Assessment of case definitions for identifying acute liver injury in large observational databases

Aaron J Katz, Patrick B Ryan, Judith A Racoosin, Paul E Stang
Drug Safety: An International Journal of Medical Toxicology and Drug Experience 2013, 36 (8): 651-61

BACKGROUND: Determining the aetiology of acute liver injury (ALI) may be challenging to both clinicians and researchers. Observational research is particularly useful in studying rare medical outcomes such as ALI; however, case definitions for ALI in previous observational studies lack consistency and sensitivity. ALI is a clinically important condition with various aetiologies, including drug exposure.

OBJECTIVE: The aim of this study was to evaluate four distinct case definitions for ALI across a diverse set of large observational databases, providing a better understanding of ALI prevalence and natural history.

DATA SOURCES: Seven healthcare databases: GE Healthcare, MarketScan(®) Lab Database, Humana Inc., Partners HealthCare System, Regenstrief Institute, SDI Health (now IMS Health, Inc.), and the National Patient Care Database of the Veterans Health Administration.

METHODS: We evaluated prevalence of ALI through the application of four distinct case definitions across seven observational healthcare databases. We described how laboratory and clinical characteristics of identified case populations varied across definitions and examined the prevalence of other hepatobiliary disorders among identified ALI cases that may decrease suspicion of drug-induced liver injury (DILI) in particular.

RESULTS: This study demonstrated that increasing the restrictiveness of the case definition resulted in fewer cases, but greater prevalence of ALI clinical features. Considerable heterogeneity in the frequency of laboratory testing and results observed among cases meeting the most restrictive definition suggests that the clinical features, monitoring patterns and suspicion of ALI are highly variable among patients.

CONCLUSIONS: Creation of four distinct case definitions and application across a disparate set of observational databases resulted in significant variation in the prevalence of ALI. A greater understanding of the natural history of ALI through examination of electronic healthcare data can facilitate development of reliable and valid ALI case definitions that may enhance the ability to accurately identify associations between ALI and drug exposures. Considerable heterogeneity in laboratory values and frequency of laboratory testing among individuals meeting the criteria for ALI suggests that the evaluation of ALI is highly variable.

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