 
the NIMH Repository and Genomics Resource (NRGR) based in the USA (see data 
flow description in 12.6). The NDA and NRGR are data repositories run by NIMH that 
allows researchers studying mental illness to collect and share pseudo-anonymised 
information with each other to progress scientific research.  
The act of pseudo-anonymising information will ensure that all personal information 
about research participants is removed and replaced with a code number. This then 
becomes re-identifiable (coded) information and means the research team will have 
the link between the participant’s personal identifying information and the coded data 
should the need to re-identify the participant arises. The principal investigator and 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
62 of 79 | Pages  
 
study team will keep the personal identifying information and matching unique code 
in a securely protected database. The DPACC will only access the coded data and will 
not access personal identifying information or the link between the coded data and 
personal identifying information. The only exception to this is that the DPACC will 
access dates when assessments were completed.  
 
As described, this is an international study and international data transfer is going to 
occur. Data flow is described appropriately in the consent forms and in relevant data 
management procedural documentation. All data will be transferred securely, at 
highest industry standards, and in accordance with applicable privacy and 
confidentiality requirements. 
 
13.3. Protocol Deviations and Suspected/Serious Breaches 
13.3.1 Protocol Deviations 
Deviations are any (minor or major) breach, divergence or departure from the 
requirements of Good Clinical Practice or the clinical trial protocol.  A protocol 
deviation is a less serious non-compliance with the approved study protocol. 
Examples of protocol deviations may include: 
1) Missed visits 
2) Missed assessments 
3) Visits/assessments performed early or later than scheduled date. 
 
13.3.2 Suspected Breaches 
A suspected breach is a possible serious breach of GCP or the protocol which has been 
identified by a third party (other than the Sponsor, e.g., the investigator) but has yet 
to be formally confirmed as a serious breach by the Sponsor. An example of suspected 
breaches include missing consent forms.  
 
13.3.3 Serious Breaches 
A serious breach is a breach of GCP or the protocol that is likely to affect to a 
significant degree: 
a)  
The safety or rights of a study participant, or 
b)  
The reliability and robustness of the data generated in the study  
 
Examples of potential serious breaches include: 
• 
Participant Informed Consent: 
- 
Confirmation that consent is not obtained 
 
• 
Missed study visits or reduced contact due to error by study team that 
impacts on participant safety. 
 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
63 of 79 | Pages  
 
14. Statistical Methods 
The details of the analytical approach will be determined based on ongoing 
consultation with the DPACC and the NIMH Steering Committee. A Data Analysis 
Team is currently being established with representatives from the DPACC, 
PRESCIENT, ProNET, NIMH, and AMP SCZ partners. However, a broad outline of 
the likely statistical methods is outlined below. It is expected that a variety of interim 
analyses may be agreed upon by relevant stakeholders.  
 
 
Testing current and forthcoming prediction models (aims 2a, 2b) 
The scale and range of data collected in the PRESCIENT network will allow external 
validation of existing and forthcoming prediction models in the field. Specifically, the 
CHR prediction models and risk calculators for psychosis conversion that have 
already been published, summarised in a number of reviews8, 116, 117, will be tested for 
performance in this newly recruited large sample. There are also a number of 
forthcoming CHR prediction models that can be tested in the current dataset, 
including those from the EU-GEI118, Pronia64, Psyscan119, and IPPACT120 studies. The 
multimodal data to be collected in PRESCIENT will be of sufficient depth and breadth 
to test all of these models.  
 
Of the existing prediction models in the field, the one that shows the strongest 
performance in the PRESCIENT sample may be made into an online risk calculator 
for preliminary use in some clinical settings (e.g., to allow clinical decision-making 
regarding the value of further assessments, such as referral for imaging), as in other 
areas of medicinee.g.121, and to allow stratification for aetiological and treatment 
research. Importantly, because the PRESCIENT dataset will include participants 
recruited from both primary and specialist service settings (headspace and 
HEPs/Orygen), the risk calculator will be able to be calibrated for type of 
recruitment/service setting, which has been found to be an important factor in risk 
prediction in this field122. This use of the PRESCIENT dataset to externally validate 
existing and forthcoming prediction models will address one of the key limitations in 
the field9, namely the lack of robust validation procedures on prediction models.  
 
Developing new prediction models (specific aim 2c) 
Critically, the PRESCIENT dataset will facilitate the development of new, more 
refined prediction models, and associated risk calculators, that take advances in the 
field into account (such as iterative and dynamic prediction, see 2.3) and which 
directly address the limitations identified in the field (lack of internal and external 
validation; low ratio of converted cases to number of predictor variables; lack of pre-
selection of predictor variables; inappropriate methods of presenting model 
performance; not covarying for treatment received; insufficient use of clinical 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
64 of 79 | Pages  
 
comparison groups9, 123, 124). Data from the PRESCIENT and ProNET networks will be 
combined (i.e., the AMP SCZ dataset) for the development of these new prediction 
models. The primary purpose of these new prediction models will be to guide 
stratification of patients in future pharmacological clinical trials, in line with the 
overarching aim of AMP SCZ to develop new treatments for the CHR stage of illness.  
 
