The PROSECCA Study, Answering New Questions in Prostate Cancer (PROSECCA)

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.

Study Overview

• Status: Recruiting
• Conditions: Prostate Cancer

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 Type: Observational
• Enrollment (Estimated): 15000

Contacts and Locations

• Study Contact: Name: Bill Nailon; Phone Number: 3560 0044 1315371000; Email: w.nailon@ed.ac.uk
• Study Contact Backup: Name: Duncan McLaren; Phone Number: 0044 1316518706; Email: Duncan.McLaren@ed.ac.uk

Study Locations

• United Kingdom
  • Lothian
    • Edinburgh, Lothian, United Kingdom, EH4 2XU
      • Recruiting
      • University of Edinburgh
      • Contact: Bill Nailon; Phone Number: 3560 00441315371000; Email: w.nailon@ed.ac.uk
      • Contact: Dora Meikle; Phone Number: 00441316518706; Email: dora.meikle@ed.ac.uk

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

This study requires no new data to be acquired relying solely on data collected on previously treated prostate cancer patients.

Description

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

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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	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	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	Plus/minus 10 years from date of radiotherapy treatment

Collaborators and Investigators

• Sponsor: University of Edinburgh
• Collaborators: NHS Lothian; NHS Tayside; NHS Greater Glasgow and Clyde; NHS Grampian; University of Glasgow; University of Lyon; Prostate Cancer UK; Movember Foundation; NHS Research Scotland; NHS Highland; Public Health Scotland
• Investigators: Principal Investigator: Bill Nailon, University of Edinburgh; Principal Investigator: Duncan McLaren, University of Edinburgh

Publications and helpful links

General 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.

Study record dates

Study Major Dates

• Study Start (Actual): July 1, 2024
• Primary Completion (Estimated): September 30, 2027
• Study Completion (Estimated): September 30, 2028

Study Registration Dates

• First Submitted: August 13, 2024
• First Submitted That Met QC Criteria: November 28, 2024
• First Posted (Actual): December 3, 2024

Study Record Updates

• Last Update Posted (Actual): August 26, 2026
• Last Update Submitted That Met QC Criteria: August 25, 2026
• Last Verified: August 1, 2026

More Information

Terms related to this study

• Keywords: Artificial Intelligence; AI; Machine Learning; Radiotherapy reactions; clinical decisions; predict outcomes; Patient individualised response; Personalized Radiotherapy; Radiotherapy Adaptation
• Additional Relevant MeSH Terms: Urogenital Diseases; Genital Diseases; Genital Neoplasms, Male; Urogenital Neoplasms; Neoplasms by Site; Neoplasms; Genital Diseases, Male; Prostatic Diseases; Male Urogenital Diseases; Prostatic Neoplasms
• Other Study ID Numbers: 2022/0221

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No