DÄ internationalArchive23/2018Frequent Adverse Drug Reactions, and Medication Groups under Suspicion

Original article

Frequent Adverse Drug Reactions, and Medication Groups under Suspicion

A descriptive analysis based on spontaneous reports to the German Federal Institute for Drugs and Medical Devices from 1978–2016

Dtsch Arztebl Int 2018; 115(23): 393-400; DOI: 10.3238/arztebl.2018.0393

Dubrall, D; Schmid, M; Alešik, E; Paeschke, N; Stingl, J; Sachs, B

Background: The adverse drug reaction database of the German Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte, BfArM) contains reports of suspected adverse drug reactions (ADRs) that are spontaneously submitted by physicians, pharmacists, or patients. The aim of the present study was a descriptive analysis of all of these spontaneous reports.

Methods: 345 662 spontaneously submitted reports were analyzed with respect to the number of reports per year, the sources of the reports, demographic variables, the most commonly reported ADRs, and the drug classes most commonly suspected.

Results: The number of reports submitted spontaneously each year has grown steadily since 1978. At the least detailed level of analysis, “drugs for the treatment of nervous system disorders” were the most common class of drugs under suspicion of causing the reported adverse drug reactions (23.1%). In a more detailed analysis by therapeutic subgroup, the three subgroups most commonly reported as suspected of causing side effects were antithrombotic agents, systemic antibiotics, and psycholeptics—causing thrombocytopenia, diarrhea, and drug dependency as the most frequently reported ADRs, respectively. The order of drug classes most commonly causing ADRs differed markedly between the physicians’ reports (diazepines, fluoroquinolones, heparins) and the patients’ reports (interferons, antithrombotic drugs, selective immunosuppressant drugs). Patients more commonly reported subjectively perceived ADRs, while physicians more commonly reported findings or diagnoses that require medical expertise.

Conclusion: The increasing number of spontaneous reports is mainly due to reports forwarded from pharmaceutical companies to the BfArM. This, in turn, is probably a result of increasingly strict legal reporting requirements in Germany. The detected differences between physicians’ and patients’ ADR reports can be taken to indicate that patients should be more specifically informed and questioned about potential ADRs. By reporting adverse drug reactions, physicians may improve drug safety.

One of the central tasks of the German Federal Institute for Drugs and Medical Devices (Bundesinstituts für Arzneimittel und Medizinprodukte, BfArM) is to monitor the safety of medicinal products. An essential methodological element in the regulatory monitoring of medicinal product safety is the spontaneous reporting system (13). Spontaneous reports are unsolicited reports by physicians, pharmacists, patients, or other sources, of suspected cases of adverse drug reactions (ADRs) with widespread, everyday use of a medicinal product, which is not in the context of systematic investigations (for example, studies).

Spontaneous reports play an important role, as clinical trials prior to medicinal product approval can include only a limited number of selected patients. The limitations of these studies means that rare ADRs, as well as those that only occur in certain vulnerable patients or after prolonged use, cannot be reliably detected (1, 2, 4, 5). Additionally, new ADRs may occur during the drug lifecycle, such as in the event of other indications for use or novel co-medications (1, 6).

Complementary, active programs for medicinal product safety monitoring have increasingly been developed in the past decade, including the analysis of so-called Big Data (7) (from electronic health records [from insurance companies], scientific literature, and social media). These systems, like the spontaneous reporting system, are subject to method-inherent limitations (7, 8). Thus, analysis of spontaneous reports still is of central importance (3, 79).

Signals from spontaneous reports can provide a major impetus for regulatory action (for instance, leading to changes in product information or to new studies) (10). A 2013 study found that 44% (11/25) of safety-related withdrawals of medicinal products in the USA or the EU were due to spontaneous reports (1).

In Germany, spontaneous reports can be submitted directly to the competent federal authorities via the BfArM/ Paul-Ehrlich-Institut (PEI) website according to the respective area of responsibility (BfArM, chemically-defined active substances, among others; PEI, monoclonal antibodies and vaccines, among others) (11, 12 , 13). However, reports may also be directed to the medicinal product commissions of the drug commissions of healthcare professions or to pharmaceutical companies, which then forward them (14). Physicians are required by their professional code to report ADRs (15). An overview of what physicians should be aware of when reporting ADRs is given in eBox 1.

What should physicians be aware of when reporting ADRs?
What should physicians be aware of when reporting ADRs?
eBox 1
What should physicians be aware of when reporting ADRs?

Since 22 November 2017, pharmaceutical companies send their reports exclusively to the European database EudraVigilance at the European Medicines Agency (EMA) (16, 17) (restricted access rights: www.adrreports.eu/en/access_policy.html). The BfArM forwards the adverse reaction reports that it receives directly (e.g. from physicians) to EudraVigilance. Future analyses within the framework of monitoring medicinal product safety will be carried out in EudraVigilance; country-specific analyses are also possible. Therefore, direct reports, e.g. from physicians and pharmacists in Germany, to the BfArM continue to be of great importance, as these may differ from ADR reports from other EU countries, for example due to difference in frequency of use of medicinal products.

The aim of this investigation was to determine the importance of ADR reports and databases for ensuring safety of medicinal product use by carrying out a retrospective descriptive analysis of all spontaneous reports contained in the adverse drug reaction database.

Methods

The starting point of the analysis comprised of all suspected ADR reports contained in BfArM’s adverse drug reaction database, from the first registration in 1978 until 31 December 2016 (N = 528 539). Of these suspected ADR reports, about 70% (n = 369 778) were spontaneous reports, about 28.2% (n = 149 034) were from systematic investigations/studies (“solicited reports”), and about 1.8% (n = 9728) were of unclear origin. This analysis only included spontaneous reports within Germany of ADRs due to suspected or interacting medicinal product(s) (herein termed “drugs under suspicion”) that did not report unintended use. The final analysis dataset contained 345 662 spontaneous reports (65.4% of all reports of the ADR database, and 93.5% of all spontaneous reports) (eFigure 1, eMethods).

Flow chart depicting generation of final dataset
Flow chart depicting generation of final dataset
eFigure 1
Flow chart depicting generation of final dataset

All spontaneous reports were of suspected ADRs of medicinal products. Case numbers were determined by computer-based database queries; no single-case evaluation was performed (for example, for causality assessment). Active substances are coded in the ADR database according to the official classification for active pharmacologically ingredients according to the ATC code (anatomic therapeutic chemical classification system) (18) (eFigure 2) and the World Health Organization‘s Drug Dictionary (19), and ADRs according to MedDRA terminology (MedDRA, Medical Dictionary for Regulatory Activities) (20) (eMethods). Suitable hierarchy levels were selected for each evaluation.

