Explainable machine learning models based on clinical trial surrogate outcomes for predicting overall survival in head and neck cancers
The Elastic Net model effectively bridges surrogate efficacy endpoints and median OS, facilitating the interpretation of early clinical trial outcomes and assisting in the prediction of OS benefit in R/M HNSCC.
Authors
- Woochan Hwang (ORCID: https://orcid.org/0000-0002-9874-7772)
- Hyun Ae Jung (ORCID: https://orcid.org/0000-0002-1583-4142)
- Leon James Worth (ORCID: https://orcid.org/0000-0003-4304-6845)
- Jong Chul Park (ORCID: https://orcid.org/0000-0002-1052-0734)
Institutions
- Samsung Medical Center (KR)
- Massachusetts General Hospital (US)
- Kangbuk Samsung Hospital (KR)
Publication Details
- Journal
- ESMO Open
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1016/j.esmoop.2025.105754
- Primary Topic
- Lung Cancer Treatments and Mutations
- Type
- article
- Field-Weighted Citation Impact
- 0.00