Multi-institutional Validation Study of Pancreatic Cyst Fluid Protein Analysis for Prediction of High-risk Intraductal Papillary Mucinous Neoplasms of the Pancreas

胰腺囊肿液蛋白分析预测胰腺高风险导管内乳头状粘液肿瘤的多机构验证研究

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作者:Mohammad A Al Efishat, Marc A Attiyeh, Anne A Eaton, Mithat Gönen, Denise Prosser, Anna E Lokshin, Carlos Fernández-Del Castillo, Keith D Lillemoe, Cristina R Ferrone, Ilaria Pergolini, Mari Mino-Kenudson, Neda Rezaee, Marco Dal Molin, Matthew J Weiss, John L Cameron, Ralph H Hruban, Michael I D'Ang

Conclusions

This multi-institutional study validated 2 CF protein marker models for preoperative identification of high-risk IPMN. When combined with a clinical nomogram, the ability to predict high-grade dysplasia was even stronger.

Methods

Clinical and radiographic data, as well as CF samples, were obtained from 149 patients who underwent resection for IPMN at 1 of 3 institutions. High-risk disease was defined as the presence of high-grade dysplasia or invasive carcinoma. Multianalyte bead array analysis (Luminex) of CF was performed for 4 protein markers that were previously associated with high-risk disease. Logistic regression models were fit on training data, with and without adjustment for a previously developed clinical nomogram and validated with an external testing set. The models incorporating clinical risk score were presented graphically as nomograms.

Objective

Preliminary work by our group suggested that proteins within the pancreatic cyst fluid (CF) may discriminate degree of IPMN dysplasia. We sought to externally validate these markers and determine whether their inclusion in a preoperative clinical nomogram could increase diagnostic accuracy. Summary background data: IPMN is the most common radiographically identifiable precursor to pancreatic cancer; however, the timing and frequency of its malignant progression are unknown, and there are currently no reliable preoperative tests that can determine the grade of dysplasia in IPMN.

Results

Within the group of 149 resected patients, 89 (60%) had low-risk disease, and 60 (40%) had high-risk disease. All 4 CF markers (MMP9, CA72-4, sFASL, and IL-4) were overexpressed in patients with high-risk IPMN (P < 0.05). Two predictive models based on preselected combinations of CF markers had concordance indices of 0.76 (Model-1) and 0.80 (Model-2). Integration of each CF marker model into a previously described clinical nomogram leads to increased discrimination compared with either the CF models or nomogram alone (c-indices of 0.84 and 0.83, respectively). Conclusions: This multi-institutional study validated 2 CF protein marker models for preoperative identification of high-risk IPMN. When combined with a clinical nomogram, the ability to predict high-grade dysplasia was even stronger.

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