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David M Coulter a Centre for Adverse
Reactions Monitoring and Intensive Medicines Monitoring Programme,
Department of Preventive and Social Medicine, University of Otago,
Dunedin, New Zealand, b Uppsala Monitoring Centre,
WHO Collaborating Centre for International Drug Monitoring, S-75320
Uppsala, Sweden
Correspondence to: I R Edwards ralph.edwards{at}who-umc.org
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Abstract |
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Objectives:
To examine the relation between
antipsychotic drugs and myocarditis and cardiomyopathy.
The antipsychotic drug clozapine has been reported to cause
myocarditis or cardiomyopathy.
1 2
other drugs in the same therapeutic class may share similar toxicity. Data mining of a large
database of suspected adverse reactions can find such new signals. As
part of the World Health Organization's programme for international
drug monitoring, national pharmacovigilance centres in 60 countries
report adverse reactions to a central database maintained by the
Uppsala Monitoring Centre in Sweden.3
To analyse this large database an approach using bayesian statistics
implemented in a neural network architecture has been developed. The
approach is able to look for new adverse reactions from combinations of
drugs and also to identify previously unknown patterns, such as risk
factors for adverse events with specific drugs We used the bayesian confidence propagation network, which
implements bayesian statistics in a neural network architecture, in the
WHO database. The network was used to test reports of clozapine and all
other antipsychotic drugs suspected of causing myocarditis or
cardiomyopathy against a background of all reports in the database. We
calculated the strength of dependency between a drug (or drug group)
and adverse reaction using a logarithmic measure of disproportionality called the information component.4 An association between
the drug and the reaction was considered significant if the information component minus 2 standard deviations was positive. The value of the
information component is based on the number of case reports for
drug(s) "x" (Cx); the number of case reports of adverse reaction(s) "y" (Cy); the number of reports of the specific combination (Cxy); and the total number of reports (C). Further details of the methods are
available on the BMJ 's website.
Myocarditis and cardiomyopathy were reported rarely as suspected
adverse drug reactions, accounting for less than 0.1% (2121) of almost
2.5 million reports. The table shows the antipsychotic drugs
reported to have caused either myocarditis or cardiomyopathy on two or
more occasions. Clozapine has a much higher information component than
other antipsychotics together and than the general background database.
Most reports predated recent publicity about clozapine. The statistical
associations of clozapine with myocarditis and cardiomyopathy
individually were also significant. The group of other antipsychotics
drugs was significantly associated with myocarditis and cardiomyopathy
together (table) and individually compared with the general database,
although these associations were much weaker than for
clozapine.
Design:
Data mining using bayesian statistics
implemented in a neural network architecture.
Setting:
International database on adverse drug
reactions run by the World Health Organization programme for
international drug monitoring.
Main outcome measures:
Reports mentioning
antipsychotic drugs, cardiomyopathy, or myocarditis.
Results:
A strong signal existed for an association between clozapine and cardiomyopathy and myocarditis. An association was also seen with other antipsychotics as a group. The association was
based on sufficient cases with adequate documentation and apparent lack
of confounding to constitute a signal. Associations between myocarditis
or cardiomyopathy and lithium, chlorpromazine, fluphenazine,
haloperidol, and risperidone need further investigation.
Conclusions:
Some antipsychotic drugs seem to be
linked to cardiomyopathy and myocarditis. The study shows the potential of bayesian neural networks in analysing data on drug safety.
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Introduction
Top
Abstract
Introduction
Methods
Results
Discussion
References
for example, patient
age, underlying diseases, and drug interactions. We used the bayesian
approach to look for cardiac effects related to antipsychotic drugs in
the WHO database of adverse reactions.
![]()
Methods
Top
Abstract
Introduction
Methods
Results
Discussion
References
![]()
Results
Top
Abstract
Introduction
Methods
Results
Discussion
References
Chlorpromazine, lithium, and fluphenazine were significantly associated
with myocarditis and cardiomyopathy. The 16 cases with risperidone were
not more than expected given the high overall reporting of the drug in
the database. Chlorpromazine was also significantly associated with
myocarditis and cardiomyopathy separately. Lithium, fluphenazine, and
risperidone were significantly associated with cardiomyopathy but not
myocarditis. In contrast, haloperidol was associated with myocarditis
but not cardiomyopathy.
