Atovaquone/proguanil-induced autoimmune-like hepatitis

Nomenclature, diagnosis and management of drug-induced autoimmune-like hepatitis (DI-ALH): An expert opinion meeting report

Drug-induced liver injury (DILI) can mimic almost all other liver disorders. A phenotype increasingly ascribed to drugs is autoimmune-like hepatitis (ALH). This article summarises the major topics discussed at a joint International Conference held between the Drug-Induced Liver Injury consortium and the International Autoimmune Hepatitis Group. DI-ALH is a liver injury with laboratory and/or histological features that may be indistinguishable from those of autoimmune hepatitis (AIH). Previous studies have revealed that patients with DI-ALH and those with idiopathic AIH have very similar clinical, biochemical, immunological and histological features. Differentiating DI-ALH from AIH is important as patients with DI-ALH rarely require long-term immunosuppression and the condition often resolves spontaneously after withdrawal of the implicated drug, whereas patients with AIH mostly require long-term immunosuppression. Therefore, revision of the diagnosis on long-term follow-up may be necessary in some cases. More than 40 different drugs including nitrofurantoin, methyldopa, hydralazine, minocycline, infliximab, herbal and dietary supplements (such as Khat and Tinospora cordifolia) have been implicated in DI-ALH. Understanding of DI-ALH is limited by the lack of specific markers of the disease that could allow for a precise diagnosis, while there is similarly no single feature which is diagnostic of AIH. We propose a management algorithm for patients with liver injury and an autoimmune phenotype. There is an urgent need to prospectively evaluate patients with DI-ALH systematically to enable definitive characterisation of this condition.

Worldwide Use of RUCAM for Causality Assessment in 81,856 Idiosyncratic DILI and 14,029 HILI Cases Published 1993-Mid 2020: A Comprehensive Analysis

Background: A large number of idiosyncratic drug induced liver injury (iDILI) and herb induced liver injury(HILI) cases of variable quality has been published but some are a matter of concern if the cases were not evaluated for causality using a robust causality assessment method (CAM) such as RUCAM (Roussel Uclaf Causality Assessment Method) as diagnostiinjuryc algorithm. The purpose of this analysis was to evaluate the worldwide use of RUCAM in iDILI and HILI cases. Methods: The PubMed database (1993-30 June 2020) was searched for articles by using the following key terms: Roussel Uclaf Causality Assessment Method; RUCAM; Idiosyncratic drug induced liver injury; iDILI; Herb induced liver injury; HILI. Results: Considering reports published worldwide since 1993, our analysis showed the use of RUCAM for causality assessment in 95,885 cases of liver injury including 81,856 cases of idiosyncratic DILI and 14,029 cases of HILI. Among the top countries providing RUCAM based DILI cases were, in decreasing order, China, the US, Germany, Korea, and Italy, with China, Korea, Germany, India, and the US as the top countries for HILI. Conclusion: Since 1993 RUCAM is certainly the most widely used method to assess causality in IDILI and HILI. This should encourage practitioner, experts, and regulatory agencies to use it in order to reinforce their diagnosis and to take sound decisions.

Toxicity profiling and prioritization of plant-derived antimalarial agents

Human malaria is the most widespread mosquito-borne life-threatening disease worldwide. In the absence of effective vaccines, prevention and treatment of malaria only depend on prophylaxis and drug-based therapy either in monotherapy or in combination. Unfortunately, the number of available antimalarial drugs presenting different mechanisms of action is rather limited. In addition, the appearance of drug-resistance in the parasite strains impacts the efficacy of the treatments. As a result, there is a crucial need to find new drugs to circumvent resistance problems. In the quest to identify new antimalarial agents a huge number of plant-derived compounds (PDCs) have been investigated. Surprisingly in the in silico PDC screening programs, toxicity filters are either never used or so simple that their interest is limited. In this context, the goal of this study was to show how to take advantage of validated toxicity QSAR models for refining the selection of PDCs. From an original data set of 507 PDCs collected from the literature, the use of toxicity filters for endocrine disruption, developmental toxicity, and hepatotoxicity in conjunction with classical pharmacokinetic filters allowed us to obtain a list of 31 compounds of potential interest. The pros and cons of such a strategy have been discussed.

