What we can learn from a PLOS Medicine study of antidepressants and violent crime

Update October 1 7:58 PM: I corrected an inaccuracy in response to a comment by DJ Jaffe, for which I am thankful.

An impressively large-scale study published in PLOS Medicine of the association between antidepressants and violent crime is being greeted with strong opinions from those who haven’t read it. But even those who attempt to read the article might miss some of the nuances and the ambiguity that its results provide.

2305701220_0fc3d01183_bIn this issue of Mind the Brain, we will explore some of these nuances, which are fascinating in themselves. But the article also provides excellent opportunities to apply the critical appraisal skills needed for correlational observational studies using administrative data sets.

Any time there is a report of a mass shooting in the media, a motley crew of commentators immediately announces that the shooter is mentally ill and has been taking psychotropic medication. Mental illness and drugs are the problem, not guns, we are told. Sprinkled among the commentators are opponents of gun-control, Scientologists, and psychiatrists seeking to make money serving as expert witnesses. They are paid handsomely to argue for the diminished responsibility for the shooter or for product liability suits against Pharma. Rebuttals will be offered by often equally biased commentators, some of them receiving funds from Pharma.

every major shoorting
This is not from the Onion, but a comment left at a blog that expresses a commonly held view.

guns-health-care-82880109353

What is generally lost is that most shooters are not mentally ill and are not taking psychotropic medication.

Yet such recurring stories in the media have created a strong impression in the public and even professionals that a large scientific literature exists which establishes a tie between antidepressant use and violence.

Even when there has been some exposure to psychotropic medication, its causal role in the shooting cannot be established either from the facts of the case or the scientific literature.

The existing literature is seriously limited in quality and quantity and contradictory in its conclusions. Ecological studies [ 1, 2,]  conclude that the availability of antidepressants may reduce violence on a community level. An “expert review” and a review of reports of adverse events conclude there is a link between antidepressants and violence. However, reports of adverse events being submitted to regulatory agencies can be strongly biased, including by recent claims in the media. Reviews of adverse events do not distinguish between correlates of a condition like depression and effects of the drug being used to treat it. Moreover, authors of these particular reviews were serving as expert witnesses in legal proceedings. Authorship adds to their credibility and publicizes their services.

The recent study in PLOS Medicine should command the attention of anyone interested in the link between antidepressants and violent crime. Already there have been many tweets and at least one media story claiming vindication of the Scientologists as being right all along  I expected the release of the study and its reaction in the media would give me another opportunity to call attention to the entrenched opposing sides in the antidepressant wars  who only claim to be driven by strength of evidence and dismiss any evidence contrary to their beliefs, as well as the gullibility of journalists. But the article and its coverage in the media are developing a very different story.

At the outset, I should say I don’t know if evidence can be assembled for an unambiguous case that antidepressants are strongly linked to violent crime. Give up on us ever been able to rely on a randomized trial in which we examine whether participants randomized to receiving an antidepressant rather than a placebo are convicted more often for violent crimes. Most persons receiving antidepressant will not be convicted for a violent crime. The overall base rate of convictions is too low to monitor as an outcome a randomized trial. We are left having to sort through correlational observational, clinical epidemiological data typically collected for other purposes.

I’m skeptical about there being a link strong enough to send a clear signal through all the noise in the data sets that we can assemble to look for it. But the PLOS Medicine article represents a step forward.

stop Association does not equal causation
From Health News Review

Correlation does not equal causality.

Any conceivable data set in which we can search will pose the challenges of competing explanations from other variables that might explain the association.

  • Most obviously, persons prescribed antidepressants suffer from conditions that may themselves increase the likelihood of violence.
  • The timing of persons seeking treatment with antidepressants may be influenced by circumstances that increase their likelihood of violence.
  • Violent persons are more likely to be under the influence of alcohol and other drugs and to have histories of use of these substances.
  • Persons taking antidepressants and consuming alcohol and other drugs may be prone to adverse effects of the combination.
  • Violent persons have characteristics and may be in circumstances with a host of other influences that may explain their behavior.
  • Violent persons may themselves be facing victimization that increases the likelihood of their committing violence and having a condition warranting treatment with antidepressants.

