The value of systemic inflammatory markers in identifying malignancy in mucinous pancreatic cystic neoplasms

Clinical and Molecular Attributes and Evaluation of Pancreatic Cystic Neoplasm

Intraductal papillary mucinous neoplasms (IPMNs) and mucinous cystic neoplasms (MCNs) are all considered "Pancreatic cystic neoplasms (PCNs)" and show a varying risk of developing into pancreatic ductal adenocarcinoma (PDAC). These lesions display different molecular characteristics, mutations, and clinical manifestations. A lack of detailed understanding of PCN subtype characteristics and their molecular mechanisms limits the development of efficient diagnostic tools and therapeutic strategies for these lesions. Proper in vivo mouse models that mimic human PCNs are also needed to study the molecular mechanisms and for therapeutic testing. A comprehensive understanding of the current status of PCN biology, mechanisms, current diagnostic methods, and therapies will help in the early detection and proper management of patients with these lesions and PDAC. This review aims to describe all these aspects of PCNs, specifically IPMNs, by describing the future perspectives.

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

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.

The Value of Serum Tumor Markers and Blood Inflammation Markers in Differentiating Pancreatic Serous Cystic Neoplasms and Pancreatic Mucinous Cystic Neoplasms

Although many studies have emphasized the prognostic and diagnostic value of tumor markers and various inflammation-related markers, their clinical significance in differentiating benign and malignant pancreatic cystic neoplasms (PCNs) remains to be clarified. The present study explored the value of serum tumor markers and inflammation-related biomarkers in the differentiation of pancreatic serous cystic neoplasms (SCNs) and pancreatic mucinous cystic neoplasms (MCNs). A total of 79 patients with PCNs were included in this study, including 35 patients with SCNs and 44 patients with MCNs. Comparison of baseline data with preoperative results of serum tumor markers and associated inflammatory markers revealed significant differences in carbohydrate antigen 199 (CA199) and “lymphocyte × ALB” (LA) between the two groups (p = 0.0023, p = 0.0149, respectively). Univariate and multivariate regression analyses showed that an increase in CA199 and a decrease in LA were relevant risk factors for MCNs. Finally, the receiver operating characteristic (ROC) curve was generated, and the area under the ROC curve (AUC) was calculated to evaluate the prediction efficiency of each indicator. The results showed that CA199 and LA had good differential diagnostic efficacy for SCNs and MCNs. This is the first to report to demonstrate that LA can be used for the differential diagnosis of SNCs and MCNs.

Molecular Diagnosis of Cystic Neoplasms of the Pancreas: a Review

BACKGROUND

The prevalence of incidental pancreatic cystic neoplasms (PCNs) has increased dramatically with advancements in cross-sectional imaging. Diagnostic imaging is limited in differentiating between benign and malignant PCNs. The aim of this review is to provide an overview of biomarkers that can be used to distinguish PCNs.

METHODS

A review of the literature on molecular diagnosis of cystic neoplasms of the pancreas was performed.

RESULTS

Pancreatic cysts can be categorized into inflammatory and non-inflammatory lesions. Inflammatory cysts include pancreatic pseudocysts. Noninflammatory lesions include both mucinous and non-mucinous lesions. Mucinous lesions include intraductal papillary mucinous neoplasm (IPMN) and mucinous cystic neoplasm. Non-mucinous lesions include serous cystadenoma and solid-pseudopapillary tumor of the pancreas. Imaging, cyst aspiration, and histologic findings, as well as carcinoembryonic antigen and amylase are commonly used to distinguish between cyst types. However, molecular techniques to detect differences in genetic mutations, protein expression, glycoproteomics, and metabolomic profiling are important developments in distinguishing between cyst types.

DISCUSSION

Nomograms incorporating common clinical, laboratory, and imaging findings have been developed in a better effort to predict malignant IPMN. The incorporation of top molecular biomarker candidates to nomograms may improve the predictive ability of current models to more accurately diagnose malignant PCNs.

Neutrophil-to-Lymphocyte Ratio as a Predictor of Invasive Carcinoma in Patients With Intraductal Papillary Mucinous Neoplasms of the Pancreas

OBJECTIVES

Preoperative determination of the grade of dysplasia in intraductal papillary mucinous neoplasms (IPMNs) is necessary for optimal management. Previous data have suggested that serum neutrophil-to-lymphocyte ratio (NLR) can predict invasive disease in patients with IPMN.

METHODS

A prospectively maintained database was queried for consecutive patients who underwent resection of IPMN. Exclusion criteria included recent diagnosis of cancer, immunosuppression, and infection or jaundice within 1 month of operation. A complete blood count with differential within 30 days of operation was used to calculate NLR.

RESULTS

Within the study period, 446 patients underwent resection for IPMN, and 348 patients (78%) met the inclusion criteria. Low-grade dysplasia was present in 60 patients (17%), 137 patients (39%) had intermediate-grade dysplasia, 76 (22%) had high-grade dysplasia, and 75 (22%) had invasive carcinoma. A higher NLR was associated with invasive carcinoma as compared with noninvasive disease (3.00 vs 2.68, P = 0.039). There was no difference in NLR between patients with high-risk (invasive and high-grade) and low-risk (low-grade and intermediate-grade) lesions (2.80 vs 2.71, P > 0.95).

CONCLUSIONS

Neutrophil-to-lymphocyte ratio was significantly higher in patients with IPMN-associated invasive carcinoma as compared with patients with noninvasive disease; however, NLR was not helpful in differentiating between high- and low-grade lesions.