Studies based on health administrative data regarding rare outcomes in inflammatory bowel disease significantly underestimate the true risk - the importance of specificity.
IF 4.8 2区 医学Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Mikkel Malham, Eric I Benchimol, Matthew P Fox, David C Wilson
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引用次数: 0
Abstract
Background: Health administrative data (HAD) have significantly increased our knowledge of rare outcomes in inflammatory bowel disease (IBD), such as cancer and mortality. We aimed to assess the information bias imposed by misclassification of the IBD diagnosis in HAD studies by performing quantitative bias analysis (QBA).
Design: In a narrative review, we identified pediatric-onset IBD (PIBD) HAD studies assessing cancer risk in which the PIBD case identification was based on published validation studies. We then performed QBA to adjust for non-differential exposure misclassification using the sensitivity and specificity values from country or region-specific validation studies.
Results: We present QBA on four recent studies reporting on cancer outcomes. Generally, we found the reported cancer risks biased towards the null. In the most extreme example, the relative risk changed from 2.0 (95% confidence interval [CI]: 1.2-3.4) to 5.8 (95%CI: 2.5-13.7) after bias adjustment. The risk difference for this example rose from 1.0% (95%CI: 0.1-1.9) to 3.8% (95%CI: 1.4-7.9) after bias adjustment.
Conclusion: The results from this study indicate that most HAD-based studies on rare long-term consequences of IBD significantly underestimate the true risk of the outcomes. These results can be extrapolated to other HAD-based studies with imperfect specificity of the case assertion algorithms.
期刊介绍:
The American Journal of Epidemiology is the oldest and one of the premier epidemiologic journals devoted to the publication of empirical research findings, opinion pieces, and methodological developments in the field of epidemiologic research.
It is a peer-reviewed journal aimed at both fellow epidemiologists and those who use epidemiologic data, including public health workers and clinicians.