Prostate CancerPROSECCANCT06714630
The PROSECCA Study, Answering New Questions in Prostate Cancer
An observational study of Prostate Cancer, run by University of Edinburgh at 1 site in United Kingdom.
Trial summary
Nearly half of all cancer patients receive radiotherapy as part of their treatment and although it is effective at destroying cancerous lesions deep within the body, this comes at the cost of damaging healthy, or normal, tissues. Read more about this study
- Who is it for?
- Any age, men only
- Conditions the study is for
- Prostate Cancer
- How many people
- 15,000 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 1 Jul 2024to 30 Sep 2028
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- Men only
- No healthy volunteers
- Child, Adult, Older adult
Study population: This study requires no new data to be acquired relying solely on data collected on previously treated prostate cancer patients.
Who may be able to join
- 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)
Who cannot join
- Incomplete course of radiotherapy
- No PSA data
- No follow-up corresponding healthcare data available
- No imaging data available
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United Kingdom1 site, 1 recruiting
- Recruiting
University of Edinburgh
Edinburgh, Lothian, EH4 2XU
Bill Nailon, 00441315371000 ext. 3560, w.nailon@ed.ac.uk
Dora Meikle, 00441316518706, dora.meikle@ed.ac.uk
About this study
Official title: Improving Radiotherapy in PROState Cancer Using EleCtronic Population-based healthCAre Data: The PROSECCA Study, Answering New Questions in Prostate Cancer
Nearly half of all cancer patients receive radiotherapy as part of their treatment and although it is effective at destroying cancerous lesions deep within the body, this comes at the cost of damaging healthy, or normal, tissues. With 50% of cancer patients surviving for 10 years or more, these patients can be left with life-changing side effects from their radiotherapy. It is clear that more must be done to limit damage to normal healthy tissue without compromising annihilation of the tumour and curing patients. The key to this is personalising an individual's radiotherapy treatment, in other words rather than assuming that all tumours respond similarly to radiotherapy, the treatment is optimised for an individual. To date, approaches to do this have been restricted to small numbers of carefully selected patients, are inordinately expensive, and not suitable for rolling out into everyday practice across the NHS. There is however another way, namely using Artificial Intelligence (AI) combined with an individual's healthcare record. By linking together large numbers of healthcare records at a national level, combined with the power of AI, the PROSECCA project will transform radiotherapy and cancer care.
Read the detailed description
As an example of how this technology is beginning to emerge, proof of concept data from the team has shown that using AI it is possible to identify patients at increased risk of damage from radiotherapy long before they receive any radiation as part of their treatment. However, to move these AI-based approaches from the research domain into the clinic requires significant effort, which is the aim of PROSECCA study.
The project will use AI to analyse healthcare records from up to 15,000 prostate cancer patients who underwent radiotherapy in Scotland. Through linkage of data obtained specifically for radiotherapy and data held within each patient's unique healthcare history it will be possible to establish new relationships between a patient's medical history and how well a patient responds to radiotherapy. By establishing what factors or information in a patient's complex healthcare record indicate that an individual may have a poor response to treatment, or an increased risk of side effects from radiation, it will be possible to identify these patients earlier than is currently possible and adapt treatment accordingly. Furthermore, identifying these important factors would improve radiotherapy treatment for prostate cancer patients in the future.
- Conditions
- Prostate Cancer
- Keywords
- Artificial Intelligence, Radiotherapy reactions, clinical decisions, predict outcomes, Patient individualised response, Machine Learning, AI, Personalized Radiotherapy, Radiotherapy Adaptation
- Medical subject headings
- Prostatic Neoplasms
What is being measured
The primary outcome is the main question the study is designed to answer.
PSA relapse free survival
PSA relapse free survival will be measured from the date of treatment. This information will be obtained from historical patient records.
The expected number of events in this category was calculated using the following approach.
5 year endpoint, 10% event rate based on Conventional or hypofractionated high dose intensity modulated radiotherapy for prostate cancer (CHHIP) trial Data up to 2015 resulting in sample size of 11,250 (75% of 15,000) Total Events = 1125
Measured: Plus/minus 10 years from date of radiotherapy treatment
Overall Survival
Overall survival will be measured from the date of treatment. This information will be obtained from historical patient records.
The expected number of events in this category was calculated using the following approach.
