PROSECCA: Using AI and health records to predict how people with prostate cancer respond to radiotherapy
Improving Radiotherapy in PROState Cancer Using EleCtronic Population-based healthCAre Data: The PROSECCA Study, Answering New Questions in Prostate Cancer
This project uses AI on past medical and radiotherapy records of men treated for prostate cancer to try to predict who will have poor treatment responses or long-term side effects.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 15000 (estimated) |
| Sex | Male |
| Sponsor | University of Edinburgh Academic / other |
| Drugs / interventions | radiation |
| Locations | 1 site (Edinburgh, Lothian) |
| Trial ID | NCT06714630 on ClinicalTrials.gov |
What this trial studies
PROSECCA links radiotherapy planning data, diagnostic and treatment CT images, PSA follow-up, and broader healthcare records from up to 15,000 prostate cancer patients treated in Scotland. The team will apply machine learning to these linked datasets to find patterns and factors in a patient’s medical history that predict radiotherapy outcomes and toxicity. The work builds on local proof-of-concept data showing AI can identify higher-risk patients before treatment. The goal is to turn those predictive signals into tools that could be used in routine care to personalise radiotherapy decisions.
Who should consider this trial
Good fit: Ideal candidates for the dataset are men with prostate cancer who received full-course external beam radiotherapy with available radiotherapy planning CT, treatment planning data, regular PSA follow-up, and linked healthcare records.
Not a fit: Patients without complete imaging, treatment planning data, PSA follow-up, or linked healthcare records, or those who did not complete radiotherapy or lack long-term follow-up, are unlikely to be included or benefit.
Why it matters
Potential benefit: If successful, the approach could identify patients at higher risk of poor response or radiation side effects earlier so clinicians can tailor or avoid treatments that cause long-term harm.
How similar studies have performed: This approach builds on early proof-of-concept work from the team and on emerging AI studies in radiotherapy, but such methods are not yet widely adopted into routine clinical practice.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * External beam radiotherapy delivered by a linear accelerator * Prostate Specific Antigen (PSA) recorded at regular intervals after radiotherapy * Minimum of 10 year survival post-radiotherapy * Diagnostic Computerised Tomography (CT) acquired * Radiotherapy planning CT acquired * Radiotherapy treatment planning data available * Corresponding healthcare data available to infer toxicity events (ref previous work by Lemanska et al) Exclusion Criteria: * Incomplete course of radiotherapy * No PSA data * No follow-up corresponding healthcare data available * No imaging data available
Where this trial is running
Edinburgh, Lothian
- University of Edinburgh — Edinburgh, Lothian, United Kingdom (Recruiting)
Study contacts
- Principal investigator: Bill Nailon — University of Edinburgh
- Study coordinator: Bill Nailon
- Email: w.nailon@ed.ac.uk
- Phone: 0044 1315371000
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.