4.5 Review

Drug induced liver injury with analysis of alternative causes as confounding variables

Journal

BRITISH JOURNAL OF CLINICAL PHARMACOLOGY
Volume 84, Issue 7, Pages 1467-1477

Publisher

WILEY
DOI: 10.1111/bcp.13593

Keywords

alternative causes; causality assessment; competing causes; drug-induced liver injury; missed diagnoses; Roussel Uclaf Causality Assessment Method

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AimsDrug-induced liver injury (DILI) is rare compared to the worldwide frequent acute or chronic liver diseases. Therefore, patients included in series of suspected DILI are at high risk of not having DILI, whereby alternative causes may confound the DILI diagnosis. The aim of this review is to evaluate published case series of DILI for alternative causes. MethodsRelevant studies were identified using a computerized search of the Medline database for publications from 1993 through 30 October 2017. We used the following terms: drug hepatotoxicity, drug induced liver injury, hepatotoxic drugs combined with diagnosis, causality assessment and alternative causes. ResultsAlternative causes as variables confounding the DILI diagnosis emerged in 22 published DILI case series, ranging from 4 to 47%. Among 13335 cases of suspected DILI, alternative causes were found to be more likely in 4555 patients (34.2%), suggesting that the suspected DILI was probably not DILI. Biliary diseases such as biliary obstruction, cholangitis, choledocholithiasis, primary biliary cholangitis and primary sclerosing cholangitis were among the most missed diagnoses. Alternative causes included hepatitis B, C and E, cytomegalovirus, Epstein-Barr virus, ischemic hepatitis, cardiac hepatopathy, autoimmune hepatitis, nonalcoholic fatty liver disease, nonalcoholic steatohepatitis, and alcoholic liver disease. ConclusionsIn more than one-third of published global DILI case series, alternative causes as published in these reports confounded the DILI diagnosis. In the future, published DILI case series should include only patients with secured DILI diagnosis, preferentially established by prospective use of scored items provided by robust diagnostic algorithms such as the updated Roussel Uclaf causality assessment method.

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