Published on in Vol 12 (2023)
This is a member publication of University College London (Jisc)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/46335, first published
.
Journals
- Permuth J, Park M, Chen D, Basinski T, Powers B, Gwede C, Dezsi K, Gomez M, Vyas S, Biachi T, Cortizas E, Crowder S, Genilo-Delgado M, Green B, Greene A, Gregg C, Hoffe S, Jiang K, Kim B, Vasudevan V, Garcialopez De Llano J, Menon A, Mo Q, MorenoUrazan L, Mok S, Parker N, Rajasekhara S, Rasool G, Sinnamon A, Sparks L, Stewart P, Tardif K, Tassielli A, Teer J, Tran D, Turner K, Vadaparampil S, Whelan C, Douglas W, Velanovich V, Karachristos A, Legaspi A, Meredith K, Molina-Vega M, Huguet K, Arnoletti J, Bloomston M, Trevino J, Merchant N, Pimiento J, Hodul P, Malafa M, Fleming J, Judge S, Jeong D, Judge A. Leveraging real-world data to predict cancer cachexia stage, quality of life, and survival in a racially and ethnically diverse multi-institutional cohort of treatment-naïve patients with pancreatic ductal adenocarcinoma. Frontiers in Oncology 2024;14 View