LAUSR

Aims This study aimed to investigate the prognostic value of clinical features for cancer-specific survival (CSS) and metastasis in patients with pancreatic mucinous cystadenocarcinoma (MCAC). We further constructed and validated an effective nomogram to predict CSS. Methods We screened patients diagnosed with pancreatic MCAC from Surveillance Epidemiology and End Results (SEER) database. Kaplan-Meier curves were used to determine the CSS time. Univariate and multivariate Cox and logistic regression analyses were conducted to identify the prognostic factors for CSS and metastasis. The nomogram was constructed to predict the prognosis of pancreatic MCAC based on the results from the multivariate analysis. We used the concordance index (C-index), the area under the curve (AUC), and the calibration plots to determine the predictive accuracy and discriminability of the nomogram. Results Multivariate Cox analysis revealed that age, primary site, grade, and radiotherapy were independent prognostic factors associated with CSS. Multivariate logistic regression analysis revealed that surgery and grade were independent risk factors associated with metastasis. The independent risk factors were included to construct a prognosis prediction model for predicting CSS in patients with pancreatic MCAC. The concordance index (C-index), receiver operating characteristic (ROC) curves, and calibration plots of the training cohort and the validation cohort showed that the nomogram had an acceptable predictive performance. Conclusion We established a nomogram that could determine the 3- and 5-year CSS, which could evaluate individual clinical outcomes and provide individualized clinical decisions.