There are a number of reasons that the AMP SCZ dataset will be able to improve on 
prediction models based on existing datasets and which may be far more useful for 
treatment decision-making and treatment development:  
1. Scale and multimodal data: The size of the dataset (approximate CHR n of 2000) and 
the comprehensive suite of multimodal data will provide greater predictive accuracy 
in model development and allow the integration of multiple data types.  
2. Dynamic prediction: There is compelling preliminary evidence that using repeat 
assessments over time can enhance predictive performance and provide early 
warning signs of deterioration or lack of treatment response. This modelling requires 
time series data, which is not extensively available in existing data sets, but will be 
collected in this new network. A variety of methods will be used to collect the required 
data (see 8.1 Schedule of Assessments): repeat biomarker data to examine predictive 
value of biomarker trajectories; in-person and online clinical, neurocognitive, and 
speech data; and digital assessment methods, including EMA and passive sensing 
(actigraphy and geolocation). The research team has developed and has access to 
world leading applications for both EMA and passive sensing. These dynamic aspects 
of predictive modelling may provide risk calculations based on trajectories in 
individual-level data and which can be updated over time in response to incoming 
information, providing recommendations for change in treatment approach (e.g., 
increase in risk indicating the need for intensification of treatment). They also have 
the potential to provide ‘real time’ indications of imminent deterioration in mental 
state.  
3. Modelling impact of treatment: Most CHR patients included in research cohorts 
receive psychosocial and/or pharmacological treatment, even if ‘standard care’ rather 
than controlled trial treatment. There has been increased recognition in recent years 
that this treatment (both as pre-emptive and for presenting complaints) influences 
outcomes, i.e., prediction models may in fact be modelling treatment response rather 
than natural course of disorder, or possibly an interaction between the two123, 125. The 
impact of type/degree of treatment components delivered (e.g., psychosocial 
interventions, medications, nutritional supplements, etc.) will be captured and 
incorporated into predictive modelling. 
 
Both traditional statistical and machine learning approaches will be deployed in 
development of prediction models. Statistical approaches will include Cox regression 
and joint modelling. While the selection of variables to be measured in the study are 
already informed by their predictive performance in previous studies, variable 
selection methods including LASSO and stepwise selection will be used to select 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
65 of 79 | Pages  
 
potential predictors in the final model. The candidate predictors include the range of 
multimodal assessments outlined in 8.1. Due to the high number of predictor 
variables, data reduction procedures may be used. Internal validation of the model 
will be conducted using bootstrap validation (a resampling technique). The 
performance of the prediction models will be assessed using measures such as 
sensitivity, specificity and concordance index (which should be at least 0.7 for good 
predictive performance). Machine learning approaches will include support vector 
machine (SVM) algorithms using model training and leave-one-site-out cross 
validation. 
 
External validation (specific aim 3) 
If a strong prediction model can be obtained, further evaluation of the prediction 
model will be conducted by using an external validation sub-sample from the AMP 
SCZ cohort. Data from a subset of sites across the two networks will be held back from 
the initial model development phase in order to externally validate the performance 
of the model. This will test the replicability of the model’s performance and the 
generalisability of the findings to diverse healthcare settings. Calibration performance 
of the model will be assessed using calibration plot (plot of predicted outcome 
probabilities against observed outcome frequencies) and tests for calibration intercept 
and slope. Discrimination performance will be assessed using measures such as 
sensitivity, specificity and concordance index. 
 
 
 
 
 
 
15. Publication and Use of Study Findings 
15.1 Publications 
The research team will follow the publication guidelines set out in Section 4 
(Publication and dissemination of research findings) and Section 5 (Authorship) of the 
2007 Australian Code for the Conduct of Research. An AMP SCZ publication policy 
has been established with the funding body, NIMH, outlining the types of research 
papers that will be published using this dataset and authorship designations. All 
research findings, whether containing negative or positive results, will be 
disseminated accurately. After approval by the coordinating/Principal Investigator, 
co-investigators and biostatisticians, results of the study will be published in peer-
reviewed scientific journals and presented at scientific conferences. The final results 
will be published after termination of the study. Where participants have asked to see 
the results of the study, these results will be provided to them in due course. AMP 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
66 of 79 | Pages  
 
SCZ data and analyses will be made publicly available to suitably qualified 
researchers through the NIMH Data Archive. 
 
15.2  NIMH Data Archive 
The https://nda.nih.gov/ will provide cloud-based infrastructure to facilitate storage 
and analysis of AMP SCZ data. The data archive currently holds raw and derived data 
collected from a total of 500,000 research participants using a variety of measures, 
including clinical, imaging, electrophysiological, cognitive, genetic, and outcome 
data. All AMP SCZ data stored in the archive will adhere to the NIMH Data Archive 
(NDA) terms and conditions and the NIMH Data Sharing Policy. Specifically, 
participant data will be transferred in a privacy-enabled manner and will be protected 
by practices that include the removal of any personally identifiable information; 
accredited users will be given secure, role-based access to the data. The archive 
includes data dictionaries to describe and enable efficient searches across the diverse 
types of data. 
The NDA will make curated AMP SCZ data available to the broader research 
community on a 6-monthly basis, in accordance with ‘open science’ principles. The 
NDA will also work with the DPACC to make data analysis pipelines available to the 
research community. The NDA requires safeguards and institutional protections and 
monitoring with clear guidelines for data use. Only investigators at approved 
institutions are permitted to submit a data use certification to the NDA. This is a legal 
document that an institution signs on behalf of the investigator. Investigators 
approved to access the data and their institutions must pledge not to attempt to 
identify any participant. Data use is restricted to research purposes only. Additionally, 
geolocation data is treated in the NDA with the additional safeguard that approved 
investigators and institutions must also receive local ethics committee approval from 
their institution to access the data and must undergo ongoing local ethics committee 
oversight. 
The NDA, established in 2006, is sustained on an ongoing basis through NIMH funds. 
 
 
15.3 Clinical Tool Development 
As noted above, the prediction models developed through this program of work may 
lead to the development of clinical prediction tools. Although the precise nature of 
these clinical prediction tools are yet to be decided, an outline of the likely process is 
provided below.   

