Strategies for quantifying the relationship between medications and suicidal behaviour: what has been learned?
ABSTRACT In recent years there has been considerable concern that certain classes of drugs, for example antidepressants, may increase the risk of suicide. In this current opinion article, we examine the literature on methodological and statistical approaches to the design and analysis of suicidal event studies. Experimental, ecological and observational studies of the relationship between drugs and suicidal events (thoughts, attempts and completion) are discussed. Areas considered include analysis of spontaneous reporting system data, ecological trends in national and/or small area (e.g. county) suicide rates, meta-analyses of randomized clinical trials, and large-scale medical claims data. New statistical and experimental strategies for investigating possible associations between drugs and suicide are highlighted, and we suggest directions for future statistical/methodological research. To put this into context, we then review the most recent literature on the relationship between drugs (antidepressants, antiepileptics, varenicline, montelukast and antipsychotics) and suicidal events. Overall, there appears to be little evidence that drugs increase the risk of suicide and related behaviour. Numerous lines of evidence in adults clearly demonstrate that inadequate treatment of depression (pharmacotherapy and/or psychotherapy) is associated with increased risk of suicidal behaviour. In children, the results are less clear and further study is required to better delineate which children benefit from treatment and who may be at increased risk as a consequence of treatment. From a statistical and methodological perspective, the field of pharmacoepidemiology is a fertile area for statistical research, both in theory and in application. In general, methods have been adopted from other areas such as general epidemiology, despite the singular nature of many of the problems that are unique to drug safety in general, in particular the study of rare events. Finally, there is considerable debate concerning the communication of risk. For suicide, regulatory action has been taken largely on the basis of evidence suggesting increased risk of suicidal thoughts. However, suicidal thoughts are quite common, particularly among patients with depression, and may have little relationship to suicidal behaviour and/or completion.
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ABSTRACT: PurposeIn the 2004, FDA placed a black box warning on antidepressants for risk of suicidal thoughts and behavior in children and adolescents. The purpose of this paper is to examine the risk of suicide attempt and self-inflicted injury in depressed children ages 5–17 treated with antidepressants in two large observational datasets taking account time-varying confounding.METHODS We analyzed two large US medical claims databases (MarketScan and LifeLink) containing 221,028 youth (ages 5–17) with new episodes of depression, with and without antidepressant treatment during the period of 2004–2009. Subjects were followed for up to 180 days. Marginal structural models were used to adjust for time-dependent confounding.ResultsFor both datasets, significantly increased risk of suicide attempts and self-inflicted injury were seen during antidepressant treatment episodes in the unadjusted and simple covariate adjusted analyses. Marginal structural models revealed that the majority of the association is produced by dynamic confounding in the treatment selection process; estimated odds ratios were close to 1.0 consistent with the unadjusted and simple covariate adjusted association being a product of chance alone.Conclusions Our analysis suggests antidepressant treatment selection is a product of both static and dynamic patient characteristics. Lack of adjustment for treatment selection based on dynamic patient characteristics can lead to the appearance of an association between antidepressant treatment and suicide attempts and self-inflicted injury among youths in unadjusted and simple covariate adjusted analyses. Marginal structural models can be used to adjust for static and dynamic treatment selection processes such as that likely encountered in observational studies of associations between antidepressant treatment selection, suicide and related behaviors in youth. Copyright © 2014 John Wiley & Sons, Ltd.Pharmacoepidemiology and Drug Safety 09/2014; 24(2). DOI:10.1002/pds.3713 · 3.17 Impact Factor
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ABSTRACT: To investigate if the widely publicized warnings in 2003 from the US Food and Drug Administration about a possible increased risk of suicidality with antidepressant use in young people were associated with changes in antidepressant use, suicide attempts, and completed suicides among young people.BMJ Clinical Research 06/2014; 348:g3596. DOI:10.1136/bmj.g3596 · 14.09 Impact Factor
- Pharmacoepidemiology and Drug Safety 02/2014; 23(2):218-20. DOI:10.1002/pds.3551 · 3.17 Impact Factor