简介：AbstractObjectives:To establish Nomogram to predict the overall survival (OS) rate of pancreatic cancer patients with lung metastasis by utilizing the database of the Surveillance, Epidemiology, and End Results (SEER) Program.Methods:We obtained the data of 363 pancreatic cancer patients with lung metastasis who were diagnosed between 2010 and 2016 from the SEER database. These patients were randomly divided into training (n=255) and validation (n=108) cohorts. The Cox proportional hazards regression model was performed to evaluate the prognostic effects of multiple clinicopathologic factors on OS. Significant prognostic factors were combined to build Nomogram. The predictive performance of Nomogram was evaluated via internal (training cohort data) and external validation (validation cohort data) by calculating index of concordance (C-index) and plotting area under curve (AUC) and calibration curves. All data from SEER database have been fully de-identified and may be used without further independent ethics committee approval.Results:In the training cohort, the results of Cox proportional hazards regression model showed that, tumor location, surgery, chemotherapy and other organ of metastasis were significantly associated with the survival prognosis (P <.05). These factors were used to establish Nomogram. The Nomogram showed good accuracy in predicting OS rate, with C-index of 0.727 [95%CI was (0.689, 0.764)] in internal validation and C-index of 0.738 [95%CI was (0.679, 0.796)] in external validation. All calibration curves showed excellent consistency between prediction by Nomogram and actual observation.Conclusion:Novel Nomogram for pancreatic cancer patients with lung metastasis was established to predict OS in our study. It has good prognostic significance. And it could provide the clinicians with more accurate and practical predictive tools which can quickly and accurately assess the patients’ survival prognosis individually, and make clinical suggestion for doctors in the follow-up treatment of patients.