Comparing clinician decisions to machine predictions in head and neck cancer treatment
Official title: A Step Towards Fully Automated Adaptive Radiotherapy in Head & Neck Cancer: A Human Versus Machine Comparison Study
Run by East and North Hertfordshire NHS Trust · NCT06035653 · Data updated 2026-05-14
This study is no longer in our active list. It may have stopped recruiting or finished. The details below are as of 2026-05-14 and are kept for reference. Check ClinicalTrials.gov for its current status, or see similar studies below.
This study looks at whether using smart software to predict treatment decisions for head and neck cancer patients is as accurate and efficient as the choices made by doctors.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 40 (estimated) |
| Sponsor | East and North Hertfordshire NHS Trust Government |
| Drugs / interventions | radiation |
| Locations | 1 site (Northwood, UK) |
| Trial ID | NCT06035653 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates are head and neck cancer patients who require new masks for radiotherapy replanning due to significant changes in their condition.
✕Probably not a fit
Patients whose primary malignancy is not of head and neck origin or those who opt out of data usage will 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
This observational study retrospectively analyzes data from head and neck cancer patients treated over a 12-month period. It compares the clinical decisions made by healthcare professionals during weekly radiotherapy meetings against the predictions generated by intelligence software. The study includes two cohorts: patients requiring new masks and replanning due to significant weight changes, and those deemed marginal who did not require total replanning. The analysis focuses on the accuracy of the software's predictions and the time efficiency of using the software compared to traditional methods.
Why it matters
Potential benefit: If successful, this study could enhance the accuracy and efficiency of radiotherapy planning for head and neck cancer patients.
How similar studies have gone: While this approach is innovative, similar studies have shown promise in utilizing machine learning for treatment planning in oncology.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * i. Head and neck cancer patients who require new mask for radiotherapy replanning will be included (Cohort A). These patients typically are ones with rapid shrinkage of the nodal disease, or whose weight change is notable (5 - 10% of baseline) in the first 2 weeks of radiotherapy ii. Patients on close observation of the head and neck multi-professional team but whose radiotherapy did no undergo total replan treatment will be included (Cohort B) Exclusion Criteria: i. Patients whose primary malignancy is not of head and neck origin ii. Patients who specifically opt against their information be used anonymously iii. Head and neck cancer patients whose radiotherapy plans did not require review in the head and neck multi-professional radiotherapy meeting iv. Patients under the age of 18
Where it's running
-
East & North Hertfordshire NHS Trust
Northwood, UK, United Kingdom Recruiting
Study contacts
- Study coordinator: Kevin Chiu
- Email: k.chiu@nhs.net
- Phone: 0203 826 2020
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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.