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胰腺神经内分泌肿瘤预后的模式和预测因素:世上没有完全相同的两片树叶?

Patterns and predictors of pancreatic neuroendocrine tumor prognosis: Are no two leaves alike?

机构信息

Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, 20032, PR China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, PR China; Shanghai Pancreatic Cancer Institute, Shanghai, 200032, PR China; Pancreatic Cancer Institute, Fudan University, Shanghai, 200032, PR China.

Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, 20032, PR China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, PR China; Shanghai Pancreatic Cancer Institute, Shanghai, 200032, PR China; Pancreatic Cancer Institute, Fudan University, Shanghai, 200032, PR China.

出版信息

Crit Rev Oncol Hematol. 2021 Nov;167:103493. doi: 10.1016/j.critrevonc.2021.103493. Epub 2021 Oct 12.

Abstract

Pancreatic neuroendocrine tumors (PanNETs) are heterogeneous; thus, individual prognostic prediction is important. Clinicopathological features, like TNM stage, grade, and differentiation, are independent clinical predictors. However, single predictors are insufficient, as patients sharing similar clinicopathological features usually show distinct prognoses. Accordingly, novel nomograms and risk stratifications have been developed for more accurate PanNET prognostic prediction. Moreover, the exploration of molecular mechanisms has identified novel prognostic predictors for PanNET. Multi-analyte assays of molecular biomarkers provide a deeper understanding of PanNET features; however, the priority, and the optimal combination of classic and novel predictors for PanNET prognosis prediction remain unclear. In this review, we summarized the patterns and predictors of PanNET prognosis and discussed their clinical utility; we emphasized that PanNET at different stages have different superior predictor, and that multi-analyte assays are more sensitive than mono-analyte biomarkers. Therefore, combined biomarkers improve the accuracy of surveillance and optimize decision-making in clinical practice.

摘要

胰腺神经内分泌肿瘤(PanNETs)具有异质性,因此个体预后预测很重要。临床病理特征,如 TNM 分期、分级和分化,是独立的临床预测因素。然而,单一的预测因素是不够的,因为具有相似临床病理特征的患者通常具有不同的预后。因此,为了更准确地预测 PanNET 的预后,已经开发了新的列线图和风险分层。此外,对分子机制的探索也确定了 PanNET 的新预后预测因子。对分子生物标志物的多分析物检测提供了对 PanNET 特征的更深入了解;然而,对于 PanNET 预后预测的经典和新型预测因子的优先级和最佳组合仍不清楚。在这篇综述中,我们总结了 PanNET 预后的模式和预测因子,并讨论了它们的临床应用;我们强调,不同阶段的 PanNET 具有不同的优势预测因子,多分析物检测比单分析物生物标志物更敏感。因此,联合生物标志物提高了监测的准确性,并优化了临床实践中的决策。

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