Suppr超能文献

一项全国范围内基于人群的遗传性肌肉疾病患病率研究。

A Nationwide, Population-Based Prevalence Study of Genetic Muscle Disorders.

机构信息

National Institute for Stroke and Applied Neurosciences, Faculty of Health and Environmental Studies, Auckland University of Technology, Auckland, New Zealand,

Muscular Dystrophy Association of New Zealand, Auckland, New Zealand.

出版信息

Neuroepidemiology. 2019;52(3-4):128-135. doi: 10.1159/000494115. Epub 2019 Jan 18.

Abstract

BACKGROUND

Previous epidemiological studies of genetic muscle disorders have relied on medical records to identify cases and may be at risk of selection biases or have focused on selective population groups.

OBJECTIVES

This study aimed to determine age-standardised prevalence of genetic muscle disorders through a nationwide, epidemiological study across the lifespan using the capture-recapture method.

METHODS

Adults and children with a confirmed clinical or molecular diagnosis of a genetic muscle disorder, resident in New Zealand on April 1, 2015 were identified using multiple overlapping sources. Genetic muscle disorders included the muscular dystrophies, congenital myopathies, ion channel myopathies, GNE myopathy, and Pompe disease. Prevalence per 100,000 persons by age, sex, disorder, ethnicity and geographical region with 95% CIs was calculated using Poisson distribution. Direct standardisation was applied to age-standardise prevalence to the world population. Completeness of case ascertainment was determined using capture-recapture modelling.

RESULTS

Age standardised minimal point prevalence of all genetic muscle disorders was 22.3 per 100,000 (95% CI 19.5-25.6). Prevalence in Europeans of 24.4 per 100,000, (95% CI 21.1-28.3) was twice that observed in NZ's other 3 main ethnic groups; Māori (12.6 per 100,000, 95% CI 7.8-20.5), Pasifika (11.0 per 100,000, 95% CI 5.4-23.3), and Asian (9.13 per 100,000, 95% CI 5.0-17.8). Crude prevalence of myotonic dystrophy was 3 times higher in Europeans (10.5 per 100,000, 9.4-11.8) than Māori and Pasifika (2.5 per 100,000, 95% CI 1.5-4.2 and 0.7 per 100,000, 95% CI 0.1-2.7 respectively). There were considerable regional variations in prevalence, although there was no significant association with social deprivation. The final capture-recapture model, with the least deviance, estimated the study ascertained 99.2% of diagnosed cases.

CONCLUSIONS

Ethnic and regional differences in the prevalence of genetic muscle disorders need to be considered in service delivery planning, evaluation, and decision making.

摘要

背景

先前的遗传性肌肉疾病的流行病学研究依赖于医疗记录来识别病例,因此可能存在选择偏差的风险,或者仅关注特定人群。

目的

本研究旨在通过全国范围内、跨生命周期的捕获-再捕获方法进行的流行病学研究,确定遗传性肌肉疾病的年龄标准化患病率。

方法

2015 年 4 月 1 日居住在新西兰的经临床或分子确诊为遗传性肌肉疾病的成人和儿童,通过多种重叠来源确定。遗传性肌肉疾病包括肌营养不良症、先天性肌病、离子通道肌病、GNE 肌病和庞贝病。使用泊松分布计算每 10 万人的患病率及其年龄、性别、疾病、种族和地理区域的 95%置信区间 (CI)。应用直接标准化法将患病率标准化为世界人口。使用捕获-再捕获模型确定病例检出的完整性。

结果

所有遗传性肌肉疾病的年龄标准化最小点患病率为 22.3/10 万(95%CI 19.5-25.6)。欧洲人的患病率为 24.4/10 万(95%CI 21.1-28.3),是新西兰其他三个主要种族组(毛利人 12.6/10 万,95%CI 7.8-20.5;太平洋岛民 11.0/10 万,95%CI 5.4-23.3;亚洲人 9.13/10 万,95%CI 5.0-17.8)的两倍。欧洲人的先天性肌营养不良症粗患病率是毛利人和太平洋岛民的 3 倍(分别为 10.5/10 万,9.4-11.8 和 2.5/10 万,95%CI 1.5-4.2 和 0.7/10 万,95%CI 0.1-2.7)。患病率存在明显的地区差异,尽管与社会贫困程度无显著相关性。最终的捕获-再捕获模型,具有最小的偏差,估计该研究检出了诊断病例的 99.2%。

结论

在服务提供规划、评估和决策中,需要考虑遗传性肌肉疾病的患病率的种族和地区差异。

相似文献

引用本文的文献

1
Long-read sequencing for diagnosis of genetic myopathies.用于诊断遗传性肌病的长读长测序
BMJ Neurol Open. 2025 May 11;7(1):e000990. doi: 10.1136/bmjno-2024-000990. eCollection 2025.

本文引用的文献

4
Prevalence of muscular dystrophies: a systematic literature review.肌肉萎缩症的患病率:系统文献回顾。
Neuroepidemiology. 2014;43(3-4):259-68. doi: 10.1159/000369343. Epub 2014 Dec 16.
5
The New Zealand Neuromuscular Disease Registry.新西兰神经肌肉疾病登记处。
J Clin Neurosci. 2012 Dec;19(12):1749-50. doi: 10.1016/j.jocn.2012.04.008. Epub 2012 Sep 19.
8
Inherited myopathies and muscular dystrophies.遗传性肌病和肌肉萎缩症
Semin Neurol. 2008 Apr;28(2):250-9. doi: 10.1055/s-2008-1062269.
9
The importance of epidemiological studies should not be downplayed.流行病学研究的重要性不应被低估。
Stroke. 2008 Jan;39(1):1-2. doi: 10.1161/STROKEAHA.107.503250. Epub 2007 Nov 15.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验