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
67 of 79 | Pages  
 
 
The expectation is that, if a prediction model with strong performance can be obtained, 
the model will be accessible to clinicians and other interested parties either online, via 
a code repository, or through publications. Specifically, by inputting the values of the 
predictors from a particular individual into the model, the intent is for the prediction 
model to estimate the probability of conversion to psychosis (primary outcome of 
interest) for that individual. This probability can be regarded as a risk score and can 
aid clinicians to make decisions about appropriate level of monitoring, type, and 
duration of treatment. Examples of such prototype clinical tools (“risk calculators”) 
are available at these online links: https://apps.konsta.com.pl/app/transpsych/#, 
http://riskcalc.org:3838/napls/126. Due to the repeat assessments and digital 
momentary assessments conducted in the current study, a clinical tool that provides 
dynamic prediction may also be developed. This would involve inputting data 
collected over time for a particular patient, with the “risk calculator” being updated 
with this newly inputted information. Further evaluation of this clinical tool will be 
conducted by using decision analysis to assess the clinical value of the tool by taking 
into account the decisions that clinicians and patients would need to make with regard 
to possible interventions127. This future work will further test and refine the clinical 
tool.  
 
 
16. Funding 
This study is funded by the National Institute of Mental Health (NIMH), US. 
 
 
 
 
17. Outcomes and Significance 
Psychotic illnesses usually first emerge in young people and result in widespread 
suffering, protracted disability, premature death, and a huge economic burden. Early 
intervention represents a vital strategy to reduce this burden. Psychotic disorders are 
preceded by a prodromal period of distress, impaired functioning and subthreshold 
symptomatology. Our original research operationally defined the Clinical High Risk 
state, which predicts a substantially increased risk of incipient psychosis. There is 
substantial heterogeneity in clinical trajectories in the CHR population. The field is 
currently unable to reliably identify these trajectories early on, particularly on an 
individual patient level. The models to date (using clinical, neurocognitive, 
neuroimaging, neurobiological and genetic data) have yielded only modest predictive 
value for conversion to psychotic disorder and other outcomes. This presents a 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
68 of 79 | Pages  
 
challenge for targeted intervention development and developing robust aetiological 
models.  
 
The current large consortia-based project seeks to develop more robust prediction 
models for a range of outcomes in the CHR population (conversion to psychotic 
disorder, persistent and incident non-psychotic disorder, non-remission of CHR 
status, persistent negative symptoms, full recovery, functional outcome) and advance 
the introduction of risk prediction tools in clinical practice. These prediction models 
and associated clinical tools will be developed using multimodal data consisting of 
biomarkers (neuroimaging, neurocognition, neurophysiology, biospecimens), clinical 
data, and digital momentary assessments. The prediction models will facilitate 
selection of CHR patients for enrolment in clinical trials (patient stratification) and 
point towards targets for aetiological research and novel treatments.  They will also 
serve as measures of early treatment effects and provide tools for monitoring disease 
progression and clinical and functional outcomes. 
 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
69 of 79 | Pages  
 
 
18. References 
 
1. 
Yung AR, McGorry PD, McFarlane CA, Jackson HJ, Patton GC, Rakkar A. 
Monitoring and care of young people at incipient risk of psychosis. Schizophr 
Bull 1996;22(2):283-303. 
2. 
Yung AR, Phillips LJ, Yuen HP, Francey SM, McFarlane CA, Hallgren M, 
McGorry PD. Psychosis prediction: 12-month follow up of a high-risk 
("prodromal") group. Schizophr Res Mar 1 2003;60(1):21-32. 
3. 
Fusar-Poli P, Borgwardt S, Bechdolf A, et al. The psychosis high-risk state: a 
comprehensive state-of-the-art review. JAMA psychiatry Jan 2013;70(1):107-
120. 
4. 
Yung AR, Phillips LJ, Yuen HP, Francey SM, McFarlane CA, Hallgren M, 
McGorry PD. Psychosis prediction: 12-month follow up of a high-risk 
("prodromal") group. Schizophrenia Research 2003;60(1):21-32. 
5. 
Tsuang MT, Van Os J, Tandon R, et al. Attenuated psychosis syndrome in 
DSM-5. Schizophr Res Oct 2013;150(1):31-35. 
6. 
McGorry PD, Nelson B, Markulev C, et al. Effect of omega-3 Polyunsaturated 
Fatty Acids in Young People at Ultrahigh Risk for Psychotic Disorders: The 
NEURAPRO Randomized Clinical Trial. JAMA Psychiatry Jan 1 2017;74(1):19-
27. 
7. 
Polari A, Lavoie S, Yuen HP, et al. Clinical trajectories in the ultra-high risk 
for psychosis population. Schizophr Res Jul 2018;197:550-556. 
8. 
Schmidt A, Cappucciati M, Radua J, et al. Improving Prognostic Accuracy in 
Subjects at Clinical High Risk for Psychosis: Systematic Review of Predictive 
Models and Meta-analytical Sequential Testing Simulation. Schizophr Bull Mar 
1 2017;43(2):375-388. 
9. 
Studerus E, Ramyead A, Riecher-Rossler A. Prediction of transition to 
psychosis in patients with a clinical high risk for psychosis: a systematic 
review of methodology and reporting. Psychol Med May 2017;47(7):1163-1178. 
10. 
Fusar-Poli P, Rocchetti M, Sardella A, et al. Disorder, not just state of risk: 
meta-analysis of functioning and quality of life in people at high risk of 
psychosis. Br J Psychiatry Sep 2015;207(3):198-206. 
11. 
Carpenter WT. Attenuated psychosis syndrome: a new diagnostic class? J 
Nerv Ment Dis May 2015;203(5):325-327. 
12. 
Carpenter WT, Schiffman J. Diagnostic Concepts in the Context of Clinical 
High Risk/Attenuated Psychosis Syndrome. Schizophr Bull Sep 
2015;41(5):1001-1002. 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
70 of 79 | Pages  
 
