Online calculator for predicting the risk of malignancy in patients with pancreatic cystic neoplasms: A multicenter, retrospective study

Abstract

BACKGROUND Efficient and practical methods for predicting the risk of malignancy in patients with pancreatic cystic neoplasms (PCNs) are lacking. AIM To establish a nomogram-based online calculator for predicting the risk of malignancy in patients with PCNs. METHODS In this study, the clinicopathological data of target patients in three medical centers were analyzed. The independent sample t-test, Mann–Whitney U test or chi-squared test were used as appropriate for statistical analysis. After univariable and multivariable logistic regression analysis, five independent factors were screened and incorporated to develop a calculator for predicting the risk of malignancy. Finally, the concordance index (C-index), calibration, area under the curve, decision curve analysis and clinical impact curves were used to evaluate the performance of the calculator. RESULTS Enhanced mural nodules [odds ratio (OR): 4.314; 95% confidence interval (CI): 1.618–11.503, P = 0.003], tumor diameter ≥ 40 mm (OR: 3.514; 95%CI: 1.138–10.849, P = 0.029), main pancreatic duct dilatation (OR: 3.267; 95%CI: 1.230–8.678, P = 0.018), preoperative neutrophil-to-lymphocyte ratio ≥ 2.288 (OR: 2.702; 95%CI: 1.008–7.244, P = 0.048], and preoperative serum CA19-9 concentration ≥ 34 U/mL (OR: 3.267; 95%CI: 1.274–13.007, P = 0.018) were independent risk factors for a high risk of malignancy in patients with PCNs. In the training cohort, the nomogram achieved a C-index of 0.824 for predicting the risk of malignancy. The predictive ability of the model was then validated in an external cohort (C-index: 0.893). Compared with the risk factors identified in the relevant guidelines, the current model showed better predictive performance and clinical utility. CONCLUSION The calculator demonstrates optimal predictive performance for identifying the risk of malignancy, potentially yielding a personalized method for patient selection and decision-making in clinical practice.

Radiomics advances in the evaluation of pancreatic cystic neoplasms

“…The incidence of pancreatic cystic neoplasms (PCNs) is approximately 2–45 % in normal adults, and its incidence is related to the age and body mass index of subjects [ [1] , [2] , [3] ]. The most common types of PCN are serous cystic neoplasm (SCN), solid pseudopapillary neoplasm (SPN), intraductal papillary mucinous neoplasm (IPMN), and mucinous cystic neoplasm (MCN) [ 4 ].…”