This material was presented in the 25th European Congress of Psychiatry which was organised by the European Psychiatry Association in Florence, Italy from 1-4th April 2017. I had access to the material as I attended the full Congress. Please note that this material remains the intellectual property of the European Psychiatry Association and its authors and any citation should include a full reference to it. For more information on the EPA and how to become a member, please visit: http://www.europsy.net/

1. Hepatotoxicity related to antidepressive psychopharmacotherapy:
implications of quantitative signal detection
1Maximilian Gahr, 1René Zeiss, 2Dirk Lang, 1Bernhard J. Connemann, 1Carlos Schönfeldt-Lecuona
1University of Ulm, Department of Psychiatry and Psychotherapy III, Leimgrubenweg 12-14, 89075 Ulm, Germany; 2University of Ulm, Department of
Psychosomatic Medicine and Psychotherapy, Albert-Einstein-Allee 23, 89081 Ulm, Germany; Contact: maximilian.gahr@uni-ulm.de
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7. Montastruc F, Scotto S, Vaz I, et al. Hepatotoxicity Related to Agomelatine and Other New Antidepressants: A Case/Noncase Approach With Information From the Portuguese, French, Spanish, and Italian Pharmacovigilance Systems. J Clin Psychopharmacol. 2014;34(3):327-330.
INTRODUCTION
Liver injury due to drug treatment is a major safety concern and ranks on place four of causes of liver injury in Western countries (1). Moreover, it is the most common
reason for withdrawing drugs from the market and for rejecting marketing applications in the Unites States of America (2). Hepatotoxic drug reactions tend to occur with
incidences between 1/100000 to 1/10000 patient-years (3, 4). Therefore, the hepatotoxic potential of any particular agent cannot usually be identified in the pre-marketing
setting where insufficient numbers of patients are treated and assessed (5). Thus, post-marketing surveillance is of paramount importance in regard of liver injury related to
drug treatment (6). Hepatotoxic reactions, even severe forms with fatal outcomes, have been reported for many antidepressants (6). Currently, up-to-date evaluations of a
larger number of antidepressants with a consistent methodological approach are missing. Methods of pharmacovigilance, as quantitative signal detection, are frequently
used to evaluate substance-related risks. In the present paper, we sought to evaluate the statistical risk for hepatotoxic adverse drug reactions related to antidepressive
agents by using pharmacovigilance data obtained from the Uppsala Monitoring Centre (VigiBaseTM) of the World Health Organization (WHO), namely numbers of
spontaneous reports of adverse drug reactions (ADR) from worldwide sources.
MATERIALS AND METHODS
Database: As a consequence of the thalidomide-related events, the WHO has established the International Drug Monitoring Programme in 1968, currently representing the largest international pharmacovigilance project. As of December 2014, national pharmacovigilance centres
of 120 countries participate and, in addition, pharmacovigilance centres from 28 countries are associated members (see http://www.who-umc.org). These national pharmacovigilance centres report adverse drug reactions (ADR) to the Uppsala Monitoring Centre (UMC), Sweden,
where ADR data is processed, evaluated and finally recorded in a database (VigiBaseTM). VigiBaseTM is the largest and most comprehensive pharmacovigilance database in the world (see http://ww.umc-products.com). The UMC is an independent foundation and a center for
international service and scientific research (see http://www.who-umc.org) and is the name of the WHO Collaborating Centre for the International Drug Monitoring Program. ADR reports submitted to the UMC originate from different sources such as regulatory and voluntary
sources (health professionals, patients) as well as pharmaceutical companies, depending on the recording strategy of the reporting national pharmacovigilance center. The ADR data recorded in VigiBaseTM are thus heterogeneous in regard of their origin. In addition, the
performance of a causality assessment (that is the evaluation of the likelihood that the pharmaceutical product caused the reported ADR) is not performed by every reporting national pharmacovigilance database and therefore the ADR data of VigiBaseTM are heterogeneous also in
regard of the presence of a separate causality assessment. Finally, it is important to consider that the ADR data and their implications do not represent the opinion of the WHO. Recording of ADR data at the UMC has been performed since 1968.