13. 
Hazan H, Spelman T, Amminger GP, et al. The prognostic significance of 
attenuated psychotic symptoms in help-seeking youth. Schizophr Res Oct 12 
2019. 
14. 
Heinze K, Lin A, Nelson B, et al. The impact of psychotic experiences in the 
early stages of mental health problems in young people. BMC Psychiatry Jun 
28 2018;18(1):214. 
15. 
Iorfino F, Scott EM, Carpenter JS, et al. Clinical Stage Transitions in Persons 
Aged 12 to 25 Years Presenting to Early Intervention Mental Health Services 
With Anxiety, Mood, and Psychotic Disorders. JAMA Psychiatry Aug 28 2019. 
16. 
Ferrarelli F, Mathalon D. The prodromal phase: Time to broaden the scope 
beyond transition to psychosis? Schizophr Res Jan 7 2020. 
17. 
McGorry PD, Hartmann JA, Spooner R, Nelson B. Beyond the "at risk mental 
state" concept: transitioning to transdiagnostic psychiatry. World Psychiatry 
Jun 2018;17(2):133-142. 
18. 
McGorry PD, Australian Early Psychosis Research Network Writing G. 
Australian Early Psychosis Research Network: national collaboration, 
international competitive advantage. Med J Aust Mar 2 2015;202(4):170-171. 
19. 
headspace. headspace Annual Report 2018-2019 2019. 
20. 
Hilferty F, Cassells R, Muir ea. Is headspace making a difference to young people’s 
lives? Final report of the independent evaluation of the headspace program. Sydney: 
Social Policy Research Centre, UNSW; 2015. 
21. 
McGorry P, Bates T, Birchwood M. Designing youth mental health services 
for the 21st century: examples from Australia, Ireland and the UK. The British 
Journal of Psychiatry January 1, 2013 2013;202(s54):s30-s35. 
22. 
McGorry PD. The specialist youth mental health model: strengthening the 
weakest link in the public mental health system. Med J Aust Oct 1 2007;187(7 
Suppl):S53-56. 
23. 
McGorry PD, Tanti C, Stokes R, Hickie IB, Carnell K, Littlefield LK, Moran J. 
headspace: Australia's National Youth Mental Health Foundation - where 
young minds come first. Medical Journal of Australia Oct 1 2007;187(7):S68. 
24. 
Scott EM, Hermens DF, Glozier N, Naismith SL, Guastella AJ, Hickie IB. 
Targeted primary care-based mental health services for young Australians. 
Med J Aust Feb 6 2012;196:136-140. 
25. 
Rickwood DJ, Telford NR, Parker AG, Tanti CJ, McGorry PD. headspace - 
Australia's innovation in youth mental health: who are the clients and why 
are they presenting? Med J Aust Feb 3 2014;200(2):108-111. 
26. 
Purcell R, Jorm AF, Hickie IB, et al. Transitions Study of predictors of illness 
progression in young people with mental ill health: study methodology. Early 
Interv Psychiatry Feb 2015;9(1):38-47. 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
71 of 79 | Pages  
 
27. 
Purcell R, Jorm AF, Hickie IB, et al. Demographic and clinical characteristics 
of young people seeking help at youth mental health services: baseline 
findings of the Transitions Study. Early Interv Psychiatry Dec 2015;9(6):487-497. 
28. 
Nelson B, Amminger GP, Yuen HP, et al. Staged Treatment in Early 
Psychosis: A sequential multiple assignment randomised trial of interventions 
for ultra high risk of psychosis patients. Early Interv Psychiatry Jun 
2018;12(3):292-306. 
29. 
Rickwood DJ, Mazzer KR, Telford NR, Parker AG, Tanti CJ, McGorry PD. 
Changes in psychological distress and psychosocial functioning in young 
people visiting headspace centres for mental health problems. Med J Aust Jun 
1 2015;202(10):537-542. 
30. 
Yuen HP, Mackinnon A. Performance of joint modelling of time-to-event data 
with time-dependent predictors: an assessment based on transition to 
psychosis data. PeerJ 2016;4:e2582. 
31. 
Yuen HP, Mackinnon A, Hartmann J, et al. Dynamic prediction of transition 
to psychosis using joint modelling. Schizophr Res Dec 2018;202:333-340. 
32. 
Yuen HP, Mackinnon A, Nelson B. A new method for analysing transition to 
psychosis: Joint modelling of time-to-event outcome with time-dependent 
predictors. Int J Methods Psychiatr Res Mar 2018;27(1):1-12. 
33. 
Yuen HP, Mackinnon A, Nelson B. Dynamic prediction systems of transition 
to psychosis using joint modelling: extensions to the base system. Schizophr 
Res Dec 12 2019. 
34. 
Nelson B, McGorry PD, Wichers M, Wigman JTW, Hartmann JA. Moving 
From Static to Dynamic Models of the Onset of Mental Disorder: A Review. 
JAMA Psychiatry May 1 2017;74(5):528-534. 
35. 
Nelson B, Hartmann JA, Parnas J. Detail, dynamics and depth: Useful 
correctives for some current research trends. British Journal of Psychiatry 2018. 
36. 
Wichers M, Schreuder MJ, Goekoop R, Groen RN. Can we predict the 
direction of sudden shifts in symptoms? Transdiagnostic implications from a 
complex systems perspective on psychopathology. Psychol Med Feb 
2019;49(3):380-387. 
37. 
Wichers M. The dynamic nature of depression: a new micro-level perspective 
of mental disorder that meets current challenges. Psychol Med May 
2014;44(7):1349-1360. 
38. 
Wichers M, Groot PC, Psychosystems ESMGEWSG. Critical Slowing Down as 
a Personalized Early Warning Signal for Depression. Psychother Psychosom 
2016;85(2):114-116. 
39. 
Brankovic M, Akkerhuis KM, van Boven N, et al. Patient-specific evolution of 
renal function in chronic heart failure patients dynamically predicts clinical 
outcome in the Bio-SHiFT study. Kidney Int Apr 2018;93(4):952-960. 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
72 of 79 | Pages  
 
