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基于非侵入性检查变量预测胰腺导管内乳头状黏液性肿瘤患者高级别异型增生和浸润性癌的列线图

Nomogram for the Prediction of High-Grade Dysplasia and Invasive Carcinoma in Patients With Intraductal Papillary Mucinous Neoplasms of the Pancreas Based on Variables of Noninvasive Examination.

作者信息

Li Bo, Shi Xiaohan, Gao Suizhi, Shen Shuo, Bian Yun, Cao Kai, Pan Yaqi, Zhang Guoxiao, Jiang Hui, Li Gang, Guo Shiwei, Jin Gang

机构信息

Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital Affiliated to Navy Medical University, Shanghai, China.

Department of General Surgery, Beidaihe Rehabilitation and Recuperation Center of PLA, Qinhuangdao, China.

出版信息

Front Oncol. 2021 Mar 9;11:609187. doi: 10.3389/fonc.2021.609187. eCollection 2021.

Abstract

Intraductal papillary mucinous neoplasms (IPMNs) are a heterogeneous group of neoplasms and represent the most common identifiable precursor lesions of pancreatic cancer. Clinical decision-making of the risk for malignant disease, including high-grade dysplasia and invasive carcinoma, is challenging. Moreover, discordance on the indication for resection exists between the contemporary guidelines. Furthermore, most of the current nomogram models for predicting malignant disease depend on endoscopic ultrasonography to evaluate the precise size of mural nodules. Thus, this study aimed to propose a model to predict malignant disease using variables from a noninvasive examination. We evaluated patients who underwent resection of pathologically confirmed IPMNs between November 2010 and December 2018 and had preoperative clinical data available for review. Based on binary multivariable logistic regression analysis, we devised a nomogram model to predict malignant IPMNs. The area under the receiver operating characteristics curve (AUC) was used to evaluate the discrimination power of the model. Of the 333 patients who underwent resection of IPMNs, 198 (59.5%) had benign and 135 (40.5%) had malignant IPMNs. Multivariable logistic regression analysis showed that cyst size, cyst location, cyst wall enhancement, multicystic lesion, diameter of main pancreatic duct, neutrophil-to-lymphocyte ratio, serum carbohydrate antigen 19-9, and carcinoembryonic antigen were significantly associated with malignancy. The nomogram, constructed based on these variables, showed excellent discrimination power with an AUC of 0.859 (95% CI: 0.818-0.900, < 0.001). In conclusion, we have developed a nomogram consisting of a combination of cross-sectional imaging features and blood markers, variables that can readily be obtained by noninvasive examinations during the surveillance period, which can distinguish benign from malignant IPMNs. Nevertheless, external validation is warranted.

摘要

导管内乳头状黏液性肿瘤(IPMNs)是一组异质性肿瘤,是胰腺癌最常见的可识别前驱病变。对于包括高级别异型增生和浸润性癌在内的恶性疾病风险进行临床决策具有挑战性。此外,当代指南之间在手术指征方面存在不一致。此外,目前大多数用于预测恶性疾病的列线图模型依赖于内镜超声来评估壁结节的精确大小。因此,本研究旨在提出一种使用非侵入性检查变量来预测恶性疾病的模型。我们评估了2010年11月至2018年12月期间接受病理证实的IPMNs切除术且有术前临床资料可供审查的患者。基于二元多变量逻辑回归分析,我们设计了一个列线图模型来预测恶性IPMNs。采用受试者操作特征曲线(AUC)下面积来评估模型的辨别力。在333例行IPMNs切除术的患者中,198例(59.5%)为良性,135例(40.5%)为恶性IPMNs。多变量逻辑回归分析显示,囊肿大小、囊肿位置、囊肿壁强化、多囊性病变、主胰管直径、中性粒细胞与淋巴细胞比值、血清糖类抗原19-9和癌胚抗原与恶性肿瘤显著相关。基于这些变量构建的列线图显示出优异的辨别力,AUC为0.859(95%CI:0.818-0.900,<0.001)。总之,我们开发了一种由横断面成像特征和血液标志物组合而成的列线图,这些变量可在监测期间通过非侵入性检查轻松获得,能够区分良性和恶性IPMNs。然而,仍需要外部验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aeeb/7985057/01c3eaf22297/fonc-11-609187-g001.jpg

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