RAPID-RT: Using Real-World Data to Rapidly Improve Radiotherapy Practice
Written by Dr Katie Lowles, Communications Officer at the MCRC
Real-World Data to Complement Clinical Trials
Clinical trials have long been regarded as the gold standard for generating evidence on new drugs, therapies, and treatments. To ensure safety and reliability, they follow stringent regulatory protocols and often involve patient participants from multiple medical centres. As a result, they are often expensive and lengthy processes, with findings typically taking several years to influence clinical practice. Crucially, certain patient demographics remain underrepresented in clinical trials, which can limit how well results reflect real-world outcomes.
Instead of relying on clinical trials, updates to routine care are often made through clinical decisions without formal trial evaluation where it appears clear that the new techniques should benefit patients. RAPID-RT is a research programme co-led by Prof Corinne Faivre-Finn and Dr Gareth Price, investigating an alternative approach to a clinical trial to see how such updates to radiotherapy (RT) practice can rapidly and safely improve patient care.
RAPID-RT uses real-world data (RWD), rather than data collected in the strictly controlled clinical trial environment, to provide broader insights into treatment effectiveness and reflect a more diverse patient population. By generating evidence as part of normal care, this approach aims to enable care teams to iteratively refine new techniques to meet the needs of their patient populations.
After 20 years of experience in randomised clinical trials, I am delighted to be involved in research that is truly inclusive and representative of the patients we treat every day. This approach not only better reflects real-world care but also allows us to generate meaningful results much faster
Professor Corinne Faivre-Finn
Professor of Thoracic Radiation Oncology, The University of Manchester, and Honorary Consultant Clinical Oncologist, The Christie
Clinical Focus: Lung Cancer and Cardiac Toxicity
RAPID-RT is a research programme with both methodological and clinical components. It uses an important clinical exemplar – the delivery of RT for lung cancer – to test a new approach to improving RT through the use of RWD and iterative refinement.
A key challenge in radiotherapy planning is delivering enough dose to the tumour while protecting nearby healthy organs. In lung cancer treatment, the heart often receives radiation, and growing evidence links this to worse patient outcomes.
RAPID-RT aims to improve radiotherapy for lung cancer patients by reducing heart damage, using a new approach that avoids radiation to a specific heart region called the Cardiac Avoidance Area (CAA). The CAA was identified by the research team in Manchester using an image-based data mining (IBDM) technique to identify the heart region where radiation dose has the strongest link to survival.
The Manchester Solution – An Interdisciplinary Approach
RAPID-RT Study Design
Following the recommendation of a citizens’ jury (see Appendix 1 for definition), RAPID-RT uses an informed opt-out consent approach to support broad and inclusive participation. Patients receive information about the study during consultation, including the option to watch a short video (see below) approved by a patient advisory group, which explains what RAPID-RT is and how their data will be used.
The study also employs broad inclusion criteria, with no exclusion criteria relating to patient comorbidities, age or performance status.
To further ensure that the study design was appropriate for the patient population, RAPID-RT also includes two patient co-applicants, both of whom have lived experience of cancer treatment. Involving patient co-applicants from the grant application stage provides an invaluable patient voice to researchers.
Clinical implementation of the new CAA
RT treatment plans are tailored to each patient, with patients using CT scans on which the cancer and nearby organs are outlined. A dose limit is applied to the CAA on these scans to protect the most radiation-sensitive heart areas. Because the new CAA is complex and time consuming to define, computational scientists and medical physicists developed an in-house AI tool to define the CAA region. The clinical team then reviews each treatment plan to ensure existing dose limits are met before patients receive their treatment. The first CAA dose limit was introduced in spring 2023. As of spring 2025, more than 1,000 patients have been treated using the RAPID-RT methodology.
My own experiences with radiotherapy, combined with my background in science and teaching mean that I have a lot to contribute to the RAPID-RT project. I am an advocate for patients going through cancer treatment - providing a patient voice to researchers and helping to ensure scientific language is clear and accessible for patients."
