1325P TRIDENT: Machine learning (ML) multimodal signatures to identify patients that would benefit most from tremelimumab (T) addition to durvalumab (D) + chemotherapy (CT) with data from the POSEIDON trial
Year: 2024
Type: article
Source: Annals of Oncology
Authors: F. Skoulidis, S. Jabbour, E.B. Garon, P. Iyengar, G. Scagliotti, L. Ferrer, G. Etchepare, O. Gallinato, J. Faure, P. Bernard, T. Colin, P. Menu, Y. Lin, L. Cai, J. Faria, A. Remorino, L. Luciani-Silverman, K.P. Miller, D. Dellamonica, Y. Zhang
Institutions: The University of Texas MD Anderson Cancer Center, Rutgers Cancer Institute, University of California, Los Angeles, Memorial Sloan Kettering Cancer Center, AstraZeneca (Italy), Sophia Genetics (France), Sophia Genetics (Switzerland), AstraZeneca (United States), AstraZeneca (United Kingdom), AstraZeneca (Spain), AstraZeneca (Switzerland)
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4402558381