Discussion
cancers, tumor, cancer death, adenocarcinoma, pancreatic head cancer
CANCERS, TUMOR, ADENOCARCINOMA, LYMPH NODE METASTASIS, LIVER METASTASIS, PANCREATIC NEUROENDOCRINE NEOPLASM
PC is one of the most lethal of all cancers with high mortality, which is the seventh leading cause of cancer death worldwide (Sung et al. In our study, a total of six clinicopathological factors were considered as risk factors associated with LNM in PC patients, including age at diagnosis, grade, histology, T-stage, primary site, and race, which was largely consistent with previous analyses (Huang et al. Various studies demonstrated that race was related to lymph node metastasis and prognosis (Oweira et al. The correlation between grade and LNM in PC patients has been revealed in previous studies widely. Harimoto Norifumi et al. shows that lymph node metastasis was significantly associated with higher tumor grade in pancreatic neuroendocrine neoplasm (Harimoto et al. The histological type is commonly considered an important predictor of the prognosis in PC patients. Bi-Yang Cao et al. found that adenocarcinoma was the independently associated risk factor for poor prognosis in patients with liver metastasis in PC patients (Cao et al. The nomogram for evaluating the risk of LNM in PC patients was developed by easily available clinicopathological factors, including age at diagnosis, race, grade, histology, T-stage, and tumor location. The AUC and the calibration curves demonstrated excellent discrimination and consistency of this nomogram model. The risk of LNM in PC patients could be conveniently and accurately calculated by those accessible variables. Furthermore, DCA curves were utilized to estimate the clinical utility, which shows good net benefit. In summary, the risk of LNM in preoperative PC patients can be easily and accurately predicted by the newly established nomogram model.Although the nomogram model had good accuracy for predicting the risk of LNM in PC patients, there are several limitations to this study. First of all, the selection bias could not be avoided due to the nature of retrospective analyses. For example, patients with missing data were excluded from our study, which may cause selection bias. Secondly, variables such as age, tumor size, leucocyte, albumin, and lymphocytes/monocytes have been identified as independent predictors of LNM in pancreatic head cancer (Guo et al. 