Studies based on health administrative data regarding rare outcomes in inflammatory bowel disease significantly underestimate the true risk—the importance of specificity

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). 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. 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% 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. 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.

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Journal
American Journal of Epidemiology
Published
2025-09-25
DOI
https://doi.org/10.1093/aje/kwaf216
Primary Topic
Health Systems, Economic Evaluations, Quality of Life
Type
article
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article

Studies based on health administrative data regarding rare outcomes in inflammatory bowel disease significantly underestimate the true risk—the importance of specificity

Eric I. Benchimol, Mikkel Malham, Matthew P. Fox, David C. Wilson
American Journal of Epidemiology
Health Systems, Economic Evaluations, Quality of Life
article

Studies based on health administrative data regarding rare outcomes in inflammatory bowel disease significantly underestimate the true risk—the importance of specificity

Eric I. Benchimol, Mikkel Malham, Matthew P. Fox, David C. Wilson
article en

Abstract

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). 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. 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% 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. 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.

American Journal of EpidemiologyVol. 194(12)
Boston University (US), University of Copenhagen (DK), University of Toronto (CA), Royal Hospital for Children (GB), Amager Hospital (DK), Hospital for Sick Children (CA), University College Copenhagen (DK), Royal Hospital for Sick Children (GB), SickKids Foundation (CA), Institute for Clinical Evaluative Sciences (CA), University of Edinburgh (GB)
Openalex Percentile: Top 65%
Health Systems, Economic Evaluations, Quality of Life
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