Database query and search strategy: We requested data from the above-referenced database in September 2014 (index date) by an online application at the WHO. Data were searched and collected using the standardised Medical Dictionary for Regulatory Activities (MedDRA)
query (SMQ). The MedDRA15 is a clinically validated international medical terminology thesaurus/dictionary used by regulatory authorities; it features a hierarchical structure of its included terms (~SMQs). It was developed in the 1990s by the International Conference on
Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) in order to provide a highly specific standardised medical terminology to allow sharing of regulatory information internationally for medical products used by humans (see
http://www.meddra.org). The SMQ-term applied for the present search was “Hepatic disorders”; in order to facilitate maximum precision we retrieved data only for cases related to a subterm of that SMQ: "Hepatic disorders - comprehensive search" (narrow scope) (thus excluding
congenital, familial, neonatal and genetic disorders of the liver, as well as liver infections, hepatic disorders specifically reported as alcohol-related, and pregnancy-related hepatic disorders). Data retrieved from VigiBaseTM database covered the period 1968-2014 (May 2014). Data
were retrieved for the following substances: agomelatine, amineptine, amitriptyline, bupropion, citalopram, clomipramine, duloxetine, escitalopram, fluoxetine, fluvoxamine, hypericum perforatum, maprotiline, mianserin, milnacipran, mirtazapine, moclobemide, nefazodone,
nortriptyline, paroxetine, reboxetine, sertraline, tianeptine, tranylcypromine, trazodone, trimipramine, venlafaxine. Amineptine and nefazodone were used as positive control substances due to their known hepatoxicity that was primarily identified and proven by data mining
methods applied to spontaneous reporting systems. The absolute numbers of all ADR-reports (no SMQ-restriction) and ADR-reports related to the above mentioned SMQs were obtained for each substance and in total (for all substances) as recorded at the index date. Causality
assessment of the evaluated ADR reports was not performed, meaning that all degrees of causality were included. Statistical analysis was performed based on the total dataset, meaning that all reporting sources from different countries were included. As all ADR reports recorded
in the assessed database are reviewed by qualified personnel before definite recording in VigiBaseTM, the individual case narratives were not evaluated separately for plausibility. The applied data query strategy did not allow to retrieve information on individual ADR-reports (e.g.
age, sex, comedication etc.). Therefore, no case-specific data were available.
Statistical analysis: Within the framework of pharmacovigilance, the detection of signals indicating a possible causal relationship between an adverse event and the use of a drug is of high importance for the safety assessment of drugs in the post-marketing setting. The Council
for International Organizations of Medical Sciences (CIOMS) defines a signal as follows: "Information that arises from one or more multiple sources (incl. observations or experiments), which suggest a new potentially causal association, or a new aspect of a known association
between an intervention and an event or set of related events, either adverse or beneficial, that is judged to be of sufficient likelihood to justify verificatory action" ("Practical Aspects of Signal Detection in Pharmacovigilance; CIOMS Working Group VIII, Geneva 2010). Data-
mining methods applied to databases of spontaneous reports of ADR are frequently used in quantitative signal detection. A highly disproportionate representation of the combination of a drug and an adverse event may indicate an important safety signal based upon a difference
from the background frequency. In our analysis, we used a case/non-case approach and calculated the reporting odds ratios (ROR) as a measure of disproportionality in order to evaluate the strength of the relation between treatment with one of the above-mentioned
antidepressants and the occurrence of the event "hepatic disorder". Cases were defined as ADR-reports related to the SMQ "Drug related hepatic disorders - comprehensive search" (narrow scope), non-cases as ADR-reports other than related to the just mentioned SMQ. Exposure
was defined as the presence of any of the above mentioned substances in an ADR-report (regardless of the probability level concerning the causation of the ADR by the respective agent). The ROR was calculated with a 95% confidence interval (CI) and was based on a two-by-two
contingency table (ROR=(a/c)/(b/d)=ad/bc)). The 95% CI interval was calculated by: eln(ROR)±1.96√(1/a+1/b+1/c+1/d). RORs were calculated for each substance separately using the entire dataset (global perspective). Statistical analysis was performed with Microsoft® Office Excel 2003
(11.8404.8405) SP3.
DISCUSSION
In the present study, we sought to assess the statistical risk of hepatotoxicity related to
several antidepressive agents. Therefore, a quantitative signal detection was performed
using data from the Uppsala Monitoring Centre of the WHO that is the worldwide largest
pharmacovigilance database and records ADR data from worldwide sources.
The risk of hepatotocixity related to agomelatine is currently widely acknowledged and the
results of our study strengthen the hypothesis of AGM being an antidepressant with a
considerable risk for hepatotoxic ADR. Our findings correspond with results of a recent
pharmacovigilance study that applied the same method to several European
pharmacovigilance systems. In this study, AGM was statistically associated with
hepatotoxicity in Spain (ROR 4.9 [95% CI 2.4-9.7]), France (ROR 2.4 [95% CI 1.5-3.7])
and Italy (ROR 5.1 [95% CI 1.7-4.1]) (7).
The used data and applied method do generally not allow a quantitative evaluation of the
hepatotoxic properties of the assessed antidepressants. In fact, disproportionality analysis
does only allow to assess if there is a statistical association between an agent and a
particular ADR or not. Nevertheless, we could detect considerable substance-specific
differences in the risk of hepatotoxicity. These differences correspond with results of a
recent comprehensive review by Voican et al. (6). In this review, agomelatine, duloxetine,
nefazodone and tianeptine were found to be associated with a greater risk of hepatotoxicity,
whereas citalopram, escitalopram, fluvoxamine and paroxetine were evaluated to feature a
comparatively low potential to cause hepatotoxic ADR (6). In our study, the latter
substances exhibited ROR-values < 1 (thus indicating a "protective effect" on the
development of hepatotoxic ADR), while the former were consistently associated with ROR-
values > 1. Another finding, supporting the plausibility of the identified substance-specific
differences concerning the statistical risk of hepatotoxicity, is the missing statistical
association of reboxetine (no hepatic metabolism, exclusively renal excretion) and
hepatotoxicity (ROR 0.5 [95% CI 0.4-0.7]). As a matter of course, the detected substance-
specific differences concerning the statistical association with hepatotoxicity must not be
interpreted as a ranking of the real risk for hepatotoxicity associated with different
antidepressants.
