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

World J Gastroenterol. 2022 Oct 7;28(37):5469-5482. doi: 10.3748/wjg.v28.i37.5469.

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.

Keywords: Calculator; Model; Nomogram; Pancreatic cystic neoplasms; Prediction; Risk of malignancy.

Publication types

  • Multicenter Study

MeSH terms

  • CA-19-9 Antigen
  • Humans
  • Nomograms
  • Pancreatic Neoplasms* / pathology
  • Retrospective Studies
  • Risk Factors

Substances

  • CA-19-9 Antigen