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呼吸与心血管疾病领域的自然实验与大型数据库

Natural experiments and large databases in respiratory and cardiovascular disease.

作者信息

Vestbo Jørgen

机构信息

Centre for Respiratory Medicine and Allergy, The University of Manchester and University Hospital South Manchester NHS Foundation Trust, Manchester, UK

出版信息

Eur Respir Rev. 2016 Jun;25(140):130-4. doi: 10.1183/16000617.0028-2016.

DOI:10.1183/16000617.0028-2016
PMID:27246589
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9487243/
Abstract

A number of scientific questions cannot be tested in a laboratory, clinic or clinical trial setting. In many cases, observational data can be used to test such hypotheses.This article illustrates how epidemiology can contribute and shows the different ways of using observational data through three approaches: 1) prospective cohort study design; 2) time series analysis; and 3) a nested case-control design in pharmacoepidemiology.In a prospective cohort study design, three cohorts were merged to study lung function decline, testing the importance of different trajectories of lung function decline for developing chronic obstructive pulmonary disease (COPD). Using these three well-described cohorts it was documented that maximally attained lung function in early adulthood is as important as excess decline in forced expiratory volume in 1 s for the development of COPD. Time series analysis is used to examine exposures and disease over time. In a recent review of cardiovascular disease some interesting associations, and not least lack of associations, were presented. Assessing effects of drugs in database studies is challenging. In a nested case-control design in a large cohort study, statins were found to reduce the risk of COPD exacerbations. These findings will be discussed.Observational data from large databases, as well as carefully collected data in cohort studies, can be used to test hypotheses that may not be addressed in a traditional experimental setting.

摘要

许多科学问题无法在实验室、诊所或临床试验环境中进行检验。在许多情况下,观察性数据可用于检验此类假设。本文阐述了流行病学如何发挥作用,并通过三种方法展示了使用观察性数据的不同方式:1)前瞻性队列研究设计;2)时间序列分析;3)药物流行病学中的巢式病例对照设计。在前瞻性队列研究设计中,合并了三个队列来研究肺功能下降情况,检验肺功能下降的不同轨迹对于慢性阻塞性肺疾病(COPD)发生发展的重要性。利用这三个详细描述的队列,研究表明成年早期达到的最大肺功能与1秒用力呼气量过度下降对于COPD的发生发展同样重要。时间序列分析用于随时间检查暴露因素和疾病情况。在最近一篇关于心血管疾病的综述中,呈现了一些有趣的关联,尤其是无关联的情况。在数据库研究中评估药物的效果具有挑战性。在一项大型队列研究的巢式病例对照设计中,发现他汀类药物可降低COPD急性加重的风险。将对这些发现进行讨论。来自大型数据库的观察性数据以及队列研究中精心收集的数据,可用于检验在传统实验环境中可能无法解决的假设。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cec/9487243/e357b0b4b5a5/ERR-0028-2016.02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cec/9487243/afae3d67d641/ERR-0028-2016.01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cec/9487243/e357b0b4b5a5/ERR-0028-2016.02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cec/9487243/afae3d67d641/ERR-0028-2016.01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cec/9487243/e357b0b4b5a5/ERR-0028-2016.02.jpg

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The Salford Lung Study protocol: a pragmatic, randomised phase III real-world effectiveness trial in chronic obstructive pulmonary disease.索尔福德肺部研究方案:一项针对慢性阻塞性肺疾病的实用、随机、III期真实世界有效性试验。
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风险因素和医疗保健对心血管疾病死亡率趋势的影响
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