Framework for Exploration of Statistical Heterogeneity in Multi-Database Studies: A Case Study Using EXACOS-CV Studies.

IF 3.4 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Clinical Epidemiology Pub Date : 2025-06-14 eCollection Date: 2025-01-01 DOI:10.2147/CLEP.S520168
Kirsty Marie Rhodes, Edeltraut Garbe, Hana Müllerová, Paul Ekwaru, Nils Kossack, Brenda N Baak, Muriel Lobier, Nathaniel M Hawkins, Clementine Nordon
{"title":"Framework for Exploration of Statistical Heterogeneity in Multi-Database Studies: A Case Study Using EXACOS-CV Studies.","authors":"Kirsty Marie Rhodes, Edeltraut Garbe, Hana Müllerová, Paul Ekwaru, Nils Kossack, Brenda N Baak, Muriel Lobier, Nathaniel M Hawkins, Clementine Nordon","doi":"10.2147/CLEP.S520168","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>Multi-database studies may provide heterogeneous results despite using common protocols, leading to challenges in interpretation, but also providing an opportunity to gain insights on populations or healthcare systems. The objectives of these analyses were to develop a framework for exploring sources of statistical heterogeneity and apply it to the multi-database EXACOS-CV (EXAcerbations of COPD and their OutcomeS on CardioVascular diseases) program.</p><p><strong>Methods: </strong>A conceptual framework to systematically assess sources of statistical heterogeneity in multi-database studies was developed. This framework distinguishes between methodological diversity and true clinical variation. Methodological diversity includes differences in study design and database selection, while true variation considers population and healthcare differences. Possible sources of methodological diversity were identified via a novel checklist and explored. In turn, hypotheses were generated about true variation. The framework and checklist were applied to EXACOS-CV cohort studies in Germany, Canada, the Netherlands, and Spain which deviated least from the common protocol and so were included. Focus was on adjusted hazard ratios (aHR) for post-exacerbation associations with decompensated heart failure (HF) and all-cause death, for which results were most and least heterogeneous, respectively.</p><p><strong>Results: </strong>Across EXACOS-CV studies, the adjusted hazard ratios (aHR) for HF in the first 1-7 days post-exacerbation, compared to non-exacerbation periods, ranged from 2.6 (95% CI, 2.3, 2.9) in Germany to 72.3 (64.4, 81.2) in Canada, and the association with death, relative to non-exacerbation periods, ranged from 3.5 (2.4, 5.3) in the Netherlands to 22.1 (19.9, 24.4) in Spain. Completed methodological diversity checklists linked differences in aHRs to possible variation in ability to capture pre-existing cardiovascular comorbidities across studies, as well as differences in confounder measurement. Standardizing adjusted models across studies did not fully explain heterogeneity, suggesting other contributing factors. Heterogeneity may result from genuine variation in prevalence of CV disease. It was hypothesized that patients with pre-existing CV disease have more accurate diagnoses and management of post-exacerbation CV events, possibly leading to lower risks of such events.</p><p><strong>Conclusion: </strong>Multi-database studies can provide directional insights on the study research question while considering healthcare system and population differences. The developed framework aids assessment of heterogeneity sources.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"551-565"},"PeriodicalIF":3.4000,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12176119/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Epidemiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/CLEP.S520168","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0

Abstract

Purpose: Multi-database studies may provide heterogeneous results despite using common protocols, leading to challenges in interpretation, but also providing an opportunity to gain insights on populations or healthcare systems. The objectives of these analyses were to develop a framework for exploring sources of statistical heterogeneity and apply it to the multi-database EXACOS-CV (EXAcerbations of COPD and their OutcomeS on CardioVascular diseases) program.

Methods: A conceptual framework to systematically assess sources of statistical heterogeneity in multi-database studies was developed. This framework distinguishes between methodological diversity and true clinical variation. Methodological diversity includes differences in study design and database selection, while true variation considers population and healthcare differences. Possible sources of methodological diversity were identified via a novel checklist and explored. In turn, hypotheses were generated about true variation. The framework and checklist were applied to EXACOS-CV cohort studies in Germany, Canada, the Netherlands, and Spain which deviated least from the common protocol and so were included. Focus was on adjusted hazard ratios (aHR) for post-exacerbation associations with decompensated heart failure (HF) and all-cause death, for which results were most and least heterogeneous, respectively.