40. 
Cao Y, Jiang Y, Lin X, Liu J, Lu T, Cheng W, Yan F. Dynamic Prediction of 
Outcome for Patients With Ovarian Cancer: Application of a Joint Model for 
Longitudinal Cancer Antigen 125 Values. Int J Gynecol Cancer Jan 
2018;28(1):85-91. 
41. 
Scheffer M, Carpenter SR, Lenton TM, et al. Anticipating critical transitions. 
Science Oct 19 2012;338(6105):344-348. 
42. 
Scheffer M, Bolhuis JE, Borsboom D, et al. Quantifying resilience of humans 
and other animals. Proc Natl Acad Sci U S A Nov 20 2018;115(47):11883-11890. 
43. 
Scheffer M. Critical Transitions in Nature and Society: Princeton University 
Press; 2009. 
44. 
McGorry PD, Hickie IB, Yung AR, Pantelis C, Jackson HJ. Clinical staging of 
psychiatric disorders: A heuristic framework for choosing earlier, safer and 
more effective interventions. Australian and New Zealand Journal of Psychiatry 
Vol 40(8) Aug 2006, 616-622 2006. 
45. 
McGorry PD, Nelson B, Goldstone S, Yung AR. Clinical staging: A gateway to 
better health and social outcomes for psychotic and mood disorders. Canadian 
Journal of Psychiatry 2010;55(8):486-497. 
46. 
Shah JL, Scott, J., McGorry, P.D., Cross, S.P.M., Keshavan, M., Nelson, B., 
Wood, S.J., Marwaha, S., Yung, A.R., Scott, E.M., Öngür, D., Conus, P., Henry, 
C., Hickie, I.B., for the International Working Group on Transdiagnostic 
Clinical Staging in Youth Mental Health. Transdiagnostic clinical staging in 
youth mental health: A first international consensus statement. World 
Psychiatry 2020;19(2):233-242. 
47. 
Wichers M, Wigman JTW, Myin-Germeys I. Micro-Level Affect Dynamics in 
Psychopathology Viewed From Complex Dynamical System Theory. Emot 
Rev Oct 2015;7(4):362-367. 
48. 
van de Leemput IA, Wichers M, Cramer AO, et al. Critical slowing down as 
early warning for the onset and termination of depression. Proc Natl Acad Sci 
U S A Jan 7 2014;111(1):87-92. 
49. 
Hofmann SG, Curtiss J, McNally RJ. A Complex Network Perspective on 
Clinical Science. Perspect Psychol Sci Sep 2016;11(5):597-605. 
50. 
Reininghaus U, Depp CA, Myin-Germeys I. Ecological Interventionist Causal 
Models in Psychosis: Targeting Psychological Mechanisms in Daily Life. 
Schizophr Bull Mar 2016;42(2):264-269. 
51. 
Reininghaus U, Gayer-Anderson C, Valmaggia L, et al. Psychological 
processes underlying the association between childhood trauma and 
psychosis in daily life: an experience sampling study. Psychol Med Oct 
2016;46(13):2799-2813. 
52. 
Reininghaus U, Kempton MJ, Valmaggia L, et al. Stress Sensitivity, Aberrant 
Salience, and Threat Anticipation in Early Psychosis: An Experience Sampling 
Study. Schizophr Bull May 2016;42(3):712-722. 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
73 of 79 | Pages  
 
53. 
Reininghaus U, Oorschot M, Moritz S, et al. Liberal Acceptance Bias, 
Momentary Aberrant Salience, and Psychosis: An Experimental Experience 
Sampling Study. Schizophr Bull Jun 18 2019;45(4):871-882. 
54. 
Studerus E, Beck K, Fusar-Poli P, Riecher-Rossler A. Development and 
Validation of a Dynamic Risk Prediction Model to Forecast Psychosis Onset in 
Patients at Clinical High Risk. Schizophr Bull Jul 29 2019. 
55. 
Borsboom D. A network theory of mental disorders. World Psychiatry Feb 
2017;16(1):5-13. 
56. 
Borsboom D, Cramer AO. Network analysis: an integrative approach to the 
structure of psychopathology. Annu Rev Clin Psychol 2013;9:91-121. 
57. 
van Borkulo C, Boschloo L, Borsboom D, Penninx BW, Waldorp LJ, Schoevers 
RA. Association of Symptom Network Structure With the Course of 
Longitudinal Depression. JAMA Psychiatry Dec 2015;72(12):1219-1226. 
58. 
DeVylder JE, Muchomba FM, Gill KE, Ben-David S, Walder DJ, Malaspina D, 
Corcoran CM. Symptom trajectories and psychosis onset in a clinical high-risk 
cohort: the relevance of subthreshold thought disorder. Schizophr Res Nov 
2014;159(2-3):278-283. 
59. 
Chung Y, Cannon TD. Brain imaging during the transition from psychosis 
prodrome to schizophrenia. J Nerv Ment Dis May 2015;203(5):336-341. 
60. 
Lavoie S, Polari AR, Goldstone S, Nelson B, McGorry PD. Staging model in 
psychiatry: Review of the evolution of electroencephalography abnormalities 
in major psychiatric disorders. Early Interv Psychiatry Dec 2019;13(6):1319-
1328. 
61. 
Whitford TJ. Speaking-Induced Suppression of the Auditory Cortex in 
Humans and Its Relevance to Schizophrenia. Biol Psychiatry Cogn Neurosci 
Neuroimaging Sep 2019;4(9):791-804. 
62. 
Clark SR, Schubert KO, Baune BT. Towards personalized secondary 
prevention of psychosis: using probabilistic assessments of transition risk in 
psychosis prodrome. J Neural Transm 2015;122:155-169. 
63. 
Clark SR, Baune BT, Schubert KO, et al. Prediction of transition from ultra-
high risk to first-episode psychosis using a probabilistic model combining 
history, clinical assessment and fatty-acid biomarkers. Transl Psychiatry Sep 20 
2016;6(9):e897. 
64. 
Koutsouleris N, Kambeitz-Ilankovic L, Ruhrmann S, et al. Prediction Models 
of Functional Outcomes for Individuals in the Clinical High-Risk State for 
Psychosis or With Recent-Onset Depression: A Multimodal, Multisite 
Machine Learning Analysis. JAMA Psychiatry Nov 1 2018;75(11):1156-1172. 
65. 
Perkins DO, Olde Loohuis L, Barbee J, et al. Polygenic Risk Score 
Contribution to Psychosis Prediction in a Target Population of Persons at 
Clinical High Risk. Am J Psychiatry Nov 12 2019:appiajp201918060721. 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
74 of 79 | Pages  
 
