Predicting Benefit of Neoadjuvant Chemotherapy and Elective Nodal Irradiation in Pancreatic Adenocarcinoma: A Supervised Machine Learning Approach
Using a machine learning approach, we define a nomogram capable of predicting treatment response to multiagent NAC followed by radiotherapy with or without ENI. Patients selected by this model had higher rates of ypN0, higher R0 resection rates, and improved OS.
Authors
- Farshid Dayyani (ORCID: https://orcid.org/0000-0002-4970-5189)
- David S. Hong (ORCID: https://orcid.org/0000-0001-8721-1609)
- Jennifer Valerin
- Zeljka Jutric (ORCID: https://orcid.org/0000-0003-1792-4376)
- David T. Imagawa
- Nicholas Peterson (ORCID: https://orcid.org/0000-0003-4157-8119)
- Garrett K. Harada (ORCID: https://orcid.org/0000-0002-7024-3783)
- Steven N. Seyedin (ORCID: https://orcid.org/0000-0002-6841-968X)
- Akul Munjal
- Jino Park (ORCID: https://orcid.org/0000-0001-5228-3880)
Institutions
- University of California, Irvine (US)
- University of California, Irvine Medical Center (US)
- UCSF Helen Diller Family Comprehensive Cancer Center (US)
Publication Details
- Journal
- Cancer Medicine
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/cam4.71447
- Primary Topic
- Pancreatic and Hepatic Oncology Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00