Rhodes Kirsty Marie, Garbe Edeltraut, Müllerová Hana, Ekwaru Paul, Kossack Nils, Baak Brenda N, Lobier Muriel, Hawkins Nathaniel M, Nordon Clementine
Real-World Science and Analytics, BioPharmaceuticals Medical, AstraZeneca, Cambridge, UK.
Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
Clin Epidemiol. 2025 Jun 14;17:551-565. doi: 10.2147/CLEP.S520168. eCollection 2025.
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.
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.
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.
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.
多数据库研究尽管采用共同方案，但可能产生异质性结果，这给解释带来挑战，但也为深入了解人群或医疗保健系统提供了机会。这些分析的目的是建立一个框架，以探索统计异质性的来源，并将其应用于多数据库EXACOS-CV（慢性阻塞性肺疾病急性加重及其对心血管疾病的影响）项目。
建立了一个概念框架，用于系统评估多数据库研究中统计异质性的来源。该框架区分方法学多样性和真正的临床变异。方法学多样性包括研究设计和数据库选择的差异，而真正的变异则考虑人群和医疗差异。通过一份新颖的清单确定并探索了方法学多样性的可能来源。相应地，针对真正的变异提出了假设。该框架和清单应用于德国、加拿大、荷兰和西班牙的EXACOS-CV队列研究，这些研究与共同方案的偏差最小，因此被纳入。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后风险比（aHR），其结果分别是异质性最大和最小的。
在EXACOS-CV研究中，与非急性加重期相比，急性加重后第1至7天HF的调整后风险比（aHR）在德国为2.6（95%CI，2.3，2.9），在加拿大为72.3（64.4，81.2）；与死亡的关联，相对于非急性加重期，在荷兰为3.5（2.4，5.3），在西班牙为22.1（19.9，24.4）。完成的方法学多样性清单将aHR的差异与各研究中捕捉既往心血管合并症能力的可能差异以及混杂因素测量的差异联系起来。跨研究标准化调整模型并未完全解释异质性，表明存在其他影响因素。异质性可能源于心血管疾病患病率的真正差异。据推测，患有既往心血管疾病的患者对急性加重后心血管事件的诊断和管理更为准确，这可能导致此类事件的风险降低。
多数据库研究在考虑医疗保健系统和人群差异的同时，可以为研究问题提供方向性见解。所建立的框架有助于评估异质性来源。
