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胰腺癌监测:携带种系CDKN2A致病变异个体的风险分层

Pancreatic cancer surveillance: Risk stratification of individuals with a germline CDKN2A pathogenic variant.

作者信息

Klatte Derk C F, Meziani Jihane, Cahen Djuna L, van Diepen Merel, Bruno Marco J, van Leerdam Monique E

机构信息

Department of Gastroenterology and Hepatology, Leiden University Medical Center, Leiden, The Netherlands.

Department of Gastroenterology and Hepatology, Erasmus Medical Center, Rotterdam, The Netherlands.

出版信息

United European Gastroenterol J. 2024 Dec;12(10):1399-1403. doi: 10.1002/ueg2.12662. Epub 2024 Nov 7.

Abstract

BACKGROUND

Individuals carrying a germline CDKN2A pathogenic variant (PV) are at a high risk of developing pancreatic ductal adenocarcinoma. Risk stratification could allow tailored surveillance.

OBJECTIVE

To develop a Fine-Gray prediction model for the risk of PDAC in carriers of a CDKN2A PV.

METHODS

Data from two large Dutch pancreatic cancer surveillance programs were used. A limited set of predictor variables were selected bsased on previous literature and the clinical expertise of the study group.

RESULTS

A total of 506 CDKN2A PV carriers were included, among whom we showed a substantial lifetime risk of PDAC (23%). The model identifies having a first-degree relative with PDAC (B = 0.7256) and a history of smoking (B = 0.4776) as significant risk factors. However, the model shows limited discrimination (c-statistic 0.64) and calibration.

CONCLUSION

Our study highlights the high lifetime risk of PDAC in carriers of a CDKN2A PV. While identifying significant risk factors such as family history of PDAC and smoking, our prediction model shows limited precision, highlighting the need for additional factors such as biomarkers to improve its clinical utility for tailored surveillance of high-risk individuals.

摘要

背景

携带种系CDKN2A致病变异(PV)的个体患胰腺导管腺癌的风险很高。风险分层有助于进行针对性监测。

目的

为携带CDKN2A PV的个体发生胰腺导管腺癌(PDAC)的风险建立一个Fine-Gray预测模型。

方法

使用了来自两个大型荷兰胰腺癌监测项目的数据。基于先前的文献和研究组的临床专业知识,选择了一组有限的预测变量。

结果

共纳入506名携带CDKN2A PV的个体,其中我们发现其患PDAC的终生风险很高(23%)。该模型确定有PDAC一级亲属(B = 0.7256)和吸烟史(B = 0.4776)为显著风险因素。然而,该模型的区分度有限(c统计量为0.64)且校准效果不佳。

结论

我们的研究强调了携带CDKN2A PV的个体患PDAC的终生风险很高。虽然识别出了诸如PDAC家族史和吸烟等显著风险因素,但我们的预测模型精度有限,这突出表明需要生物标志物等其他因素来提高其对高危个体进行针对性监测的临床效用。

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