Description and schematic depiction of ATC* (anatomical, therapeutic, chemical) classification using morphine as an example
Description and schematic depiction of ATC* (anatomical, therapeutic, chemical) classification using morphine as an example
eFigure 2
Description and schematic depiction of ATC* (anatomical, therapeutic, chemical) classification using morphine as an example

The primary reporting source provides information from whom the report originated (e.g. physician) regardless of the reporting channel (e.g. pharmaceutical company). Healthcare professionals (HCPs) are defined as those with medical qualifications; this includes physicians, pharmacists, and nurses (21). Consumers and non-HCPs are defined as people who are not HCPs; this includes patients and relatives (herein referred to as “patients”). Ratios were calculated as appropriate to investigate possible associations between the number of reports and population size (22), number of prescriptions (23), or number of physicians (24) in Germany.

The classification “serious adverse drug reaction” takes into account criteria from the legal definition (e.g., it results in death, is life-threatening, requires inpatient hospitalization, results in permanent disability, and/or is a congenital anomaly). These criteria differ from clinical criteria (11).

Approval for the study protocol was obtained from the ethics committee of the Medical Faculty of the Rheinische Friedrich-Wilhelms-Universität Bonn (Lfd. Nr. 009/17).

Results

The 345 662 spontaneous reports comprised more than 904 242 ADRs, which were associated with 421 581 drugs under suspicion or combinations of drugs under suspicion. The primary reporting sources were physicians (64.1%; 221 427) and pharmacists (10.3%; 35 776), other HCPs (2.6%; 9011), patients (9.5%; 32 992), and lawyers (0.6%; 2138).

The total number of spontaneous reports per year has been rising steadily since 1978 (Figure 1). Reporting from physicians has had a slower rate of increase since 2002; in contrast, reporting has noticeably increased from pharmacists and other HCPs since 2005, and from patients since 2008. Reporting from lawyers show peak levels that can be traced back to special factors (for example, the case of rofecoxib in 2007).

Number of spontaneous reports received per year according to primary reporting source
Number of spontaneous reports received per year according to primary reporting source
Figure 1
Number of spontaneous reports received per year according to primary reporting source

The time course of spontaneous reports in total and of those sent to the BfArM by pharmaceutical companies has been very similar since 1988 (Figure 2). In contrast, there are no clear associations between the increasing number of spontaneous reports and changes in population size (22), prescription data (23), or the number of working physicians (24) (Figure 3).

Number of spontaneous reports per year that are forwarded by pharmaceutical companies to the German Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte, BfArM)
Number of spontaneous reports per year that are forwarded by pharmaceutical companies to the German Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte, BfArM)
Figure 2
Number of spontaneous reports per year that are forwarded by pharmaceutical companies to the German Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte, BfArM)
Quotient of spon- FIGURE 3 taneous reports per 100 000 population, per 100 000 prescriptions, or per 100 physicians, over time
Quotient of spon- FIGURE 3 taneous reports per 100 000 population, per 100 000 prescriptions, or per 100 physicians, over time
Figure 3
Quotient of spon- FIGURE 3 taneous reports per 100 000 population, per 100 000 prescriptions, or per 100 physicians, over time

The observed increase in the number of spontaneous reports from 1989 to 1996 is not reflected in the number of spontaneous reports sent to the BfArM from other sources. This increase could therefore be the result of other statutory reporting obligations in this period (25), as pharmaceutical companies also were required to report non-serious ADRs to the BfArM during that time (eBox 2).

ADR reporting by pharmaceutical companies
ADR reporting by pharmaceutical companies
eBox 2
ADR reporting by pharmaceutical companies

Around 66.9% of all spontaneous reports are classified as serious (11). The proportion of spontaneous reports including the serious criterion “fatal” was 5.5%.

Stratification according to patient age shows a continuous increase in accumulated reports for patients from 11 to 70 years of age (eFigure 3). The most spontaneous reports refer to the age group 66–70 years.

Stratification of spontaneous reports by age and sex
Stratification of spontaneous reports by age and sex
eFigure 3
Stratification of spontaneous reports by age and sex

Overall, 54.6% of spontaneous reports refer to females, and 38.8%, refer to males (with 6.6% not specified). For children aged ≤ 15 years, more spontaneous reports are made for males.

For this age group the most frequent ADRs are for the drug group of “nervous system disorders” with the most reports for the subgroup of “psychostimulants, ADHD medication, and nootropics” (11.9%, 830). The most commonly reported ADRs are aggression (6.1%; 51), suicidal thoughts (6.1%; 51), and headache (5.9%; 49).

For adolescent women (> 15 to ≤ 20 years), the most frequent ADRs are for the drug group of “hormonal contraceptives for systemic use” (23.7%; 1046). The most commonly reported ADRs are pulmonary embolism (20.1%; 217), deep vein thrombosis (17.4%; 182), and pelvic vein thrombosis (11.9%; 124).

The three ADRs that were cumulatively reported most frequently for all groups (irrespective of age or sex) during the observation period were nausea, pruritus, and dizziness (eTable 1). Many other nonspecific general symptoms (such as vomiting, headache, and pyrexia) are also among the 15 most common ADRs. Three of these 15 ADRs are visible cutaneous ADRs (skin rash, erythema, and urticaria); two others (hypersensitivity and pruritus) may show visible cutaneous symptoms.

The 15 most frequently reported ADRs in the generated dataset
The 15 most frequently reported ADRs in the generated dataset
eTable 1
The 15 most frequently reported ADRs in the generated dataset

If the reported drugs under suspicion are analyzed at the highest hierarchical level of the ATC drug groups, the drugs for nervous system disorders are clearly in first place (23.1%), as four of the ten most reported therapeutic subgroups, all of which are listed in Table 1 (psycholeptics, psychoanaleptics [antidepressants], analgesics, and antiepileptics) are comprised in this drug group. This is followed by drugs for the treatment of cardiovascular disorders (13.0%) and “antineoplastics and immunomodulating agents” (12.4%) (eTable 2).