10 year endpoint, 29% event rate based on RT01 radiotherapy trial Data up to 2010 resulting in sample size of 7,500 (50% of 15,000) Total Events = 2175
Measured: Plus/minus 10 years from date of radiotherapy treatment
Radiotherapy Toxicity
Radiotherapy Toxicity was estimated based on the cohort toxicity reported in the CHHIP trial. The same estimates were applied to this cohort with the expected number of events as follows.
Note that a higher attrition rate is expected for this endpoint, 60% of 15,000=10,000 5 year endpoint, 12% event rate for Grade 2+ toxicity based on CHHIP trial Total Events = 900
Measured: Plus/minus 10 years from date of radiotherapy treatment
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted3 Dec 2024
- Study start1 Jul 2024
- Primary completion30 Sep 2027 (estimated)
- Study completion30 Sep 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Prostate CancerStudies of the same condition, open and under way.
- More trials run by University of EdinburghThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 15,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Edinburgh
- Sponsor type
- University, hospital or other
- Collaborators
- NHS Greater Glasgow and Clyde, NHS Grampian, NHS Highland, NHS Tayside, University of Glasgow, University of Lyon, NHS Lothian, NHS Research Scotland, Public Health Scotland, Prostate Cancer UK, Movember Foundation
- Responsible party
- Sponsor
- Investigators
- Bill Nailon, Principal investigator, University of EdinburghDuncan McLaren, Principal investigator, University of Edinburgh
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06714630
- Sponsor's protocol ID
- 2022/0221
- Acronym
- PROSECCA
- Status last verified
- Aug 2026
- First submitted
- 13 Aug 2024
- Last updated
- 26 Aug 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Nailon WH, Noble DJ, Harrison E, Yang Z, Elliot S, MacNair A, Beckett G, Hallam A, Sheikh A, Mills N, Halliday R, Morrison D, Chalmers A, Cameron D, Gourley C, Hall P, Lilley C, Carruthers LJ, Trainer M, Burns D, Dee F, Andiappa S, Lonsdale A, Couper M, Farnan K, McLellan J, Miller A, Ogg J, Moses J, Colligan S, MacDonald G, McPhail N, Niblock P, MacLeod N, Davies ME, Laurenson DI, Hopgood JR, Boyle D, Paterson C, Grose D, Phillips I, Harrow S, Berger T, Shelley LEA, Sanders I, Henderson S, Duffton A, Mitchell J, Rutherford A, McLaren DB. Protocol for the PROSECCA study: a new approach for predicting radiotherapy outcome using artificial intelligence and electronic population-based healthcare data. BMJ Open. 2026 Feb 2;16(2):e104408. doi: 10.1136/bmjopen-2025-104408.
PubMed 41628931
Study at a glance
From the registry record, last updated by the sponsor on 26 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Improving Radiotherapy in PROState Cancer Using EleCtronic Population-based healthCAre Data: The PROSECCA Study, Answering New Questions in Prostate Cancer
- ClinicalTrials.gov ID
- NCT06714630
- Acronym / sponsor ID
- PROSECCA / 2022/0221
- Conditions
- Prostate Cancer
- Keywords
- Artificial Intelligence, Radiotherapy reactions, clinical decisions, predict outcomes, Patient individualised response, Machine Learning, AI, Personalized Radiotherapy
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 15,000 participants (estimated)
- Lead sponsor
- University of EdinburghUniversity, hospital or other
- Collaborators
- NHS Greater Glasgow and Clyde, NHS Grampian, NHS Highland, NHS Tayside, University of Glasgow, University of Lyon, NHS Lothian, NHS Research Scotland, Public Health Scotland, Prostate Cancer UK, Movember Foundation
- Study start
- 1 Jul 2024 (actual)
- Primary completion
- 30 Sep 2027 (estimated)
- Study completion
- 30 Sep 2028 (estimated)
- First posted
- 3 Dec 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Nearly half of all cancer patients receive radiotherapy as part of their treatment and although it is effective at destroying cancerous lesions deep within the body, this comes at the cost of damaging healthy, or normal, tissues. With 50% of cancer patients surviving for 10 years or more, these patients can be left with life-changing side effects from their radiotherapy. It is clear that more must be done to limit damage to normal healthy tissue without compromising annihilation of the tumour and curing patients. The key to this is personalising an individual's radiotherapy treatment, in other words rather than assuming that all tumours respond similarly to radiotherapy, the treatment is optimised for an individual. To date, approaches to do this have been restricted to small numbers of carefully selected patients, are inordinately expensive, and not suitable for rolling out into everyday practice across the NHS. There is however another way, namely using Artificial Intelligence (AI) combined with an individual's healthcare record. By linking together large numbers of healthcare records at a national level, combined with the power of AI, the PROSECCA project will transform radiotherapy and cancer care.
