Clinical data combined with radiological imaging improves the accuracy of TNM staging of pancreatic body and tail adenocarcinoma

Abstract

Purpose: Pancreatic body and tail adenocarcinoma (PBTA) remains one of the deadliest cancers, and current radiological modalities still have limitations on the staging of PBTA. Improving PBTA staging will contribute to the management of this disease. Patients and methods: Clinicopathological characteristics of 91 surgically treated PBTA patients were retrospectively retrieved. Clinical data associated with postoperative tumor staging (pTNM) were assessed using ordinal logistic regression model. Discriminant analysis was performed using function formula based on multivariate analysis results; further cross-validation was conducted by Bootstrap methods. Results: Multivariate analysis showed that carbohydrate antigen 19-9 ≥955.0 U/L, albumin, and alkaline phosphatase/total bilirubin ratio were independent factors contributing to improved accuracy of pTNM staging. Discriminant analysis exhibited better performance and showed that the probability of accurate prediction of pTNM stage was 90.6% and the probability of cross-validation was 85.9%. After excluding patients with preoperative diagnosis of stage IV disease, the probability of accurate prediction of pTNM stage was 86.1% and the probability of cross-validation was 75.0%. Conclusion: The combination of imaging and clinical data has higher accuracy in staging PBTA than radiological data alone. A model proposed in this study will improve the management of PBTA.