内分泌和神经内分泌肿瘤

A. Grossman, Márta Korbonitis, P. Plowman
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引用次数: 8

摘要

背景:神经内分泌肿瘤(NETs)是由多种神经内分泌细胞类型引起的异质肿瘤。根据欧洲立法的标准,有些可能是孤儿适应症。然而,关于特定亚型蚊帐的流行病学数据很少。本研究旨在评估欧盟胃肠胰(GEP)和肺部NETs的患病率。方法:采用Medline和Embase文献数据库进行系统文献综述。搜索策略结合了以下概念,使用MeSH和Emtree术语:感兴趣的疾病,流行病学?数据(发病率或流行率)和感兴趣的国家。检索期包括2010年1月1日至2016年2月15日。还进行了网络资源和会议记录的实用搜索。使用检索中确定的数据,根据患病率(P)、发病率(I)和疾病持续时间(D)之间的关系(如适用)估计患病率。使用截至2015年1月1日的欧盟人口规模来估计患有GEPand肺部NETs的患者数量。由于患者的发病率和生存率在不同国家和环境中有所不同,因此还进行了敏感性分析。结果:通过文献检索和语用检索,GEP-NETs和lung NETs分别鉴定出87和23个来源。经过深入审查,分别保留了8个和6个数据源用于提取GEP和肺NETs的流行病学数据。考虑到GEP-NETs和肺部NETs的最高估计患病率(3.8和1.9)
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Endocrine and Neuroendocrine Tumors
Background: Neuroendocrine tumours (NETs) consist of a heterogeneous group of neoplasms arising from avarietyof neuroendocrine cell types. According to criteria of the European legislation, some may be orphan indications. However, epidemiologic data on specific sub-types of NETs are scarce. This studyaimed at assessing the prevalence of gastroenteropancreatic (GEP) and lung NETs in the European Union. Methods: Systematic literature reviews were conducted using Medline and Embase bibliographical databases. Search strategies combined the following concepts, using MeSH and Emtree terms: Disease of interest, epidemiologic? data (incidence or prevalence) and countries of interest. The search period covered 1st Jan 2010 to 15 Feb 2016, inclusively. Pragmatic searches of web sources and conference proceedings were also conducted. Using data identified in the search, prevalence rates were estimated using the relationship between prevalence (P), incidence (I), and disease duration (D), where applicable. Size of the EU population as of 1 st January 2015 was used to estimate number of patients with GEPand lung NETs. As incidences rates and survival of patients varyacross countries and settings, sensitivityanalyses were also performed. Results: A total of 87 and 23 sources were identified through the literature search and pragmatic search, respectively for GEP-NETs and lung NETs. Following in-depth review, 8 and 6 data sources were retained forepidemiologic data extraction on GEP and lung NETs, respectively.Considering, the highest estimated prevalence rates of GEP-NETs and lung NETs (3.8 and 1.9
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