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Discussion |
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Our analysis suggests that antipsychotic drugs other than clozapine may be associated with myocarditis and cardiomyopathy. The findings may have three explanations. The conditions for which antipsychotics are used could be risk factors for myocarditis and cardiomyopathy; the antipsychotic drug could be an innocent bystander; or there may be a causal association. Despite patients taking clozapine being intensively monitored for agranulocytosis, the former two are unlikely explanations for the strong relation between clozapine and myocarditis and cardiomyopathy.5 The association with clozapine cannot be explained by coprescribed drugs. In some of the cases in the other antipsychotics group the patient was also taking clozapine or non-antipsychotic drugs known to cause myocarditis or cardiomyopathy. However, standardised clinical evaluation6 shows that there were sufficient cases with adequate documentation and apparent lack of confounding to constitute a signal for cardiomyopathy or myocarditis in the other antipsychotics identified above.
Choice of methods
Our results were obtained by a data mining approach. A concern had
been raised about myocarditis with clozapine. We then examined the
association between the group of antipsychotics with myocarditis or
cardiomyopathy. Having discovered a quantitative association between
the antipsychotics group and cardiomyopathy and myocarditis, we
investigated individual antipsychotic drugs and then performed a case
by case analysis. Our study shows that data mining can be used
successfully to detect signals of adverse reactions in the WHO
database.
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What is known on this topic
Clozapine has been reported to be associated with myocarditis and cardiomyopathy What this study addsThe WHO database shows that clozapine is significantly more frequently reported in relation to cardiomyopathy and myocarditis than other drugs Myocarditis and cardiomyopathy were also particularly associated with chlorpromazine, lithium, fluphenazine, risperidone, and haloperidol These associations need to be investigated further to establish whether they are causal Data mining is a useful tool in pharmacovigilance |
Implications
The summaries of case histories in the database do not allow us to
draw definite conclusions about the likelihood of the possible causes
of the associations we observed between antipsychotic drugs and
myocarditis and cardiomyopathy. Adverse drug reactions are greatly
underreported worldwide. Further study is needed to determine if
antipsychotics other than clozapine cause myocarditis or
cardiomyopathy, particularly lithium, chlorpromazine, fluphenazine,
haloperidol, and risperidone, and to consider the comparative risks and
effectiveness of antipsychotics. This is especially important given the
recent finding that older and newer drugs have similar
efficacy.9 Antipsychotic drugs should also be considered
in unexplained sudden deaths in psychotic patients.
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Acknowledgments |
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We thank the national centres that contribute data to the WHO international drug monitoring programme. The opinions and conclusions, however, are not necessarily those of the various national centres or of the WHO. Roland Orre was central in developing the bayesian confidence propagation neural network as a routine tool for signal detection in the WHO database of drug adverse reactions.
Contributors: DMC suggested the study and made a provisional investigation of the data, AB and IRE planned and designed the study; AB carried out the study; and IRE, AB, and ML evaluated the results. RHBM drafted the first report of the study, AB and IRE wrote the paper, and all authors contributed to modifying the manuscript and the final editing of the paper. IRE is the guarantor.
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Footnotes |
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Funding: None.
Competing interests: None declared.
Details of the methods are
available on the BMJ's website
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References |
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| 1. | Jensen VE, Gotzsche O. Allergic myocarditis in clozapine treatment. Ugeskrift for Laeger 1994; 156: 4151-4152[Medline]. |
| 2. | Killian JG, Kerr K, Lawrence C, Celermajer DS. Myocarditis and cardiomyopathy associated with clozapine. Lancet 1999; 354: 1841-1845[CrossRef][Medline]. |
| 3. | Olsson S. The role of the WHO programme on international drug monitoring in coordinating worldwide drug safety efforts. Drug Safety 1998; 19: 1-10[CrossRef][Medline]. |
| 4. | Bate A, Lindquist M, Edwards IR, Olsson S, Orre R, Lansner A, et al. A Bayesian neural network method for adverse drug reaction signal generation. Eur J Clin Pharmacol 1998; 54: 315-321[Medline]. |
| 5. | Honigfeld G, Arellano F, Sethi J, Bianchini A, Schein J. Reducing clozapine-related morbidity and mortality: 5 years of experience with the clozaril national registry. J Clin Psychiatry 1998; 59(suppl 3): 3-7. |
| 6. | Edwards IR, Lindquist M, Wiholm B-E, Napke E. Quality criteria for early signals of possible adverse drug reactions. Lancet 1990; 336: 156-158[Medline]. |
| 7. | Hand DJ. Statistics and data mining: intersecting disciplines. SIGKDD Explorations 1999; 1: 16-19. |
| 8. |
Edwards IR.
Adverse drug reactions: finding the needle in the haystack.
BMJ
1997;
315:
500 |
| 9. |
Geddes J, Freemantle N, Harrison P, Bebbington P.
Atypical antipsychotics in the treatment of schizophrenia: systematic overview and meta-regression analysis.
BMJ
2000;
321:
1371-1376 |
(Accepted 20 February 2001)
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