The most frequently reported medication groups under suspicion, and their most frequently reported ADRs, in the total dataset (N = 345 662)
The most frequently reported medication groups under suspicion, and their most frequently reported ADRs, in the total dataset (N = 345 662)
Table 1
The most frequently reported medication groups under suspicion, and their most frequently reported ADRs, in the total dataset (N = 345 662)
The ten most frequently reported medication groups under suspicion at the top level
The ten most frequently reported medication groups under suspicion at the top level
eTable 2
The ten most frequently reported medication groups under suspicion at the top level

Table 1 shows the ten therapeutic subgroups that are most frequently reported as suspicious, with their most commonly reported ADRs. The aim of this study was to obtain a descriptive analysis of all spontaneous reports. Therefore, Table 1 lists many known associations, such as bleeding events related to antithrombotic agents.

Reported ADRs from physicians and patients are similar in terms of the most commonly reported ADRs but differ in ranking (eTable 3). However, among the 50 ADRs most frequently reported by physicians, those that are typically diagnosed by physicians, such as specific diagnoses (e.g., pulmonary embolism, ranked #35) and laboratory findings (e.g., leukopenia, ranked #14), are prevalent. In contrast, ADRs reported by patients are mainly those that can be subjectively perceived (e.g., anxiety, ranked #29; taste disturbances, ranked #45) and/or those that limit individual quality of life (e.g., weight increased, ranked #40; alopecia, ranked #28). This distinction is also evident when the medicinal products most frequently reported by either physicians or patient are directly compared (Table 2). On average, patients report more ADRs per report than physicians (3.5 versus 2.5) as well as more serious ADRs (75.6% versus 65.8%). Only three of the drug groups most frequently reported by physicians as suspicious were also among the top ten from patients. Notably, patients were more likely than physicians to report immunostimulants (e.g., interferons, ranked #1) and contraceptives (progestogens and estrogens, fixed combination, ranked #5; intrauterine contraceptives, ranked #6); these were ranked #18, #16, and #21, respectively, by physicians.

Physician reports (n = 221 427) compared to patient reports (n = 32 992): Comparison of the most frequently reported ADRs in the ten most frequently reported medication groups under suspicion (based on physician reporting)*1
Physician reports (n = 221 427) compared to patient reports (n = 32 992): Comparison of the most frequently reported ADRs in the ten most frequently reported medication groups under suspicion (based on physician reporting)*1
Table 2
Physician reports (n = 221 427) compared to patient reports (n = 32 992): Comparison of the most frequently reported ADRs in the ten most frequently reported medication groups under suspicion (based on physician reporting)*1
The ten most frequent ADRs reported by physicians and patients
The ten most frequent ADRs reported by physicians and patients
eTable 3
The ten most frequent ADRs reported by physicians and patients

Discussion

To our knowledge, this is the first and largest cumulative evaluation of spontaneous reports from Germany in the BfArM adverse drug reaction database, and it revealed a continuous increase in reports from 1978 to 2016. Furthermore, the number of reports increased with patient age (11–70 years), and more reports involving women. The three most commonly reported medication groups (with the most common ADRs in parentheses) were: antithrombotic agents (thrombocytopenia, gastrointestinal hemorrhage, and hemorrhage), antibacterials for systemic use (diarrhea, skin rash, and pruritus), and psycholeptics (drug dependence, leukopenia, and pyrexia).

The steady increase in number of spontaneous reports in the BfArM database is mainly due to more reports being sent to the BfArM by pharmaceutical companies. Various factors could be behind this, such as a general increase in willingness to report by physicians and patients (as primary reporting sources); this could be due to increased awareness of ADRs and of reporting options, and having more information sources (Internet). However, the proportion of direct reports to the BfArM (spontaneous reports without reports from pharmaceutical companies) did not show a comparably strong increase (Figure 2). Likewise, there was no clear association between the increase in spontaneous reports and population size, the number of prescriptions made, or the number of working physicians (Figure 3), although certain limitations must be taken into account (eBox 3). Therefore, modified or tightened legal requirements for reporting ADR reports to the BfArM were probably more important for increasing the number of reports sent to the BfArM by the pharmaceutical companies (eBox 3).

Limitations on the evaluation of the time course of the quotient of spontaneous reports per 100 000 population, 100 000 prescriptions, and 100 physicians in Germany
Limitations on the evaluation of the time course of the quotient of spontaneous reports per 100 000 population, 100 000 prescriptions, and 100 physicians in Germany
eBox 3
Limitations on the evaluation of the time course of the quotient of spontaneous reports per 100 000 population, 100 000 prescriptions, and 100 physicians in Germany

About every tenth spontaneous report comes from a patient. Reports from this source have increased substantially since 2008. This could be due to increased sensitivity to the topic due to high-profile medicinal product scandals, the possibility since 2009 to report ADRs online to the BfArM, and the calls for reporting suspected ADRs in the package leaflet (26). Patients in other European countries also have reported more frequently over time (27, 28).

The relatively high proportion of reports classified as serious (66.9%) (11) is likely due to regulatory reporting requirements for pharmaceutical companies. It is not possible to determine how many ADRs were fatal, as the calculated proportion (5.5%) does not provide any statement about the cause of death. In other words, many reports do not indicate whether death was due to the ADR itself, to the consequences of the ADR, or to underlying diseases.

ADRs are known to increase with age (from 11 to 70 years) (2931) and may be due to increased medicinal product use in older people (32, 33). A higher risk of ADRs in older people may also be the result of comorbidity, polymedication, and/or decreased liver or kidney function (32, 3436).

A prevalence of the female sex in ADR reports (54.6% versus 38.8%) has also been described previously in other analyses (2931). Explanations for this could be more frequent visits to the physician by women (34, 37), a higher use of medicines by women (29, 33), and sex differences in pharmacokinetics (38).

Thirteen of the 15 most commonly reported ADRs were nonspecific general symptoms. This could be due to the fact that, in addition to the ADR leading to the report, nonspecific general symptoms associated with the main ADR were (co-)reported and therefore appeared overly frequently in the analysis.

One-fifth of the most common ADRs are cutaneous, and one-third of the reported ADRs were related to skin. Adverse drug reactions should therefore be considered when making a differential diagnosis of skin lesions.

It is striking that in our study, as well as in other studies (29, 31), “medicinal products for the treatment of the nervous system disorders” were most frequently reported as suspect in the top-level drug groups. However, based on these data, no conclusions can be made about whether these medicines actually cause more ADRs or are only reported more frequently, as the corresponding frequency of use is not known (among other reasons). Nonetheless, in Germany in the period from 2008 to 2011, the highest prevalence of medicinal product use was observed for treating cardiovascular disorders (28.4%), followed by varia (22.5%), and then for nervous system disorders (21.2%) (33).

