Risk factors, prognostic predictors, and nomograms for liver metastasis in patients with pancreatic cancer: a population-based study.

Abstract Background Liver metastasis (LM) is a significant risk predictor for poor outcomes among pancreatic cancer patients. This study aimed to investigate the risk and prognostic factors of pancreatic cancer with liver metastases (PCLM) and establish diagnostic and prognostic nomograms for these entities. Methods Between 2010 and 2015, data on individuals with primary diagnosed PC were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. To identify independent risk factors for PCLM, univariate and multivariate logistic regression analyses were used. Prognostic factors were identified using LASSO regression and multivariate Cox regression analyses. Furthermore, two nomograms for predicting the risk and prognosis of PCLM were developed. The performance of the nomogram models was evaluated using receiver operating characteristic (ROC) curves, calibration plots, decision curve analysis (DCA), and risk subgroup classification. To compare survival results between groupings, Kaplan-Meier curves were constructed. Results A total of 33459 PC patients were included in the study, with 11458 patients (34.2%) having LM at the time of diagnosis. Younger than 70 years of age, primary site in the body or tail, lymph node metastasis, neuroendocrine carcinoma, larger tumor size, and higher grade are identified as independent risk factors for LM in patients with PC. The independent factors associated with poor prognosis for PCLM patients include older than 70 years, adenocarcinoma, poor or anaplastic differentiation, lung metastases, and not receiving surgery or chemotherapy. Based on their observed analysis results of ROC, calibration, DCA, and Kaplan-Meier survival curves, two nomograms can accurately predict the occurrence and prognosis of PCLM patients. Conclusion We developed two nomograms for predicting the risk of LM among PC patients as well as the personalized prognosis for PCLM patients that may aid clinical decision-making.