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非恒定风险疾病的流行病学负担估计:根据年龄、梅塔维分级和基因型对意大利丙型肝炎病毒的应用:一项系统评价和荟萃分析

Epidemiological burden estimates for pathologies with a nonconstant risk: an application to HCV in Italy according to age, Metavir score, and genotype: A systematic review and meta-analysis.

作者信息

Mancusi Rossella Letizia, Andreoni Massimo, d'Angela Daniela, Sarrecchia Cesare, Spandonaro Federico

机构信息

C.R.E.A. Sanità (Consortium for Applied Economic Research in Healthcare), Department of Economic and Finance, University of Rome "Tor Vergata" Clinical infectious Disease, Department of Medicine of Systems, Tor Vergata University Hospital Department of Economic and Finance, University of Rome "Tor Vergata", C.R.E.A. Sanità (Consortium for Applied Economic Research in Healthcare), Italy.

出版信息

Medicine (Baltimore). 2016 Oct;95(42):e5143. doi: 10.1097/MD.0000000000005143.

DOI:10.1097/MD.0000000000005143
PMID:27759643
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5079327/
Abstract

Between western European countries, the hepatitis C virus (HCV) endemic is highest in Italy. The main objective of this paper is to estimate the endemic diffusion of hepatitis C at the national level and by geographical area, with an extrapolation at the regional level and by uniform cohorts of subjects (by sex and year of birth). The secondary objective is a stratification by gravity of the estimated statistical figures to provide an overview of possible targets of the new anti-HCV treatments.PubMed and the Cochrane Library were searched for relevant Italian populations studies regarding HCV prevalence. Random and fixed effect models were used for pooling data. To develop the epidemiological model, a meta-analysis of studies of Italian populations and the explicit consideration of the changes in the etiology of the disease in different cohorts (by year of birth) of population and the impact of effective treatments that have been introduced since the 1990s. A Markovian transition model, which is based on the distribution of HCV+ and HCV Ribonucleic Acid (RNA)+ subjects, provides a plausible assessment of the Italian situation. The Meta-analysis of Observational Studies in Epidemiology recommendations/statements were followed.In 2014, 1569,215 HCV+ subjects (95% credible interval [CrI]: 1202,630-2021,261) were estimated in Italy, with a 2.58% prevalence (95% CrI: 1.98%-3.33%). A total of 828,884 HCV RNA+ subjects (95% CrI: 615,892-1081,123), which is equal to a 1.36% prevalence (95% CrI: 1.01%-1.78%), is higher in southern Italy and the islands (1.9%) than in central-northern Italy (1.1%). The predominance of adult and elderly subjects, with an old or very old infection, inevitably entails a significant number of HCV RNA+ subjects in the advanced stages of the illness. According to our estimates, approximately 400,000 subjects have cirrhosis, decompensated cirrhosis, and hepatocarcinoma, with a median age of 70 years.The model aims to support policymakers to define action plans by providing an estimate of both the emerged infected population and nonemerged infected population by age, gender, gravity, genotype, and geographical area. In the future, the model may contribute to simulation of the costs and outcome of different action strategies that can be adopted by health authorities.

摘要

在西欧国家中,丙型肝炎病毒(HCV)在意大利的流行程度最高。本文的主要目的是估计丙型肝炎在国家层面以及地理区域层面的流行传播情况,并外推至区域层面以及按统一的人群队列(按性别和出生年份)进行估计。次要目的是根据估计的统计数据的严重程度进行分层,以概述新型抗HCV治疗可能的目标人群。

检索了PubMed和Cochrane图书馆中有关意大利人群HCV患病率的相关研究。使用随机效应模型和固定效应模型合并数据。为建立流行病学模型,对意大利人群研究进行荟萃分析,并明确考虑不同出生队列人群中疾病病因的变化以及自20世纪90年代以来引入的有效治疗的影响。基于HCV阳性和HCV核糖核酸(RNA)阳性受试者分布的马尔可夫转换模型,对意大利的情况提供了合理评估。遵循了流行病学观察性研究的荟萃分析建议/声明。

2014年,意大利估计有1569215名HCV阳性受试者(95%可信区间[CrI]:1202630 - 2021261),患病率为2.58%(95% CrI:1.98% - 3.33%)。共有828884名HCV RNA阳性受试者(95% CrI:615892 - 1081123),患病率为1.36%(95% CrI:1.01% - 1.78%),在意大利南部和岛屿地区(1.9%)高于中北部意大利(1.1%)。成年和老年受试者占主导,感染时间长或非常长,不可避免地导致大量处于疾病晚期的HCV RNA阳性受试者。根据我们的估计,约有40万受试者患有肝硬化、失代偿性肝硬化和肝癌,中位年龄为70岁。

该模型旨在通过按年龄、性别、严重程度、基因型和地理区域提供已感染人群和未感染人群的估计数,支持政策制定者制定行动计划。未来,该模型可能有助于模拟卫生当局可采用的不同行动策略的成本和结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba8c/5079327/b5d836735c08/medi-95-e5143-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba8c/5079327/ed9b49874f6b/medi-95-e5143-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba8c/5079327/b9615a398d10/medi-95-e5143-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba8c/5079327/efe83165e4e7/medi-95-e5143-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba8c/5079327/b5d836735c08/medi-95-e5143-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba8c/5079327/ed9b49874f6b/medi-95-e5143-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba8c/5079327/b9615a398d10/medi-95-e5143-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba8c/5079327/efe83165e4e7/medi-95-e5143-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba8c/5079327/b5d836735c08/medi-95-e5143-g008.jpg

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