Results: Across EXACOS-CV studies, the adjusted hazard ratios (aHR) for HF in the first 1-7 days post-exacerbation, compared to non-exacerbation periods, ranged from 2.6 (95% CI, 2.3, 2.9) in Germany to 72.3 (64.4, 81.2) in Canada, and the association with death, relative to non-exacerbation periods, ranged from 3.5 (2.4, 5.3) in the Netherlands to 22.1 (19.9, 24.4) in Spain. Completed methodological diversity checklists linked differences in aHRs to possible variation in ability to capture pre-existing cardiovascular comorbidities across studies, as well as differences in confounder measurement. Standardizing adjusted models across studies did not fully explain heterogeneity, suggesting other contributing factors. Heterogeneity may result from genuine variation in prevalence of CV disease. It was hypothesized that patients with pre-existing CV disease have more accurate diagnoses and management of post-exacerbation CV events, possibly leading to lower risks of such events.

Conclusion: Multi-database studies can provide directional insights on the study research question while considering healthcare system and population differences. The developed framework aids assessment of heterogeneity sources.

探索多数据库研究中统计异质性的框架:使用EXACOS-CV研究的案例研究。
目的:多数据库研究可能会提供不同的结果,尽管使用共同的协议,导致解释上的挑战,但也提供了一个机会,以获得对人群或医疗保健系统的见解。这些分析的目的是建立一个框架来探索统计异质性的来源,并将其应用于多数据库EXACOS-CV (COPD恶化及其心血管疾病结局)项目。方法:建立了一个概念性框架,系统地评估多数据库研究中统计异质性的来源。这个框架区分了方法学多样性和真正的临床变异。方法多样性包括研究设计和数据库选择的差异,而真正的差异考虑人口和医疗保健的差异。方法多样性的可能来源通过一个新的检查表确定和探索。反过来,产生了关于真实变异的假设。该框架和检查表应用于德国、加拿大、荷兰和西班牙的EXACOS-CV队列研究,这些研究与通用方案偏差最小,因此被纳入研究。重点是急性加重后与失代偿性心力衰竭(HF)和全因死亡相关的调整风险比(aHR),结果分别具有最大和最小的异质性。结果:在EXACOS-CV研究中,与非加重期相比,加重后1-7天HF的校正危险比(aHR)从德国的2.6 (95% CI, 2.3, 2.9)到加拿大的72.3(64.4,81.2)不等,与非加重期相比,与死亡的相关性从荷兰的3.5(2.4,5.3)到西班牙的22.1(19.9,24.4)不等。完整的方法多样性检查表将ahr的差异与不同研究中捕获预先存在的心血管合并症的能力的可能差异以及混杂因素测量的差异联系起来。标准化的研究调整模型并不能完全解释异质性,这表明还有其他因素在起作用。异质性可能是由于CV疾病患病率的真实差异。假设已有心血管疾病的患者对加重后心血管事件的诊断和管理更准确,可能导致此类事件的风险更低。结论:多数据库研究可以在考虑医疗体系和人群差异的情况下,为研究问题提供方向性的见解。开发的框架有助于评估异质性来源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Clinical Epidemiology
Clinical Epidemiology Medicine-Epidemiology
CiteScore
6.30
自引率
5.10%
发文量
169
审稿时长
16 weeks
期刊介绍: Clinical Epidemiology is an international, peer reviewed, open access journal. Clinical Epidemiology focuses on the application of epidemiological principles and questions relating to patients and clinical care in terms of prevention, diagnosis, prognosis, and treatment. Clinical Epidemiology welcomes papers covering these topics in form of original research and systematic reviews. Clinical Epidemiology has a special interest in international electronic medical patient records and other routine health care data, especially as applied to safety of medical interventions, clinical utility of diagnostic procedures, understanding short- and long-term clinical course of diseases, clinical epidemiological and biostatistical methods, and systematic reviews. When considering submission of a paper utilizing publicly-available data, authors should ensure that such studies add significantly to the body of knowledge and that they use appropriate validated methods for identifying health outcomes. The journal has launched special series describing existing data sources for clinical epidemiology, international health care systems and validation studies of algorithms based on databases and registries.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信