The importance of medical expertise becomes clear with regard to ADRs typically determined by a physician, such as specific diagnoses (pulmonary embolism) or laboratory findings (thrombocytopenia). Patients, on the other hand, are more likely than physicians to report ADRs that are subjectively perceived, as well as those that may be of particular importance to their personal quality of life (for example, weight changes, sleep disorders, or alopecia). In this respect, patient reports can be an important supplement to reports from physicians. Furthermore, ADRs that affect the patient’s quality of life may affect adherence. Together with an appropriate patient education, patient knowledge about such ADRs and their significance can be relevant to the success of a therapy.

The benefits of the spontaneous reporting system include monitoring the full spectrum of medicinal products (including over-the-counter [OTC] medications), a large population coverage that includes high-risk groups (e.g., children and pregnant women), and acquisition without a time limit. Among the inherent limitations of the spontaneous reporting system is underreporting (3, 14, 39); while this is estimated to be around 90% (40), it depends on the type, severity, and familiarity of the ADR, and of the drug under suspicion (old/new), as was shown in a German study (e1). Other limitations include partially incomplete documentation of case reports and the inability to determine ADR frequency.

The BfArM regularly informs about new risks identified within the framework of medicinal product safety monitoring. Analysis of spontaneous reports contributes substantially to risk recognition of new medical products and can provide the basis for a range of various regulatory measures, such as intensified surveillance, obligation of studies, inclusion of new contraindications in the product information of medicinal products, and revocation of authorization.

Examples of BfArM measures that were based on spontaneous reports include:

  • changes in monitoring requirements due to progressive multifocal leukoencephalopathy with the use of fumarates (e2);
  • obligation to determine liver values during treatment with kava-kava–containing medicinal products due to hepatotoxic events (e3);
  • withdrawal of approval of topically applied bufexamac-containing medicinal products due to contact allergic reactions (e4).

As regulatory measures required to ensure medicinal product safety are based on relevant data and information, ADR reports and the quality of these reports are of major importance for medicinal produce safety. Therefore, the BfArM would also like to use this article to strongly encourage reporting of suspected ADRs (14).

Acknowledgments
We would like to thank the teams responsible for “database search” and “processing/capturing of ADR reports” from the Division of Pharmacovigilance at the BfArM.

We also thank our colleagues at the Institute for Medical Biometry, Informatics, and Epidemiology (IMBIE) at the University Hospital of Bonn for their support.


Conflict of interest statement
The authors declare that no conflict of interest exists.

Manuscript received on 9 October 2017, revised version accepted on 29 March 2018.

Translated from the original German by Veronica A. Raker, PhD.


Corresponding author
Prof. Dr. med. Bernhardt Sachs
German Federal Institute for Drugs and Medical Devices (BfArM)
Kurt-Georg-Kiesinger Allee 3
53175 Bonn, Germany

Supplementary material
For eReferences please refer to:
www.aerzteblatt-international.de/ref2318