66. 
Nelson B, Lavoie S, Gaweda L, et al. Testing a neurophenomenological model 
of basic self disturbance in early psychosis. World Psychiatry Feb 
2019;18(1):104-105. 
67. 
Nelson B, Lavoie S, Gaweda L, et al. The neurophenomenology of early 
psychosis: An integrative empirical study. Conscious Cogn Jan 2020;77:102845. 
68. 
Berger M, Kraeuter AK, Romanik D, Malouf P, Amminger GP, Sarnyai Z. 
Cortisol awakening response in patients with psychosis: Systematic review 
and meta-analysis. Neurosci Biobehav Rev Sep 2016;68:157-166. 
69. 
Goldsmith DR, Rapaport MH, Miller BJ. A meta-analysis of blood cytokine 
network alterations in psychiatric patients: comparisons between 
schizophrenia, bipolar disorder and depression. Mol Psychiatry Dec 
2016;21(12):1696-1709. 
70. 
Berk M. The Classification of Biomarkers. JAMA Psychiatry Oct 
2015;72(10):1056-1057. 
71. 
Smesny S, Milleit B, Schaefer MR, et al. Effects of omega-3 PUFA on the 
vitamin E and glutathione antioxidant defense system in individuals at ultra-
high risk of psychosis. Prostaglandins, leukotrienes, and essential fatty acids Oct 
2015;101:15-21. 
72. 
Lavoie S, Berger M, Schlogelhofer M, et al. Erythrocyte glutathione levels as 
long-term predictor of transition to psychosis. Translational psychiatry Mar 21 
2017;7(3):e1064. 
73. 
Upthegrove R, Khandaker GM. Cytokines, Oxidative Stress and Cellular 
Markers of Inflammation in Schizophrenia. Current topics in behavioral 
neurosciences May 22 2020;44:49-66. 
74. 
Kohler-Forsberg O, Petersen L, Gasse C, Mortensen PB, Dalsgaard S, Yolken 
RH, Mors O, Benros ME. A Nationwide Study in Denmark of the Association 
Between Treated Infections and the Subsequent Risk of Treated Mental 
Disorders in Children and Adolescents. JAMA Psychiatry Mar 1 
2019;76(3):271-279. 
75. 
Madrid-Gambin F, Focking M, Sabherwal S, et al. Integrated Lipidomics and 
Proteomics Point to Early Blood-Based Changes in Childhood Preceding Later 
Development of Psychotic Experiences: Evidence From the Avon 
Longitudinal Study of Parents and Children. Biol Psychiatry Jul 1 
2019;86(1):25-34. 
76. 
Focking M, Sabherwal S, Cates HM, et al. Complement pathway changes at 
age 12 are associated with psychotic experiences at age 18 in a longitudinal 
population-based study: evidence for a role of stress. Mol Psychiatry Jan 11 
2019. 
77. 
English JA, Lopez LM, O'Gorman A, et al. Blood-Based Protein Changes in 
Childhood Are Associated With Increased Risk for Later Psychotic Disorder: 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
75 of 79 | Pages  
 
Evidence From a Nested Case-Control Study of the ALSPAC Longitudinal 
Birth Cohort. Schizophr Bull Feb 15 2018;44(2):297-306. 
78. 
Walker EF, Trotman HD, Pearce BD, et al. Cortisol levels and risk for 
psychosis: initial findings from the North American prodrome longitudinal 
study. Biol Psychiatry Sep 15 2013;74(6):410-417. 
79. 
Labad J, Stojanovic-Perez A, Montalvo I, et al. Stress biomarkers as predictors 
of transition to psychosis in at-risk mental states: roles for cortisol, prolactin 
and albumin. J Psychiatr Res Jan 2015;60:163-169. 
80. 
Berger M, Lavoie S, McGorry PD, et al. Relationship between allostatic load 
and clinical outcomes in youth at ultra-high risk for psychosis in the 
NEURAPRO study. Schizophr Res Oct 16 2018. 
81. 
Miller AH, Raison CL. The role of inflammation in depression: from 
evolutionary imperative to modern treatment target. Nat Rev Immunol Jan 
2016;16(1):22-34. 
82. 
Bedi G, Carrillo F, Cecchi GA, et al. Automated analysis of free speech 
predicts psychosis onset in high-risk youths. Npj Schizophrenia 08/26/online 
2015;1:15030. 
83. 
Corcoran CM, Carrillo F, Fernandez-Slezak D, Bedi G, Klim C, Javitt DC, 
Bearden CE, Cecchi GA. Prediction of psychosis across protocols and risk 
cohorts using automated language analysis. World Psychiatry Feb 
2018;17(1):67-75. 
84. 
Gupta T, Haase CM, Strauss GP, Cohen AS, Mittal VA. Alterations in facial 
expressivity in youth at clinical high-risk for psychosis. J Abnorm Psychol May 
2019;128(4):341-351. 
85. 
Gifford G, Crossley N, Fusar-Poli P, Schnack HG, Kahn RS, Koutsouleris N, 
Cannon TD, McGuire P. Using neuroimaging to help predict the onset of 
psychosis. Neuroimage Jan 15 2017;145(Pt B):209-217. 
86. 
Yung AR, Yuen HP, McGorry PD, et al. Mapping the onset of psychosis: the 
Comprehensive Assessment of At-Risk Mental States. Aust N Z J Psychiatry 
Nov-Dec 2005;39(11-12):964-971. 
87. 
Polari A, Lavoie S, Yuen HP, et al. Clinical trajectories in the ultra-high risk 
for psychosis population. Schizophr Res Feb 18 2018. 
88. 
Andreasen NC, Carpenter WT, Jr., Kane JM, Lasser RA, Marder SR, 
Weinberger DR. Remission in schizophrenia: proposed criteria and rationale 
for consensus.[see comment]. American Journal of Psychiatry 2005;162(3):441-
449. 
89. 
Yung AR, Nelson B, McGorry PD, Wood SJ, Lin A. Persistent negative 
symptoms in individuals at Ultra High Risk for psychosis. Schizophr Res Apr 
2019;206:355-361. 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
76 of 79 | Pages  
 