Limitations: The drug safety information that can be generated using data from a
spontaneous reporting system is statistically very weak. This starts with the high diversity
of the data, continues with the missing causality assessment, the missing information on
the kind of and on the severity of the reported drug-related hepatic disorder, and does not
end with the reporting bias under an ongoing discussion on the respective ADR, particularly
in regard of agomelatine.
RESULTS
Both positive control substances, amineptine (ROR 38.4 [95% CI (33.8-43.6]) and nefazodone (ROR 3.2 [95% CI 3.0-3.5]), were statistically associated with hepatotoxicity.
Statistical associations with hepatotoxicity were also found for amitriptyline (ROR 1.5 [95% CI 1.4-3.6]), clomipramine (ROR 2.3 [95% CI 2.1-2.5]), duloxetine (ROR 2.7
[95% CI 2.6-2.8]), Hypericum perforatum (ROR 1.7 [95% CI 1.4-2.2]), maprotiline (ROR 1.3 [95% CI 1.1-1.5]), mianserin (ROR 3.6 [95% CI 3.3-3.9]), mirtazapine (ROR
1.5 [95% CI 1.4-1.6]), tianeptine (ROR 4.4 [95% CI 3.6-5.3]), and trimipramine (ROR 2.9 [95% CI 2.5-3.4)]. ROR-values and numbers of ADR-reports related to all
evaluated antidepressants are presented in table 1. Following amineptine, agomelatine (ROR 6.4 [95% CI 5.7-7.2]) exhibited the highest ROR-value (followed by tianeptine,
mianserin, and nefazodone) in comparison to all other evaluated antidepressants.
Table 1: Numbers of reports of hepatotoxic ADR related to particular
antidepressants, proportions in VigiBaseTM and reporting odds
ratios*
Substances
Number of ADR-reports/
proportion**
ROR (95% CI)
Agomelatine 334 (19.0%) 6.4 (5.7-7.2)
Amitriptyline 857 (5.2%) 1.5 (1.4-1.6)
Bupropion 591 (1.2%) 0.3 (0.3-0.4)
Citalopram 797 (3.2%) 0.9 (0.8-0.1.0)
Clomipramine 608 (7.2%) 2.3 (2.1-2.5)
Duloxetine 2341 (9.0%) 2.7 (2.6-2.8)
Escitalopram 379 (2.7%) 0.8 (0.7-0.8)
Fluoxetine 1854 (3.0%) 0.8 (0.8-0.9)
Fluvoxamine 297 (3.4%) 1.0 (0.9-1.1)
Hypericum perforatum 71 (6.0%) 1.7 (1.4-2.2)
Maprotiline 162 (4.5%) 1.3 (1.1-1.5)
Mianserin 618 (11.6%) 3.6 (3.3-3.9)
Milnacipran 74 (2.6%) 0.7 (0.6-0.9)
Mirtazapine 778 (5.2%) 1.5 (1.4-1.6)
Moclobemide 126 (3.3%) 1.0 (0.8-1.1)
Nortriptyline 172 (3.8%) 1.0 (0.9-1.3)
Paroxetine 1306 (2.2%) 0.6 (0.6-0.7)
Reboxetine 38 (1.7%) 0.5 (0.4-0.7)
Sertraline 1398 (2.9%) 0.8 (0.8-0.9)
Tianeptine 124 (13.9%) 4.4 (3.6-5.3)
Tranylcypromine 56 (3.7%) 1.1 (0.8-1.4)
Trazodone 386 (3.6%) 1.0 (0.9-1.1)
Trimipramine 177 (9.6%) 2.9 (2.5-3.4)
Venlafaxine 1297 (3.2%) 0.9 (0.86-1.0)
Positive control substances:
Amineptine 575 (58.5%) 38.4 (33.8-43.6)
Nefazodone 930 (10.6%) 3.2 (3.0-3.5)
Legend: ADR=adverse drug reaction; CI=confidence interval; ROR=reporting odds ratio;
SMQ=standardised Medical Dictionary for Regulatory Activities query; *=calculations
based on a total of n=9383954 ADR-reports in VigiBaseTM at the index date (n=332772
ADR-reports related to SMQ “Drug related hepatic disorders - comprehensive search;
narrow scope”); **=calculated by number of ADR-reports related to SMQ “Drug
related hepatic disorders - comprehensive search” (narrow scope) and associated with
the respective substance / number of all ADR-reports associated with the respective
substance x 100 [%].