eBoxes, eFigures, eTables, eMethods:
www.aerzteblatt-international.de/18m0393

1.
Coloma PM, Trifirò G, Patadia V, Sturkenboom M: Postmarketing safety surveillance: where does signal detection using electronic healthcare records fit into the big picture? Drug Saf 2013; 36: 183–97 CrossRef MEDLINE
2.
Paludetto MN, Olivier-Abbal P, Montastruc JL: Is spontaneous reporting always the most important information supporting drug withdrawals for pharmacovigilance reasons in France? Pharmacoepidemiol Drug Saf 2012; 21: 1289–94 CrossRef MEDLINE
3.
Huang YL, Moon J, Segal JB: A comparison of active adverse event surveillance systems worldwide. Drug Saf 2014; 37: 581–96 CrossRef MEDLINE PubMed Central
4.
Hoffman KB, Dimbil M, Erdman CB, Tatonetti NP, Overstreet BM: The Weber effect and the United States Food and Drug Administration’s Adverse Event Reporting System (FAERS): analysis of sixty-two drugs approved from 2006 to 2010. Drug Saf 2014; 37: 283–94 CrossRef MEDLINE PubMed Central
5.
Amery WK: Why there is a need for pharmacovigilance. Pharmacoepidemiol Drug Saf 1999; 8: 61–4 CrossRef
6.
Pacurariu AC, Coloma PM, van Haren A, Genov G, Sturkenboom MC, Straus SM: A description of signals during the first 18 months of the EMA pharmacovigilance risk assessment committee. Drug Saf 2014; 37: 1059–66 CrossRef MEDLINE
7.
Harpaz R, DuMochel W, Shah NH: Big data and adverse drug reaction detection. Clin Pharmacol & Ther 2016; 99: 268–70 CrossRef MEDLINE
8.
Pacurariu AC, Straus SM, Trifirò G, et al.: Useful interplay between spontaneous ADR reports and electronic healthcare records in signal detection. Drug Saf 2015; 38: 1201–10 CrossRef MEDLINE PubMed Central
9.
Robb MA, Racoosin JA, Sherman RE, et al.: The US Food and Drug Administration‘s Sentinel Initiative: expanding the horizons of medical product safety. Pharmacoepidemiol Drug Saf 2012; 21: 9–11 CrossRef MEDLINE
10.
European Medicines Agency: Guideline on good pharmacovigilance practices (GVP). Module IX — signal management (Rev 1). www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2017/10/WC500236408.pdf (last accessed on 9 October 2017).
11.
Arzneimittelgesetz: Gesetz über den Verkehr mit Arzneimitteln (Arzneimittelgesetz – AMG). Arzneimittelgesetz in der Fassung der Bekanntmachung vom 12. Dezember 2005 (BGBl. I S. 3394), zuletzt geändert durch Artikel 5 des GKV-Arzneimittelversorgungsstärkungsgesetzes (AMVSG) vom 4. Mai 2017 (BGBl. I S. 1050).
12.
Bundesinstitut für Arzneimittel und Medizinprodukte (BfArM): Nebenwirkungsmeldung durch Angehörige der Heilberufe. www.bfarm.de/SharedDocs/Formulare/DE/Arzneimittel/Pharmakovigilanz/aa-uaw-melde-bogen.pdf?__blob=publicationFile&v=17.
13.
Paul-Ehrlich-Institut (PEI): Meldung von Verdachtsfällen unerwünschter Arzneimittelwirkungen und Impfkomplikationen. www.pei.de/DE/infos/fachkreise/meldeformulare-fach/meldeformulare-fach-node.html (last accessed on 17 April 2018).
14.
Stammschulte T, Pachl H, Gundert-Remy U, et al.: Einführung in die Grundlagen der Pharmakovigilanz (Teil II): Spontanmeldesystem zur Erfassung von Verdachtsfällen unerwünschter Arzneimittelwirkungen (UAW). Bulletin zur Arzneimittelsicherheit 2010; 4: 18–26.
15.
Bundes­ärzte­kammer: (Muster-)Berufsordnung für die in Deutschland tätigen Ärztinnen und Ärzte – MBO-Ä 1997 – in der Fassung des Beschlusses des 118. Deutschen Ärztetages 2015 in Frankfurt am Main, Stand: 27.05.2015.
16.
European Medicines Agency: EudraVigilance. www.ema.europa.eu/ema/index.jsp?curl=pages/regulation/general/general_content_000679.jsp&mid=WC0b01ac05800250b5 (last accessed on 17 April 2018).
17.
EudraVigilance. Häufig gestellte Fragen rund um das Meldesystem. www.adrreports.eu/de/faqs.html (last accessed on 17 April 2018).
18.
Deutsches Institut für Medizinische Dokumentation und Information (DIMDI): Anatomisch-Therapeutisch-Chemische (ATC) Klassifikation. www.dimdi.de/static/de/amg/atcddd/index.htm (last accessed on 17 April 2018).
19.
WHO Collaborating Centre for Drug Statistics Methodology: Anatomisch-Therapeutisch-Chemische (ATC) Klassifikation. www.whocc.no/atc_ddd_index/ (last accessed on 17 April 2018).
20.
MedDRA: Medical Dictionary for Regulatory Activities. www.meddra.org/how-to-use/support-documentation (last accessed on 17 April 2018).
21.
European Medicines Agency: Guideline on good pharmacovigilance practices (GVP). Module VI — Collection, management and submission of reports of suspected adverse reactions to medicinal products (Rev 2). www.ema.europa.eu/docs/en_GB/document_library/Regulatory_and_procedural_guideline/2017/08/WC500232767.pdf (last accessed on 28 July 2017).
22.
Statistisches Bundesamt: Bevölkerungsstand. www.destatis.de/DE/ZahlenFakten/GesellschaftStaat/Bevoelkerung/Bevoelkerungsstand/Tabellen_/lrbev03.html (last accessed on 17 April 2018).
23.
Schwabe U, Ludwig WD: Arzneiverordnungen 2016 im Überblick. In: Schwabe U, Paffrath D, Ludwig WD, Klauber J (eds.): Arzneiverordnungsreport 2017. Berlin, Heidelberg: Springer 2017; 3–32 CrossRef CrossRef
24.
Bundes­ärzte­kammer: Ärztestatistik zum 31. Dezember 2016. www.bundesaerztekammer.de/fileadmin/user_upload/downloads/pdf-Ordner/Statistik2016/Stat16AbbTab.pdf (last accessed on 17 April 2018).
25.
Einführung der Meldepflicht 1987 und Bekanntmachung dazu vom 28.10.1987. Anzeige von Nebenwirkungen, Wechselwirkungen mit anderen Arzneimitteln und Arzneimittelmissbrauch nach §2 Abs. Satz 2 AMG vom 28.10.1987.
26.
Gemeinsame Bekanntmachung über die zu verwendenden Standardsätze in der Fachinformation und Packungsbeilage zum Berichten von Nebenwirkungen sowie für Arzneimittel, die einer zusätzlichen Überwachung unterliegen, gemäß § 11 Absatz 1b und § 11a Absatz 1 Satz 9 des Arzneimittelgesetzes (AMG), vom 3. Juli 2013. www.bfarm.de/SharedDocs/Bekanntmachungen/DE/Pharmakovigilanz/bm-phvig-20130807-standardsaetze.pdf?__blob=publicationFile&v=6 (last accessed on 17 April 2018).
27.
Inch J, Watson MC, Anakwe-Umeh S: Patient versus healthcare professional spontaneous adverse drug reaction reporting: a systematic review. Drug Saf 2012; 35: 807–18 CrossRef
28.
European Medicines Agency: Annual Report 2016. www.ema.europa.eu/docs/en_GB/document_library/Annual_report/2017/05/WC500227334.pdf (last accessed on 17 April 2018).