90. 
Buchanan RW. Persistent negative symptoms in schizophrenia: an overview. 
Schizophr Bull Jul 2007;33(4):1013-1022. 
91. 
Nelson B, Yuen HP, Wood SJ, et al. Long-term follow-up of a group at ultra 
high risk ("prodromal") for psychosis: the PACE 400 study. JAMA Psychiatry 
Aug 2013;70(8):793-802. 
92. 
Moons KG, Altman DG, Reitsma JB, et al. Transparent Reporting of a 
multivariable prediction model for Individual Prognosis or Diagnosis 
(TRIPOD): explanation and elaboration. Ann Intern Med Jan 6 2015;162(1):W1-
73. 
93. 
Riley RD, Ensor J, Snell KIE, et al. Calculating the sample size required for 
developing a clinical prediction model. Bmj Mar 18 2020;368:m441. 
94. 
Overall J, Gorham D. The Brief Psychiatric Rating Scale. Psychological Reports 
1962 1962;10:799-812. 
95. 
Norman SB, Cissell SH, Means-Christensen AJ, Stein MB. Development and 
validation of an Overall Anxiety Severity And Impairment Scale (OASIS). 
Depression and anxiety 2006;23(4):245-249. 
96. 
Group WAW. The Alcohol, Smoking and Substance Involvement Screening 
Test (ASSIST): development, reliability and feasibility. Addiction Sep 
2002;97(9):1183-1194. 
97. 
First MB, Williams JBW, Karg RS, Spitzer RL. Structured Clinical Interview for 
DSM-5, Research Version  (SCID-5 for DSM-5, Research Version; SCID-5-RV). 
Arlington, VA: American Psychiatric Association; 2015. 
98. 
Goldman H, Skodol A, Lave T. Revising Axis V for DSM-IV: A review of 
measures of social functioning. American Journal of Psychiatry 1992;149:1148-
1156. 
99. 
Radua J, Ramella-Cravaro V, Ioannidis JPA, et al. What causes psychosis? An 
umbrella review of risk and protective factors. World Psychiatry Feb 
2018;17(1):49-66. 
100. 
Wechsler D. Wechsler Abbreviated Scale of Intelligence -Second Edition (WASI -II). 
San Antonio, Texas: Psychological Corporation; 2011. 
101. 
Lavoie S, Allott K, Amminger P, et al. Harmonised collection of data in youth 
mental health: Towards large datasets. Aust N Z J Psychiatry Jan 2020;54(1):46-
56. 
102. 
First MB, Williams JBW, Benjamin LS, Spitzer RL. Structured Clinical Interview 
for DSM-5 Personality Disorder (SCID-5-PD). Arlington, VA: American 
Psychiatric Association; 2015. 
103. 
Initiative NG. Family Interview for Genetic Studies (FIGS). Rockville: National 
Institute of Mental Health 1992. 
104. 
Cornblatt BA, Auther AM, Niendam T, Smith CW, Zinberg J, Bearden CE, 
Cannon TD. Preliminary findings for two new measures of social and role 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
77 of 79 | Pages  
 
functioning in the prodromal phase of schizophrenia. Schizophr Bull May 
2007;33(3):688-702. 
105. 
Strauss GP, Pelletier-Baldelli A, Visser KF, Walker EF, Mittal VA. A review of 
negative symptom assessment strategies in youth at clinical high-risk for 
psychosis. Schizophr Res Aug 2020;222:104-112. 
106. 
Hanish AE, Lin-Dyken DC, Han JC. PROMIS Sleep Disturbance and Sleep-
Related Impairment in Adolescents: Examining Psychometrics Using Self-
Report and Actigraphy. Nurs Res May/Jun 2017;66(3):246-251. 
107. 
Addington D, Addington J, Maticka-Tyndale E, Joyce J. Reliability and 
validity of a depression rating scale for schizophrenics. Schizophr Res Mar 
1992;6(3):201-208. 
108. 
Addington J, Shah H, Liu L, Addington D. Reliability and validity of the 
Calgary Depression Scale for Schizophrenia (CDSS) in youth at clinical high 
risk for psychosis. Schizophr Res Mar 2014;153(1-3):64-67. 
109. 
Posner K, Brown GK, Stanley B, et al. The Columbia-Suicide Severity Rating 
Scale: initial validity and internal consistency findings from three multisite 
studies with adolescents and adults. Am J Psychiatry Dec 2011;168(12):1266-
1277. 
110. 
Salokangas RK, Schultze-Lutter F, Patterson P, et al. Psychometric properties 
of the Trauma and Distress Scale, TADS, in an adult community sample in 
Finland. Eur J Psychotraumatol 2016;7:30062. 
111. 
Cohen S, & Williamson, G. Perceived stress in a probability sample of the 
United States. In: (Eds.) SSSO, ed. The social psychology of health: Symposium on 
applied social psychology. . Newbury Park, CA: Sage; 1988:31-37. 
112. 
Janssen I, Hanssen M, Bak M, Bijl RV, de Graaf R, Vollebergh W, McKenzie K, 
van Os J. Discrimination and delusional ideation. Br J Psychiatry Jan 
2003;182(1):71-76. 
113. 
Petersen AC, Crockett L, Richards M, Boxer A. A self-report measure of 
pubertal status: Reliability, validity, and initial norms. J Youth Adolesc Apr 
1988;17(2):117-133. 
114. 
Shiffman S, Stone AA, Hufford MR. Ecological momentary assessment. . Annu 
Rev Clin Psychol 2008;4:1-32. 
115. 
McGorry PD. Early clinical phenotypes, clinical staging, and strategic 
biomarker research: building blocks for personalized psychiatry. Biol 
Psychiatry Sep 15 2013;74(6):394-395. 
116. 
Addington J, Farris M, Stowkowy J, Santesteban-Echarri O, Metzak P, Kalathil 
MS. Predictors of Transition to Psychosis in Individuals at Clinical High Risk. 
Curr Psychiatry Rep Apr 29 2019;21(6):39. 
117. 
Sanfelici R, Dwyer DB, Antonucci LA, Koutsouleris N. Individualized 
Diagnostic and Prognostic Models for Patients With Psychosis Risk 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
78 of 79 | Pages  
 