Detailed description
As an example of how this technology is beginning to emerge, proof of concept data from the team has shown that using AI it is possible to identify patients at increased risk of damage from radiotherapy long before they receive any radiation as part of their treatment. However, to move these AI-based approaches from the research domain into the clinic requires significant effort, which is the aim of PROSECCA study.
The project will use AI to analyse healthcare records from up to 15,000 prostate cancer patients who underwent radiotherapy in Scotland. Through linkage of data obtained specifically for radiotherapy and data held within each patient's unique healthcare history it will be possible to establish new relationships between a patient's medical history and how well a patient responds to radiotherapy. By establishing what factors or information in a patient's complex healthcare record indicate that an individual may have a poor response to treatment, or an increased risk of side effects from radiation, it will be possible to identify these patients earlier than is currently possible and adapt treatment accordingly. Furthermore, identifying these important factors would improve radiotherapy treatment for prostate cancer patients in the future.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
Who may qualify
- Sex
- Male only
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- This study requires no new data to be acquired relying solely on data collected on previously treated prostate cancer patients.
Key inclusion criteria (7 listed)
- 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
Key exclusion criteria (4 listed)
- Incomplete course of radiotherapy
- No PSA data
- No follow-up corresponding healthcare data available
- No imaging data available
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
PSA relapse free survival
Time frame: Plus/minus 10 years from date of radiotherapy treatment
PSA relapse free survival will be measured from the date of treatment. This information will be obtained from historical patient records. The expected number of events in this category was calculated using the following approach. 5 year endpoint, 10% event rate based on Conventional or hypofractionated high dose intensity modulated radiotherapy for prostate cancer (CHHIP) trial Data up to 2015 resulting in sample size of 11,250 (75% of 15,000) Total Events = 1125
Overall Survival
Time frame: Plus/minus 10 years from date of radiotherapy treatment
Overall survival will be measured from the date of treatment. This information will be obtained from historical patient records. The expected number of events in this category was calculated using the following approach. 10 year endpoint, 29% event rate based on RT01 radiotherapy trial Data up to 2010 resulting in sample size of 7,500 (50% of 15,000) Total Events = 2175
Radiotherapy Toxicity
Time frame: Plus/minus 10 years from date of radiotherapy treatment
Radiotherapy Toxicity was estimated based on the cohort toxicity reported in the CHHIP trial. The same estimates were applied to this cohort with the expected number of events as follows. Note that a higher attrition rate is expected for this endpoint, 60% of 15,000=10,000 5 year endpoint, 12% event rate for Grade 2+ toxicity based on CHHIP trial Total Events = 900
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Aug 2026.
- Derived from this study: PubMed 41628931Nailon WH, Noble DJ, Harrison E, Yang Z, Elliot S, MacNair A, Beckett G, Hallam A, Sheikh A, Mills N, Halliday R, Morrison D, Chalmers A, Cameron D, Gourley C, Hall P, Lilley C, Carruthers LJ, Trainer M, Burns D, Dee F, Andiappa S, Lonsdale A, Couper M, Farnan K, McLellan J, Miller A, Ogg J, Moses J, Colligan S, MacDonald G, McPhail N, Niblock P, MacLeod N, Davies ME, Laurenson DI, Hopgood JR, Boyle D, Paterson C, Grose D, Phillips I, Harrow S, Berger T, Shelley LEA, Sanders I, Henderson S, Duffton A, Mitchell J, Rutherford A, McLaren DB. Protocol for the PROSECCA study: a new approach for predicting radiotherapy outcome using artificial intelligence and electronic population-based healthcare data. BMJ Open. 2026 Feb 2;16(2):e104408. doi: 10.1136/bmjopen-2025-104408.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Bill Nailon principal investigator
University of Edinburgh
Duncan McLaren principal investigator
University of Edinburgh
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Prostate Cancer, run by University of Edinburgh at 1 site in United Kingdom.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 7 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 26 Aug 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United Kingdom. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Bill Nailon (0044 1315371000 ext. 3560, w.nailon@ed.ac.uk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
PSA relapse free survival (time frame: Plus/minus 10 years from date of radiotherapy treatment). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06714630, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 26 Aug 2026.