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肺神经内分泌肿瘤分级:循证建议。

Grading the neuroendocrine tumors of the lung: an evidence-based proposal.

机构信息

Institute of Anatomic Pathology, Università Cattolica del Sacro Cuore - Policlinico A. Gemelli, Rome, Italy Service of Biometry and Clinical Epidemiology, Research Department, IRCCS Fondazione Policlinico San Matteo, Pavia, Italy Service of Pathology, Centro Diagnostico Italiano, Milan, Italy Thoracic Unit, Department of Surgery, University of Parma, Parma, Italy Medical Oncology Unit, University Hospital of Parma, Parma, Italy Unit of Pathological Anatomy, Centre for Molecular and Translational Oncology, University Hospital, University of Parma, Parma, Italy Medical Oncology Unit of Respiratory Tract and Sarcomas, Department of Medical Oncology, European Institute of Oncology, Milan, Italy Division of Thoracic Surgery, European Institute of Oncology, Milan, Italy Department of Thoracic Surgery, Università Cattolica del Sacro Cuore - Policlinico A. Gemelli, Rome, Italy Division of Pathology, University of Turin at San Luigi Hospital, Orbassano, Torino, Italy Division of Thoracic Surgery, European Institute of Oncology, University of Milan School of Medicine, Milan, Italy Division of Pathology and Laboratory Medicine, European Institute of Oncology, Milan, Italy Department of Biomedical and Clinical Sciences 'Luigi Sacco', Università degli Studi, Milan, Italy.

出版信息

Endocr Relat Cancer. 2013 Dec 16;21(1):1-16. doi: 10.1530/ERC-13-0246. Print 2014 Feb.

Abstract

Lung neuroendocrine tumors are catalogued in four categories by the World Health Organization (WHO 2004) classification. Its reproducibility and prognostic efficacy was disputed. The WHO 2010 classification of digestive neuroendocrine neoplasms is based on Ki67 proliferation assessment and proved prognostically effective. This study aims at comparing these two classifications and at defining a prognostic grading system for lung neuroendocrine tumors. The study included 399 patients who underwent surgery and with at least 1 year follow-up between 1989 and 2011. Data on 21 variables were collected, and performance of grading systems and their components was compared by Cox regression and multivariable analyses. All statistical tests were two-sided. At Cox analysis, WHO 2004 stratified patients into three major groups with statistically significant survival difference (typical carcinoid vs atypical carcinoid (AC), P=0.021; AC vs large-cell/small-cell lung neuroendocrine carcinomas, P<0.001). Optimal discrimination in three groups was observed by Ki67% (Ki67% cutoffs: G1 <4, G2 4-<25, G3 ≥25; G1 vs G2, P=0.021; and G2 vs G3, P≤0.001), mitotic count (G1 ≤2, G2 >2-47, G3 >47; G1 vs G2, P≤0.001; and G2 vs G3, P≤0.001), and presence of necrosis (G1 absent, G2 <10% of sample, G3 >10% of sample; G1 vs G2, P≤0.001; and G2 vs G3, P≤0.001) at uni and multivariable analyses. The combination of these three variables resulted in a simple and effective grading system. A three-tiers grading system based on Ki67 index, mitotic count, and necrosis with cutoffs specifically generated for lung neuroendocrine tumors is prognostically effective and accurate.

摘要

肺神经内分泌肿瘤在世界卫生组织(WHO 2004 年)分类中分为四类。其可重复性和预后效果存在争议。基于 Ki67 增殖评估的 2010 年版 WHO 消化系统神经内分泌肿瘤分类在预后上被证明是有效的。本研究旨在比较这两种分类,并为肺神经内分泌肿瘤定义一种预后分级系统。该研究纳入了 1989 年至 2011 年间接受手术且至少随访 1 年的 399 例患者。收集了 21 个变量的数据,并通过 Cox 回归和多变量分析比较了分级系统及其组成部分的性能。所有统计检验均为双侧检验。在 Cox 分析中,WHO 2004 版将患者分为三组,三组之间的生存差异具有统计学意义(典型类癌与非典型类癌(AC),P=0.021;AC 与大细胞/小细胞肺神经内分泌癌,P<0.001)。Ki67%(Ki67%截断值:G1<4、G2 4-<25、G3≥25;G1 与 G2,P=0.021;G2 与 G3,P≤0.001)、有丝分裂计数(G1≤2、G2>2-47、G3>47;G1 与 G2,P≤0.001;G2 与 G3,P≤0.001)和坏死(G1 无、G2<10%样本、G3>10%样本;G1 与 G2,P≤0.001;G2 与 G3,P≤0.001)在单变量和多变量分析中观察到三组的最佳区分度。这三个变量的组合产生了一种简单有效的分级系统。一种基于 Ki67 指数、有丝分裂计数和坏死的三层次分级系统,其截断值是专门为肺神经内分泌肿瘤生成的,具有预后效果和准确性。

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