Syndromes: A Meta-analytic View on the State of the Art. Biol Psychiatry Aug 
15 2020;88(4):349-360. 
118. 
European Network of National Networks studying Gene-Environment 
Interactions in S, van Os J, Rutten BP, et al. Identifying gene-environment 
interactions in schizophrenia: contemporary challenges for integrated, large-
scale investigations. Schizophr Bull Jul 2014;40(4):729-736. 
119. 
Tognin S, van Hell HH, Merritt K, et al. Towards Precision Medicine in 
Psychosis: Benefits and Challenges of Multimodal Multicenter Studies-
PSYSCAN: Translating Neuroimaging Findings From Research into Clinical 
Practice. Schizophr Bull Aug 19 2019. 
120. 
Bonnett LJ, Varese F, Smith CT, Flores A, Yung AR. Individualised prediction 
of psychosis in individuals meeting at-risk mental state (ARMS) criteria: 
protocol for a systematic review of clinical prediction models. Diagn Progn Res 
2019;3:21. 
121. 
Wells BJ, Kattan MW, Cooper GS, Jackson L, Koroukian S. ColoRectal Cancer 
Predicted Risk Online (CRC-PRO) Calculator Using Data from the Multi-
Ethnic Cohort Study. The Journal of the American Board of Family 
                Medicine 2014-01-01 00:00:00 2014;27:42-55. 
122. 
Fusar-Poli P, Schultze-Lutter F, Cappucciati M, et al. The Dark Side of the 
Moon: Meta-analytical Impact of Recruitment Strategies on Risk Enrichment 
in the Clinical High Risk State for Psychosis. Schizophr Bull May 
2016;42(3):732-743. 
123. 
Nelson B, Hartmann JA. Prediction in mental health research and its limits (or 
why life can only be understood backwards but must be lived forwards). 
Early Interv Psychiatry Oct 2018;12(5):767-770. 
124. 
Millman ZB, Gold JM, Mittal VA, Schiffman J. The Critical Need for Help-
Seeking Controls in Clinical High-Risk Research. Clinical Psychological Science 
2019;7(6):1171-1189. 
125. 
McGorry PD, Nelson B. Beyond meta: The limits of the analysts. JAMA 
Psychiatry 2020;In press. 
126. 
Cannon TD, Yu C, Addington J, et al. An Individualized Risk Calculator for 
Research in Prodromal Psychosis. Am J Psychiatry Oct 1 2016;173(10):980-988. 
127. 
Vickers AJ, Van Calster B, Steyerberg EW. Net benefit approaches to the 
evaluation of prediction models, molecular markers, and diagnostic tests. Bmj 
Jan 25 2016;352:i6. 
 
 
 
 
 

HREC 2021.166 
CONFIDENTIAL 
 
 
PRESCIENT Protocol Version 2.0  
17th November 2021 
CONFIDENTIAL 
79 of 79 | Pages  
 
 
 
Appendix A 
 
Antipsychotic Dose Equivalents 
 
The doses provided in the table below are currently equivalent to a haloperidol dose 
of 50 mg. The RA must seek out the latest dose equivalent at the time of entry into the 
study for each participant this relates to.  
 
Abbreviated Drug Name, Drug Name and Trade name 
 
Dose in mg 
AMS 
Amisulpiride (Solian) 
1875 
APP 
Aripiprazole (Abilitat, Abilify) 
187.5 
ASP 
Asenapine (Saphris) 
125 
BRX 
Brexpiprazole (Rexulti) 
25 
CRP 
Cariprazine (Vraylar) 
18.75 
CPZ 
Chlorpromazine (Largactil) 
2500 
CLZ 
Clozapine (Clozaril) 
2500 
DPL 
Droperidol (Droleptan) 
100 
FLH 
Fluphenazine HCL (Anatensol) 
50 
HPL 
Haloperidol (Haldol) 
50 
ILO 
Iloperidone (Fanapt) 
100 
LUM 
Lumateperone (Caplyta) 
525 
LUR 
Lurasidone (Latuda) 
1500 
OLZ 
Olanzapine (Zyprexa) 
125 
PAL 
Paliperidone (Invega) 
50 
PCZ 
Pericyazine (Neulactil) 
250 
PIM 
Pimozide (Orap) 
50 
PPH 
Perphenazine (Trilafon) 
200 
QTP 
Quetiapine Fumarate (Seroquel) 
1875 
RIS/RSP 
Risperidone (Risperdal) 
50 
SUL 
Sulpiride (Dolmatil, Sulpitil, Sulparex) 
5000 
THI 
Thiothixene (Navane) 
100 
THZ 
Thioridazine (Melleril, Aldazine) 
2500 
TPZ 
Trifluoperazine (Stelazine) 
125 
ZPD 
Ziprasidone (Geodon) 
1500