29.
Thiessard F, Roux E, Miremont-Salame G, et al.: Trends in spontaneous adverse drug reaction reports to the French pharmacovigilance system (1986–2001). Drug Saf 2005; 28: 731–40 CrossRef MEDLINE
30.
Ozcan G, Aykac E, Kasap Y, Nemutlu NT, Sen E, Aydinkarahaliloglu ND: Adverse drug reaction reporting pattern in Turkey: analysis of the national database in the context of the first pharmacovigilance legislation. Drugs Real World Outcomes 2016; 3: 33–43 CrossRef MEDLINE
31.
Aagaard L, Strandell J, Melskens L, Petersen PS, Holme Hansen E: Global patterns of adverse drug reactions over a decade. Drug Saf 2012; 35: 1171–82 CrossRef MEDLINE
32.
Alhawassi TM, Krass I, Bajorek BV, Pont LG: A systematic review of the prevalence and risk factors for adverse drug reactions in the elderly in the acute care setting. Clin Interv Aging 2014; 9: 2079–86 MEDLINE PubMed Central
33.
Knopf H, Grams D: Arzneimittelanwendung von Erwachsenen in Deutschland: Ergebnisse der Studie zur Gesundheit Erwachsener in Deutschland (DEGS1). Bundesgesundheitsbl 2013; 56: 868–77 CrossRef MEDLINE
34.
Telschow C, Schröder M: Arzneimittelverordnungen nach Alter und Geschlecht. In: Schwabe U, Paffrath D, Ludwig WD, Klauber J (eds.): Arzneiverordnungs-Report 2017. Berlin, Heidelberg: Springer 2017; 783–792.
35.
Klotz U: Pharmacokinetics and drug metabolism in the elderly. Drug Metab Rev 2009; 41: 67–76 CrossRef MEDLINE
36.
Hämmerlein A, Derendorf H, Lowenthal DT: Pharmacokinetic and pharmacodynamic changes in the elderly. Clin Pharmacokinet 1998; 35: 49–64 CrossRef MEDLINE
37.
Glaeske G, Gerdau-Heitmann C, Höfel F, Schicktanz C: „Gender-specific drug prescription in Germany“ results from prescription analysis. In: Regitz-Zagrosek V (ed.): Sex and gender differences in pharmacology. Berlin, Heidelberg: Springer 2012; 149–67 MEDLINE
38.
Zopf Y, Rabe C, Neubert A, et al.: Gender-based differences in drug prescription: relation to adverse drug reactions. Pharmacology 2009; 84: 333–9 CrossRef MEDLINE
39.
Lütkehermölle W, Paeschke N: Einführung in die Grundlagen der Pharmakovigilanz (Teil I) – Verdachtsfälle von unerwünschten Arzneimittelwirkungen. Bulletin zur Arzneimittelsicherheit 2010; 1: 14–7.
40.
Hazell L, Shakir SA: Under-reporting of adverse drug reactions. Drug Saf 2006; 29: 385–96 CrossRef
e1.
Hasford J, Goettler M, Munter KH, Müller-Oerlinghausen B: Physicians’ knowledge and attitudes regarding the spontaneous reporting system for adverse drug reactions. J Clin Epidemiol 2002; 55: 945–50 CrossRef
e2.
BfArM: Dimethylfumarathaltige Arzneimittel und progressive multifokale Leukencephalopathie (PML). Stand: 7. April 2015. www.bfarm.de/SharedDocs/Risikoinformationen/Pharmakovigilanz/DE/RI/2015/RI-dimethylfumarat.html (last accessed on 17 April 2018).
e3.
BfArM: Kava-Kava, Widerruf der Zulassung. Stand: 31. August 2015. www.bfarm.de/SharedDocs/Risikoinformationen/Pharmakovigilanz/DE/RV_STP/g-l/kavakava3.html (last accessed on 17 April 2018).
e4.
BfArM: Bufexamac-haltige Arzneimittel: Kontaktallergische Reaktionen. Feststellungsbescheid. Stand 5. Mai 2010. www.bfarm.de/SharedDocs/Risikoinformationen/Pharmakovigilanz/DE/RV_STP/a-f/bufexamac.html (last accessed on 17 April 2018).
e5.
BfArM: Glossar: over the counter OTC. www.bfarm.de/SharedDocs/Glossareintraege/DE/O/OTC.html (last accessed on 17 April 2018).
e6.
MedDRA: Standardised MedDRA queries. www.meddra.org/standardised-meddra-queries (last accessed on 17 April 2018).
e7.
Farzan J: Neue Pharmakovigilanz-Gesetzgebung in der EU. Bulletin zur Arzneimittelsicherheit 2011; 3: 14–7.
e8.
BfArM: Glossar: Schwarzes Dreieck. www.bfarm.de/SharedDocs/Glossareintraege/DE/S/Schwarzes_Dreieck.html (last accessed on 17 April 2018).
German Federal Institute for Drugs and Medical Devices (BfArM), Bonn, Germany: Diana Dubrall,
Dr. med. vet. Eva Alešik, Dr. med. Norbert Paeschke, Prof. Dr. med. Julia Stingl, Prof. Dr. med. Bernhardt Sachs
Institute for Medical Biometry, Informatics, and Epidemiology (IMBIE), University Hospital of Bonn, German: Diana Dubrall, Prof. Dr. rer. nat. Matthias Schmid
Center for Translational Medicine, Universität Bonn, Germany: Prof. Dr. med. Julia Stingl
Clinic for Dermatology and Allergology, University Hospital (RWTH), Aachen, Germany: Prof. Dr. med. Bernhardt Sachs
Number of spontaneous reports received per year according to primary reporting source
Number of spontaneous reports received per year according to primary reporting source
Figure 1
Number of spontaneous reports received per year according to primary reporting source
Number of spontaneous reports per year that are forwarded by pharmaceutical companies to the German Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte, BfArM)
Number of spontaneous reports per year that are forwarded by pharmaceutical companies to the German Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte, BfArM)
Figure 2
Number of spontaneous reports per year that are forwarded by pharmaceutical companies to the German Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte, BfArM)
Quotient of spon- FIGURE 3 taneous reports per 100 000 population, per 100 000 prescriptions, or per 100 physicians, over time
Quotient of spon- FIGURE 3 taneous reports per 100 000 population, per 100 000 prescriptions, or per 100 physicians, over time
Figure 3
Quotient of spon- FIGURE 3 taneous reports per 100 000 population, per 100 000 prescriptions, or per 100 physicians, over time
Key messages
The most frequently reported medication groups under suspicion, and their most frequently reported ADRs, in the total dataset (N = 345 662)
The most frequently reported medication groups under suspicion, and their most frequently reported ADRs, in the total dataset (N = 345 662)
Table 1
The most frequently reported medication groups under suspicion, and their most frequently reported ADRs, in the total dataset (N = 345 662)
Physician reports (n = 221 427) compared to patient reports (n = 32 992): Comparison of the most frequently reported ADRs in the ten most frequently reported medication groups under suspicion (based on physician reporting)*1
