The impact of metastatic sites on survival Rates and predictors of extended survival in patients with metastatic pancreatic cancer

Background objectives: The aim of this study was to determine the role of site-specific metastatic patterns over time and assess factors associated with extended survival in metastatic PDAC. Half of all patients with pancreatic ductal adenocarcinoma (PDAC) present with metastatic disease. The site of metastasis plays a crucial role in clinical decision making due to its prognostic value. Methods: We examined 56,757 stage-IV PDAC patients from the National Cancer Database (2016-2019), categorizing them by metastatic site: multiple, liver, lung, brain, bone, carcinomatosis, or other. The sitespecific prognostic value was assessed using log-rank tests while time-varying effects were assessed by Aalen's linear hazards model. Factors associated with extended survival (>3years) were assessed with logistic regression. Results: Median overall survival (mOS) in patients with distant lymph node-only metastases (9.0 months) and lung-only metastases (8.1 months) was significantly longer than in patients with liver-only metastases (4.6 months, p < 0.001). However, after six months, the metastatic site lost prognostic value. Logistic regression identified extended survivors (3.6 %) as more likely to be younger, Hispanic, privately insured, Charlson-index <2, having received chemotherapy, or having undergone primary or distant site surgery (all p < 0.001). Conclusion: While synchronous liver metastases are associated with worse outcomes than lung-only and lymph node-only metastases, this predictive value is diminished after six months. Therefore, treatment decisions beyond this time should not primarily depend on the metastatic site. Extended survival is possible in a small subset of patients with favorable tumor biology and good conditional status, who are more likely to undergo aggressive therapies. (c) 2024 IAP and EPC. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.