Curran Desmond, Callegaro Andrea, Fahrbach Kyle, Neupane Binod, Vroling Hilde, van Oorschot Désirée, Yawn Barbara P
GSK, Wavre, Belgium.
GSK, Rixensart, Belgium.
Infect Dis Ther. 2022 Feb;11(1):389-403. doi: 10.1007/s40121-021-00567-8. Epub 2021 Dec 7.
Many studies have been conducted worldwide to estimate herpes zoster (HZ) incidence rates. We synthesized studies of HZ incidence rates in the general population using meta-analysis models.
A random effects meta-analysis was conducted to estimate HZ incidence from a published worldwide systematic literature review (SLR) including only individuals aged 50 years and older. Meta-regression was used to explore whether variability in incidence rates could be explained by a combination of study-specific characteristics including age, gender, continent and year of study data. The impact of adding additional covariates-case detection method (general practitioner surveillance, healthcare database, sentinel network, etc.), case definition (medical record-based, self-reported), study design (retrospective passive surveillance, retrospective active surveillance, etc.), incidence type (cumulative incidence/1000 persons or incidence rate/1000 person-years), patient type (outpatients or in- and out-patients) and latitude to the base model-was also assessed.
Sixty-one records from 59 studies were included in the analysis: 25, 20, 11 and 5 from Europe, North America, Asia and Oceania, respectively. There was variation in study methodology and outcomes. Heterogeneity of incidence rates was greatest among studies conducted in Asia. Meta-analysis showed that incidence increased with age, was lower in males compared to females, tended to be lower in Europe and North America compared to Asia and Oceania and increased with year of study data. The data-driven meta-regression model included continent, year of study data, gender, age and an age × gender interaction term. The difference in incidence between males and females was greater in younger ages (e.g., 50-59) compared to older age groups (e.g., 80+). None of the additional covariates contributed significantly to the model.
Incidence rates were shown to vary by age, gender, continent and year of study data.
全球已开展了许多研究来估计带状疱疹（HZ）的发病率。我们使用荟萃分析模型综合了普通人群中HZ发病率的研究。
进行了一项随机效应荟萃分析，以根据已发表的全球系统性文献综述（SLR）估计HZ发病率，该综述仅纳入了50岁及以上的个体。使用元回归来探讨发病率的变异性是否可以由包括年龄、性别、大洲和研究数据年份在内的特定研究特征的组合来解释。还评估了在基础模型中添加其他协变量（病例检测方法（全科医生监测、医疗保健数据库、哨点网络等）、病例定义（基于病历、自我报告）、研究设计（回顾性被动监测、回顾性主动监测等）、发病率类型（累积发病率/1000人或发病率/1000人年）、患者类型（门诊患者或门诊和住院患者）和纬度）的影响。
分析纳入了来自59项研究的61条记录：分别来自欧洲、北美、亚洲和大洋洲的25条、20条、11条和5条。研究方法和结果存在差异。亚洲进行的研究中发病率的异质性最大。荟萃分析表明，发病率随年龄增加，男性低于女性，与亚洲和大洋洲相比，欧洲和北美的发病率往往较低，且随研究数据年份增加。数据驱动的元回归模型包括大洲、研究数据年份、性别、年龄和年龄×性别交互项。与老年组（如80岁以上）相比，年轻年龄组（如50 - 59岁）中男性和女性的发病率差异更大。没有其他协变量对模型有显著贡献。
发病率显示因年龄、性别、大洲和研究数据年份而异。
