Using machine learning to predict side effects of radiotherapy in cancer patients
Official title: Hamlet-RT: Heuristics, Algorithms and Machine Learning: Evaluation & Testing in Radiation Therapy
Run by Cambridge University Hospitals NHS Foundation Trust · NCT04060706 · Data updated 2026-11-12
This study is trying to see if using advanced computer techniques can help predict which cancer patients might experience serious side effects from their radiotherapy treatment.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 310 (estimated) |
| Sponsor | Cambridge University Hospitals NHS Foundation Trust Academic / other |
| Drugs / interventions | radiation |
| Locations | 1 site (Cambridge, Cambridgeshire) |
| Status | Recruiting |
| Started | September 11, 2019 |
| Main results expected | January 1, 2023 |
| Study ends | January 1, 2028 |
| Registry record updated | August 2, 2021 |
| Trial ID | NCT04060706 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates include adults aged 18 and older diagnosed with primary prostate cancer, head and neck cancer, lung cancer, or brain tumors who are suitable for radical image-guided radiotherapy.
✕Probably not a fit
Patients who are not willing or able to complete the required study protocols, including web-based questionnaires, may not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
The Hamlet.rt study collects data and patient questionnaires from individuals undergoing image-guided radiotherapy with the goal of predicting the risk of significant side effects from treatment. By utilizing novel machine learning and mathematical techniques, the study aims to create a predictive model based on normal tissue dose calculations and patient characteristics. This model will be continuously updated throughout the patient's treatment journey. Additionally, the study seeks to establish a shared data resource to facilitate further research in machine learning and medical image processing for radiation therapy.
Why it matters
Potential benefit: If successful, this study could lead to personalized treatment plans that minimize side effects for cancer patients undergoing radiotherapy.
How similar studies have gone: Other studies utilizing machine learning in radiation therapy have shown promise, indicating that this approach may lead to significant advancements in patient care.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Participant is willing and able to give informed consent for participation in the study * Male or Female * Aged 18 years or older * Diagnosed with primary prostate cancer, head and neck cancer, lung cancer, or brain tumour * Treated with curative intent * Suitable for radical image guided radiotherapy * WHO ECOG performance status 0 or 1 * Expected survival of 18 months or more Exclusion Criteria: * Participant is not willing or able to complete the protocol-stated requirements of the study, e.g. accessing \& completing web-based long-term follow-up questionnaires.
Where it's running
-
Cambridge University Hospitals NHS Foundation Trust
Cambridge, Cambridgeshire, United Kingdom Recruiting
Study contacts
- Principal investigator: Raj Dr. Jena — Cambridge University Hospitals NHS Foundation Trust & the University of Cambridge
- Study coordinator: Meena Murthy
- Email: meena.murthy@addenbrookes.nhs.uk
- Phone: 01223 349707
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.