The PROSECCA Study, Answering New Questions in Prostate Cancer
- Conditions
- Prostate Cancer
- Registration Number
- NCT06714630
- Lead Sponsor
- University of Edinburgh
- Brief 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. 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.
Recruitment & Eligibility
- Status
- ACTIVE_NOT_RECRUITING
- Sex
- Male
- Target Recruitment
- 15000
- 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)
- Incomplete course of radiotherapy
- No PSA data
- No follow-up corresponding healthcare data available
- No imaging data available
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method PSA relapse free survival 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 = 1125Overall Survival 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 = 2175Radiotherapy Toxicity 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
- Secondary Outcome Measures
Name Time Method
Related Research Topics
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Trial Locations
- Locations (1)
University of Edinburgh
🇬🇧Edinburgh, Lothian, United Kingdom