Physician reports (n = 221 427) compared to patient reports (n = 32 992): Comparison of the most frequently reported ADRs in the ten most frequently reported medication groups under suspicion (based on physician reporting)*1
Table 2
Physician reports (n = 221 427) compared to patient reports (n = 32 992): Comparison of the most frequently reported ADRs in the ten most frequently reported medication groups under suspicion (based on physician reporting)*1
What should physicians be aware of when reporting ADRs?
What should physicians be aware of when reporting ADRs?
eBox 1
What should physicians be aware of when reporting ADRs?
ADR reporting by pharmaceutical companies
ADR reporting by pharmaceutical companies
eBox 2
ADR reporting by pharmaceutical companies
Limitations on the evaluation of the time course of the quotient of spontaneous reports per 100 000 population, 100 000 prescriptions, and 100 physicians in Germany
Limitations on the evaluation of the time course of the quotient of spontaneous reports per 100 000 population, 100 000 prescriptions, and 100 physicians in Germany
eBox 3
Limitations on the evaluation of the time course of the quotient of spontaneous reports per 100 000 population, 100 000 prescriptions, and 100 physicians in Germany
Flow chart depicting generation of final dataset
Flow chart depicting generation of final dataset
eFigure 1
Flow chart depicting generation of final dataset
Description and schematic depiction of ATC* (anatomical, therapeutic, chemical) classification using morphine as an example
Description and schematic depiction of ATC* (anatomical, therapeutic, chemical) classification using morphine as an example
eFigure 2
Description and schematic depiction of ATC* (anatomical, therapeutic, chemical) classification using morphine as an example
Stratification of spontaneous reports by age and sex
Stratification of spontaneous reports by age and sex
eFigure 3
Stratification of spontaneous reports by age and sex
The 15 most frequently reported ADRs in the generated dataset
The 15 most frequently reported ADRs in the generated dataset
eTable 1
The 15 most frequently reported ADRs in the generated dataset
The ten most frequently reported medication groups under suspicion at the top level
The ten most frequently reported medication groups under suspicion at the top level
eTable 2
The ten most frequently reported medication groups under suspicion at the top level
The ten most frequent ADRs reported by physicians and patients
The ten most frequent ADRs reported by physicians and patients
eTable 3
The ten most frequent ADRs reported by physicians and patients
1.Coloma PM, Trifirò G, Patadia V, Sturkenboom M: Postmarketing safety surveillance: where does signal detection using electronic healthcare records fit into the big picture? Drug Saf 2013; 36: 183–97 CrossRef MEDLINE
2.Paludetto MN, Olivier-Abbal P, Montastruc JL: Is spontaneous reporting always the most important information supporting drug withdrawals for pharmacovigilance reasons in France? Pharmacoepidemiol Drug Saf 2012; 21: 1289–94 CrossRef MEDLINE
3.Huang YL, Moon J, Segal JB: A comparison of active adverse event surveillance systems worldwide. Drug Saf 2014; 37: 581–96 CrossRef MEDLINE PubMed Central
4.Hoffman KB, Dimbil M, Erdman CB, Tatonetti NP, Overstreet BM: The Weber effect and the United States Food and Drug Administration’s Adverse Event Reporting System (FAERS): analysis of sixty-two drugs approved from 2006 to 2010. Drug Saf 2014; 37: 283–94 CrossRef MEDLINE PubMed Central
5.Amery WK: Why there is a need for pharmacovigilance. Pharmacoepidemiol Drug Saf 1999; 8: 61–4 CrossRef
6.Pacurariu AC, Coloma PM, van Haren A, Genov G, Sturkenboom MC, Straus SM: A description of signals during the first 18 months of the EMA pharmacovigilance risk assessment committee. Drug Saf 2014; 37: 1059–66 CrossRef MEDLINE
7.Harpaz R, DuMochel W, Shah NH: Big data and adverse drug reaction detection. Clin Pharmacol & Ther 2016; 99: 268–70 CrossRef MEDLINE
8.Pacurariu AC, Straus SM, Trifirò G, et al.: Useful interplay between spontaneous ADR reports and electronic healthcare records in signal detection. Drug Saf 2015; 38: 1201–10 CrossRef MEDLINE PubMed Central
9.Robb MA, Racoosin JA, Sherman RE, et al.: The US Food and Drug Administration‘s Sentinel Initiative: expanding the horizons of medical product safety. Pharmacoepidemiol Drug Saf 2012; 21: 9–11 CrossRef MEDLINE
10.European Medicines Agency: Guideline on good pharmacovigilance practices (GVP). Module IX — signal management (Rev 1). www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2017/10/WC500236408.pdf (last accessed on 9 October 2017).
11.Arzneimittelgesetz: Gesetz über den Verkehr mit Arzneimitteln (Arzneimittelgesetz – AMG). Arzneimittelgesetz in der Fassung der Bekanntmachung vom 12. Dezember 2005 (BGBl. I S. 3394), zuletzt geändert durch Artikel 5 des GKV-Arzneimittelversorgungsstärkungsgesetzes (AMVSG) vom 4. Mai 2017 (BGBl. I S. 1050).
12.Bundesinstitut für Arzneimittel und Medizinprodukte (BfArM): Nebenwirkungsmeldung durch Angehörige der Heilberufe. www.bfarm.de/SharedDocs/Formulare/DE/Arzneimittel/Pharmakovigilanz/aa-uaw-melde-bogen.pdf?__blob=publicationFile&v=17.
13.Paul-Ehrlich-Institut (PEI): Meldung von Verdachtsfällen unerwünschter Arzneimittelwirkungen und Impfkomplikationen. www.pei.de/DE/infos/fachkreise/meldeformulare-fach/meldeformulare-fach-node.html (last accessed on 17 April 2018).
14.Stammschulte T, Pachl H, Gundert-Remy U, et al.: Einführung in die Grundlagen der Pharmakovigilanz (Teil II): Spontanmeldesystem zur Erfassung von Verdachtsfällen unerwünschter Arzneimittelwirkungen (UAW). Bulletin zur Arzneimittelsicherheit 2010; 4: 18–26.
15.Bundes­ärzte­kammer: (Muster-)Berufsordnung für die in Deutschland tätigen Ärztinnen und Ärzte – MBO-Ä 1997 – in der Fassung des Beschlusses des 118. Deutschen Ärztetages 2015 in Frankfurt am Main, Stand: 27.05.2015.
16.European Medicines Agency: EudraVigilance. www.ema.europa.eu/ema/index.jsp?curl=pages/regulation/general/general_content_000679.jsp&mid=WC0b01ac05800250b5 (last accessed on 17 April 2018).
17.EudraVigilance. Häufig gestellte Fragen rund um das Meldesystem. www.adrreports.eu/de/faqs.html (last accessed on 17 April 2018).
