AI-Driven Early Detection of Cachexia in Pancreatic Cancer and Feasibility of Diet and Exercise Interventions
This observational study aims to (1) validate a multimodal artificial intelligence (AI) model for early detection of cancer-associated cachexia in pancreatic cancer patients and (2) assess the feasibility and acceptability of diet and exercise interventions for cachexia management. The study will use retrospective data from the Florida Pancreas Collaborative and prospective data from newly diagnosed patients at Moffitt Cancer Center.
• Age ≥ 18 years
• Histologically or cytologically confirmed diagnosis of pancreatic ductal adenocarcinoma (PDAC) or clinical features highly suggestive of PDAC with diagnostic confirmation anticipated during the screening or early study period.
• Presentation consistent with resectable, borderline resectable, local, or locally advanced, nonmetastatic disease
• Treatment-naive at the time of enrollment (i.e., no prior systemic therapy or radiation for pancreatic cancer)
• May or may not have had surgery
• Treatment plan likely includes systemic therapy for pancreatic cancer
• ECOG performance status 0-2
• Able to tolerate oral intake and not currently receiving enteral or parenteral nutrition
• Able to read and speak English
• Able to provide written informed consent