Mr Brian Turner
RAPID-RT co-applicant
RAPID-RT’s Dual Focus: Methodology and Outcomes
- RAPID-RT Methodological Hypothesis: “RWD can provide rapid evidence of clinical impact of changing radiotherapy care where randomised trials will not be used”
- RAPID-RT Clinical Hypothesis: “Introducing a new dose limit for the CAA will improve overall survival of lung cancer patients treated with curative intent radiotherapy”
The Rapid Learning Study Cycle
RAPID-RT follows a rapid learning framework in which changes to care are iteratively evaluated and refined in a series of learning cycles. Each cycle is composed of the steps below:
Treatment Change: introduce change in care – e.g. the new dose limit to the CAA
Evaluation: use automatically collected RWD to determine the impact of the new technique on survival and toxicity
Refinement: use results to decide if and how the change needs to be refined – e.g. an altered dose limit for the next cycle
While RAPID-RT uses the clinical exemplar of the introduction of a new cardiac dose limit in lung cancer to develop and demonstrate the new methodology, it is hoped the methodological approach will be extended to other areas of clinical practice.
Outcomes: Methodological Hypothesis
The study and its informed opt-out consent approach are highly acceptable to patients, with only 1 patient from >1,000 choosing not to participate. Thanks to this consent model and the absence of strict eligibility criteria, RAPID-RT has recruited an average of 40 patients per month at a single centre since its beginning in early 2023, an enrolment rate rarely seen in conventional oncology trials. The study’s high level of inclusivity enables the collection of large volumes of data, which both strengthens the generalisability of the evidence to a broad patient population and drives refinement of the technique in the next rapid learning cycle.
High-quality data is essential for RWD studies and rapid-learning approaches, relying on electronic records that capture structured data suitable for computer analysis. Data quality also depends on active engagement and collaboration with clinical teams, who must ensure accurate data entry. The RAPID-RT study had an average data absence of only 6%, likely because direct care teams know and understand how the data they enter into the electronic record supports research such as RAPID-RT.
It's exciting to see how routinely collected information about patients' cancer journeys can help provide valuable evidence about how care can be improved for all our patients.
Dr Gareth Price
Senior Lecturer in Cancer Digital Sciences and Machine Learning at The University of Manchester
Outcomes: Clinical Hypothesis
Early clinical results, presented earlier this year at ESTRO 2025, show that the new CAA limit has a moderate probability of providing a survival benefit for lung cancer patients, with early findings suggesting an average increase of approximately 4% in 12-month survival probability. These probability estimates are derived from Kaplan–Meier survival curves, which illustrate the likelihood of survival over time. In simpler terms, about 4 more patients out of every 100 are still alive one year after treatment compared to before the CAA limit was introduced. Further follow-up and patient accrual are expected to reduce the uncertainty in this estimate.
The future of RAPID-RT
Currently, RAPID-RT is a single centre study; future research will explore expansion into the multi-centre setting – an important step for evaluating changes in care for rarer cancers with smaller patient populations.
The next phase of the project is about creating clear, practical guidelines so that others can apply the RAPID-RT approach in different cancer care settings. We don’t want researchers reinventing the wheel when it comes to improving cancer treatment; instead, we want them to build on what we have learned from RAPID-RT so that we can make faster progress together.
Mr Brian Turner
RAPID-RT co-applicant
Having already yielded promising early results, RAPID-RT is pioneering a new way of complementing conventional clinical trial evidence by driving inclusive, fast and safe change in NHS clinics. As the study continues to recruit patients, additional outcomes, including toxicity and patient quality of life, will offer a fuller picture of its clinical impact.
Appendix 1: A citizens’ jury is a deliberative tool used to gather public input and make recommendations on complex and often ethically sensitive issues. To ensure diverse perspectives are considered, the jury is composed of individuals representing a broad demographic cross-section. For the RAPID-RT trial, a jury of 24 members met to decide on an appropriate patient consent model for the use of patient data for research purposes in this specific study. Jurors decided on an informed opt-out approach. They also decided that patients should be introduced to the study via simple information sheets during a meeting with a clinician.
This project is funded by the National Institute for Health and Care Research (NIHR) under its Programme Grants for Applied Research (PGfAR) (Grant Reference Number NIHR202024). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.