Idiosyncratic DILI: Analysis of 46,266 Cases Assessed for Causality by RUCAM and Published From 2014 to Early 2019

One of the most difficult challenges in clinical hepatology is the diagnosis of a drug-induced liver injury (DILI). The timing of the events, exclusion of alternative causes, and taking into account the clinical context should be systematically assessed and scored in a transparent manner. RUCAM (Roussel Uclaf Causality Assessment Method) is a well-established diagnostic algorithm and scale to assess causality in patients with suspected DILI. First published in 1993 and updated in 2016, RUCAM is now the worldwide most commonly used causality assessment method (CAM) for DILI. The following manuscript highlights the recent implementation of RUCAM around the world, by reviewing the literature for publications that utilized RUCAM, and provides a review of “best practices” for the use of RUCAM in cases of suspected DILI. The worldwide appreciation of RUCAM is substantiated by the current analysis of 46,266 DILI cases, all tested for causality using RUCAM. These cases derived from 31 reports published from 2014 to early 2019. Their first authors came from 10 countries, with China on top, followed by the US, and Germany on the third rank. Importantly, all RUCAM-based DILI reports were published in high profile journals. Many other reports were published earlier from 1993 up to 2013 in support of RUCAM. Although most of the studies were of high quality, the current case analysis revealed shortcomings in few studies, not at the level of RUCAM itself but rather associated with the work of the users. To ensure in future DILI cases a better performance by the users, a list of essential elements is proposed. As an example, all suspected DILI cases should be evaluated 1) by the updated RUCAM to facilitate result comparisons, 2) according to a prospective study protocol to ensure complete data sets, 3) after exclusion of cases with herb induced liver injury (HILI) from a DILI cohort to prevent confounding variables, and 4) according to inclusion of DILI cases with RUCAM-based causality gradings of highly probable or probable, in order to increase the specificity of the results. In conclusion, RUCAM benefits from its high appreciation and performs well provided the users adhere to published recommendations to prevent confounding variability.

The first report of atovaquone/proguanil-induced vanishing bile duct syndrome: Case report and mini-review

The combination of Atovaquone and Proguanil (Malarone™) has been widely used for treatment and prevention of Plasmodium falciparum malaria. Transient elevation of liver enzymes is a recognized side effect of the medication. The association of Vanishing bile duct syndrome (VBDS) with the use of Atovaqoune/Proguanil was not previously reported. We describe a case of a 62-year-old male with no history of liver disease who presented with painless jaundice after receiving malaria prophylaxis with Atovaquone-proguanil for 25 days. The patient developed severe hepatitis with Vanishing bile duct syndrome. This case highlights a serious side effect of a usually well-tolerated medication.

Idiosyncratic DILI: Analysis of 46,266 Cases Assessed for Causality by RUCAM and Published From 2014 to Early 2019

One of the most difficult challenges in clinical hepatology is the diagnosis of a drug-induced liver injury (DILI). The timing of the events, exclusion of alternative causes, and taking into account the clinical context should be systematically assessed and scored in a transparent manner. RUCAM (Roussel Uclaf Causality Assessment Method) is a well-established diagnostic algorithm and scale to assess causality in patients with suspected DILI. First published in 1993 and updated in 2016, RUCAM is now the worldwide most commonly used causality assessment method (CAM) for DILI. The following manuscript highlights the recent implementation of RUCAM around the world, by reviewing the literature for publications that utilized RUCAM, and provides a review of "best practices" for the use of RUCAM in cases of suspected DILI. The worldwide appreciation of RUCAM is substantiated by the current analysis of 46,266 DILI cases, all tested for causality using RUCAM. These cases derived from 31 reports published from 2014 to early 2019. Their first authors came from 10 countries, with China on top, followed by the US, and Germany on the third rank. Importantly, all RUCAM-based DILI reports were published in high profile journals. Many other reports were published earlier from 1993 up to 2013 in support of RUCAM. Although most of the studies were of high quality, the current case analysis revealed shortcomings in few studies, not at the level of RUCAM itself but rather associated with the work of the users. To ensure in future DILI cases a better performance by the users, a list of essential elements is proposed. As an example, all suspected DILI cases should be evaluated 1) by the updated RUCAM to facilitate result comparisons, 2) according to a prospective study protocol to ensure complete data sets, 3) after exclusion of cases with herb induced liver injury (HILI) from a DILI cohort to prevent confounding variables, and 4) according to inclusion of DILI cases with RUCAM-based causality gradings of highly probable or probable, in order to increase the specificity of the results. In conclusion, RUCAM benefits from its high appreciation and performs well provided the users adhere to published recommendations to prevent confounding variability.