Pancreatic cystic lesions: clinical predictors of malignancy in patients undergoing surgery

Abstract

Background: Despite advances in cross-sectional imaging and the use of molecular markers, distinguishing between benign and malignant cysts remains a clinical challenge.

Aims: To identify both preoperative clinical and cyst characteristics at the time of EUS that predict malignancy.

Methods: A retrospective analysis was performed on consecutive patients with pancreatic cysts who underwent endoscopic ultrasound (EUS) and surgical resection from May 1996 to December 2007 at a tertiary centre. Clinical history, EUS characteristics, cytology, tumour markers and surgical histology were collected. Predictors of malignancy were determined by univariate and multivariate analysis using logistic regression.

Results: A total of 153 patients underwent a EUS and subsequent surgical intervention.Of the 153 patients, 57 (37%) had a histological diagnosis of malignancy. On univariate analysis, older age (P < 0.001), male gender (P = 0.010), jaundice (P = 0.039), history of other malignancy (P = 0.036), associated mass in cyst (P = 0.004) and malignant cytology (P < 0.001) were found to be associated with malignancy. History of pancreatitis (P = 0.008) and endoscopist impression of pseudocyst (P = 0.001) were found to be associated with benign cysts. Multivariate analysis found that only older age [Odds ratio (OR), 1.04; 95% confidence interval (CI), 1.01-1.08], male gender (OR, 2.26; 95% CI, 1.08-4.73) and malignant cytology (OR, 6.60; 95% CI, 2.02-21.58) were independent predictors of malignancy.

Conclusions: Older age, male gender and malignant cytology from EUS predict malignancy at surgical resection. These characteristics may be used to estimate the probability of malignancy in a cyst and aid in management.

Conflict of interest statement

Disclosure: none

Figures

Figure 1

Probability of Malignancy. Using the odds ratio from multivariate analysis (Table 4), the probability of malignancy is plotted against age of the patient. Each curve represents a different probability curve based on the gender and the presence of malignant cytology from EUS.