Head and Neck Sarcoma Assessor (HaNSA) for treatment decisions using real-world data
We present the largest Asian HNS cohort, with diverse subtypes and disease extent. Our analysis highlights poor outcomes from a higher incidence of radiotherapy-associated disease, showing the challenging landscape of HNS in Asia. Through our prognostic calculator, we demonstrate how meaningfully curated real-world data in a rare disease entity can be used for the prediction of OS in individual patients with specific treatment approaches.
Authors
- Janice Jia Ni Goh (ORCID: https://orcid.org/0009-0005-0203-5949)
- A. Sairi
- W.L. Goh
- Chun En Yau (ORCID: https://orcid.org/0000-0002-5844-8962)
- Xing Yi Woo (ORCID: https://orcid.org/0000-0002-5980-4383)
- Whee Sze Ong (ORCID: https://orcid.org/0000-0002-3531-6182)
- Chen Ee Low (ORCID: https://orcid.org/0000-0002-8652-0984)
- Mohamed Mahtar (ORCID: https://orcid.org/0000-0002-6011-059X)
- N.F. Mohamed Noor
- Ru Xin Wong
- Valerie Shiwen Yang (ORCID: https://orcid.org/0000-0002-8844-9421)
- Morgan See (ORCID: https://orcid.org/0009-0009-7932-3331)
- J.T. Suha
Institutions
- Agency for Science, Technology and Research (SG)
- National University of Singapore (SG)
- Nanyang Technological University (SG)
- Duke-NUS Medical School (SG)
- National Cancer Centre Singapore (SG)
- Institute of Molecular and Cell Biology (SG)
Publication Details
- Journal
- ESMO Real World Data and Digital Oncology
- Published
- 2024-09-01
- DOI
- https://doi.org/10.1016/j.esmorw.2024.100069
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00