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Related Experiment Video

Updated: Jan 16, 2026

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RT-HaND_C: A Multi-Source, Validated Real-world Head and Neck Cancer Dataset for Research.

T Young1, H Drake2, V Butterworth1

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Clinical Oncology (Royal College of Radiologists (Great Britain))
|October 4, 2025
PubMed
Summary
This summary is machine-generated.

A new head and neck cancer (HNC) dataset, RT-HaND_C, was developed using real-world data (RWD). This comprehensive dataset reveals significant long-term weight loss in HNC patients post-radiotherapy.

Keywords:
Artificial intelligenceData miningNatural language processingReal-world data

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Area of Science:

  • Oncology
  • Data Science
  • Medical Informatics

Background:

  • Real-world data (RWD) offers valuable insights into head and neck cancer (HNC) patient outcomes, particularly for diverse and comorbid populations often excluded from clinical trials.
  • Challenges in RWD quality necessitate rigorous evaluation for reliable real-world evidence generation.
  • Developing comprehensive HNC oncology datasets is crucial for advancing research.

Purpose of the Study:

  • To develop a large-scale, high-quality HNC oncology dataset integrating multiple data sources.
  • To establish a robust evaluation framework for RWD in HNC research.
  • To assess the usability of the developed dataset by investigating long-term weight trends post-radiotherapy.

Main Methods:

  • The RT-HaND_C dataset was created by integrating structured and unstructured Electronic Health Record (EHR) data, alongside manually curated information.
  • Utilized a validated AI-driven Natural Language Processing tool for extracting unstructured EHR data.
  • Incorporated extensive demographic, disease, treatment, outcome, and radiotherapy dosimetry data from 2010-2023, with rigorous data quality assessments.

Main Results:

  • The RT-HaND_C dataset comprises 2,895 HNC patients with over 1.9 million data points and >2000 data categories.
  • Achieved >98% accuracy for most variables, with high data completeness and consistency across key categories.
  • Demonstrated statistically significant, persistent weight loss in HNC patients up to 5 years post-radiotherapy, peaking at 6 months.

Conclusions:

  • RT-HaND_C is a novel, high-quality real-world data resource with an integrated evaluation framework for HNC research.
  • The dataset facilitates multi-modal research through virtual linkage with imaging data.
  • RT-HaND_C is available for research collaborations, with ongoing efforts to enhance its completeness and incorporate prospective data.