18.Deutsches Institut für Medizinische Dokumentation und Information (DIMDI): Anatomisch-Therapeutisch-Chemische (ATC) Klassifikation. www.dimdi.de/static/de/amg/atcddd/index.htm (last accessed on 17 April 2018).
19.WHO Collaborating Centre for Drug Statistics Methodology: Anatomisch-Therapeutisch-Chemische (ATC) Klassifikation. www.whocc.no/atc_ddd_index/ (last accessed on 17 April 2018).
20.MedDRA: Medical Dictionary for Regulatory Activities. www.meddra.org/how-to-use/support-documentation (last accessed on 17 April 2018).
21.European Medicines Agency: Guideline on good pharmacovigilance practices (GVP). Module VI — Collection, management and submission of reports of suspected adverse reactions to medicinal products (Rev 2). www.ema.europa.eu/docs/en_GB/document_library/Regulatory_and_procedural_guideline/2017/08/WC500232767.pdf (last accessed on 28 July 2017).
22.Statistisches Bundesamt: Bevölkerungsstand. www.destatis.de/DE/ZahlenFakten/GesellschaftStaat/Bevoelkerung/Bevoelkerungsstand/Tabellen_/lrbev03.html (last accessed on 17 April 2018).
23.Schwabe U, Ludwig WD: Arzneiverordnungen 2016 im Überblick. In: Schwabe U, Paffrath D, Ludwig WD, Klauber J (eds.): Arzneiverordnungsreport 2017. Berlin, Heidelberg: Springer 2017; 3–32 CrossRef CrossRef
24.Bundes­ärzte­kammer: Ärztestatistik zum 31. Dezember 2016. www.bundesaerztekammer.de/fileadmin/user_upload/downloads/pdf-Ordner/Statistik2016/Stat16AbbTab.pdf (last accessed on 17 April 2018).
25.Einführung der Meldepflicht 1987 und Bekanntmachung dazu vom 28.10.1987. Anzeige von Nebenwirkungen, Wechselwirkungen mit anderen Arzneimitteln und Arzneimittelmissbrauch nach §2 Abs. Satz 2 AMG vom 28.10.1987.
26.Gemeinsame Bekanntmachung über die zu verwendenden Standardsätze in der Fachinformation und Packungsbeilage zum Berichten von Nebenwirkungen sowie für Arzneimittel, die einer zusätzlichen Überwachung unterliegen, gemäß § 11 Absatz 1b und § 11a Absatz 1 Satz 9 des Arzneimittelgesetzes (AMG), vom 3. Juli 2013. www.bfarm.de/SharedDocs/Bekanntmachungen/DE/Pharmakovigilanz/bm-phvig-20130807-standardsaetze.pdf?__blob=publicationFile&v=6 (last accessed on 17 April 2018).
27.Inch J, Watson MC, Anakwe-Umeh S: Patient versus healthcare professional spontaneous adverse drug reaction reporting: a systematic review. Drug Saf 2012; 35: 807–18 CrossRef
28.European Medicines Agency: Annual Report 2016. www.ema.europa.eu/docs/en_GB/document_library/Annual_report/2017/05/WC500227334.pdf (last accessed on 17 April 2018).
29.Thiessard F, Roux E, Miremont-Salame G, et al.: Trends in spontaneous adverse drug reaction reports to the French pharmacovigilance system (1986–2001). Drug Saf 2005; 28: 731–40 CrossRef MEDLINE
30.Ozcan G, Aykac E, Kasap Y, Nemutlu NT, Sen E, Aydinkarahaliloglu ND: Adverse drug reaction reporting pattern in Turkey: analysis of the national database in the context of the first pharmacovigilance legislation. Drugs Real World Outcomes 2016; 3: 33–43 CrossRef MEDLINE
31.Aagaard L, Strandell J, Melskens L, Petersen PS, Holme Hansen E: Global patterns of adverse drug reactions over a decade. Drug Saf 2012; 35: 1171–82 CrossRef MEDLINE
32.Alhawassi TM, Krass I, Bajorek BV, Pont LG: A systematic review of the prevalence and risk factors for adverse drug reactions in the elderly in the acute care setting. Clin Interv Aging 2014; 9: 2079–86 MEDLINE PubMed Central
33.Knopf H, Grams D: Arzneimittelanwendung von Erwachsenen in Deutschland: Ergebnisse der Studie zur Gesundheit Erwachsener in Deutschland (DEGS1). Bundesgesundheitsbl 2013; 56: 868–77 CrossRef MEDLINE
34.Telschow C, Schröder M: Arzneimittelverordnungen nach Alter und Geschlecht. In: Schwabe U, Paffrath D, Ludwig WD, Klauber J (eds.): Arzneiverordnungs-Report 2017. Berlin, Heidelberg: Springer 2017; 783–792.
35.Klotz U: Pharmacokinetics and drug metabolism in the elderly. Drug Metab Rev 2009; 41: 67–76 CrossRef MEDLINE
36.Hämmerlein A, Derendorf H, Lowenthal DT: Pharmacokinetic and pharmacodynamic changes in the elderly. Clin Pharmacokinet 1998; 35: 49–64 CrossRef MEDLINE
37.Glaeske G, Gerdau-Heitmann C, Höfel F, Schicktanz C: „Gender-specific drug prescription in Germany“ results from prescription analysis. In: Regitz-Zagrosek V (ed.): Sex and gender differences in pharmacology. Berlin, Heidelberg: Springer 2012; 149–67 MEDLINE
38.Zopf Y, Rabe C, Neubert A, et al.: Gender-based differences in drug prescription: relation to adverse drug reactions. Pharmacology 2009; 84: 333–9 CrossRef MEDLINE
39.Lütkehermölle W, Paeschke N: Einführung in die Grundlagen der Pharmakovigilanz (Teil I) – Verdachtsfälle von unerwünschten Arzneimittelwirkungen. Bulletin zur Arzneimittelsicherheit 2010; 1: 14–7.
40.Hazell L, Shakir SA: Under-reporting of adverse drug reactions. Drug Saf 2006; 29: 385–96 CrossRef
e1.Hasford J, Goettler M, Munter KH, Müller-Oerlinghausen B: Physicians’ knowledge and attitudes regarding the spontaneous reporting system for adverse drug reactions. J Clin Epidemiol 2002; 55: 945–50 CrossRef
e2.BfArM: Dimethylfumarathaltige Arzneimittel und progressive multifokale Leukencephalopathie (PML). Stand: 7. April 2015. www.bfarm.de/SharedDocs/Risikoinformationen/Pharmakovigilanz/DE/RI/2015/RI-dimethylfumarat.html (last accessed on 17 April 2018).
e3.BfArM: Kava-Kava, Widerruf der Zulassung. Stand: 31. August 2015. www.bfarm.de/SharedDocs/Risikoinformationen/Pharmakovigilanz/DE/RV_STP/g-l/kavakava3.html (last accessed on 17 April 2018).
e4.BfArM: Bufexamac-haltige Arzneimittel: Kontaktallergische Reaktionen. Feststellungsbescheid. Stand 5. Mai 2010. www.bfarm.de/SharedDocs/Risikoinformationen/Pharmakovigilanz/DE/RV_STP/a-f/bufexamac.html (last accessed on 17 April 2018).
e5.BfArM: Glossar: over the counter OTC. www.bfarm.de/SharedDocs/Glossareintraege/DE/O/OTC.html (last accessed on 17 April 2018).
e6.MedDRA: Standardised MedDRA queries. www.meddra.org/standardised-meddra-queries (last accessed on 17 April 2018).
e7.Farzan J: Neue Pharmakovigilanz-Gesetzgebung in der EU. Bulletin zur Arzneimittelsicherheit 2011; 3: 14–7.
e8.BfArM: Glossar: Schwarzes Dreieck. www.bfarm.de/SharedDocs/Glossareintraege/DE/S/Schwarzes_Dreieck.html (last accessed on 17 April 2018).