Etc, etc.

The PLOS Medicine article introduces a number of other interesting possibilities for such confounding.

Statistical controls are never perfect

Studies will always incompletely specify of confounds and imperfectly measure them. Keep in mind that completeness of statistical control requires that all possible confounding factors be identified and measured without error. These ideal conditions are not attainable. Yet any application of statistics to “control” confounds that do not meet these ideal conditions risks producing less accurate estimate of effects than simply examining basic associations. Yet, we already know that these simple associations are not sufficient to indicate causality.

The PLOS Medicine article doesn’t provide definitive answers, but it presents data with greater sophistication than has previously been available. The article’s careful writing should make misinterpretation or missing of its main points less likely. And one of the authors – Professor Seena Fazel of the Department of Psychiatry, Oxford University – did an exemplary job of delivering careful messages to any journalist who would listen.

Professor Seena Fazel
Professor Seena Fazel

Professor Fazel can be found explaining his study in the media at 8:45 in a downloadable BBC World New Health Check News mp3.

Delving into the details of the article

The PLOS Medicine article is of course open access and freely available.

Molero, Y., Lichtenstein, P., Zetterqvist, J., Gumpert, C. H., & Fazel, S. (2015). Selective Serotonin Reuptake Inhibitors and Violent Crime: A Cohort Study. PLoS Med, 12(9), e1001875.

Supplementary material are also available from the web [1, 2, 3] for the study including a completed standardized STROBE checklist of items  that should be included in reports of observational studies, additional tables, and details of the variables and how they were obtained.

An incredible sample

Out of Sweden’s total population of 7,917,854 aged 15 and older in 2006, the researchers identified 856,493 individuals who were prescribed a selective serotonin reuptake inhibitor (SSRI) antidepressant from 2006-2009 and compared them to the 7,061,361 Swedish individuals who were not been prescribed this medication in that four year period.

SSRIs  were chosen for study because they represent the bulk of antidepressants being prescribed and also because SSRIs are the class of antidepressants to which the question of an association with violence of the most often raised. Primary hypotheses were about the SSRIs as a group, but secondary analyses focused on individual SSRIs – fluoxetine, citalopram, paroxetine, sertraline, fluvoxamine, and escitalopram. It was not expected that the analyses at the level of individual SSRI drugs have sufficient statistical power to explore associations with violent crimes. Data were also collected on non-SSRI antidepressants and other psychotropic medication, and these data were used to adjust for medications taken concurrently with SSRIs.

With these individuals’ unique identification number, the researchers collected information on the particular medications and dates of prescription from the Swedish Prescribed Drug Register. The register provides complete data on all prescribed and dispensed medical drugs from all pharmacies in Sweden since July 2005. The unique identification number also allowed obtaining information concerning hospitalizations and outpatient visits and reasons for visit and diagnoses.

crime sceneThese data were then matched against information on convictions for violent crimes for the same period from the Swedish national crime register.

These individuals were followed from January 1, 2006, to December 31, 2009.

During this period 1% of individuals prescribed an SSRI were convicted of a violent crime versus .6% of those not being prescribed an SSRI. The article focused on the extent to which prescription of an SSRI affected the likelihood of committing a violent crime and considered other possibilities for any association that was found.

A clever analytic strategy

Epidemiologic studies most commonly make comparisons between individuals differing in their exposures to particular conditions in terms of whether they have particular outcomes. Detecting bona fide causal associations can be derailed by other characteristics being associated with both antidepressants and violent crimes. An example of a spurious relationship is one between coffee drinking and cardiovascular disease. Exposure to coffee may be associated with lung cancer, but the association is spurious, due to smokers smoking Confoundinglighting up when they have coffee breaks. Taking smoking into account eliminates the association of coffee and cardiovascular disease. In practice, it can be difficult to identify such confounds, particularly when they are left unmeasured or imperfectly measured.

So, such Between-individual analyses of people taking antidepressants and those who are not are subject to a full range of unmeasured, but potentially confounding background variables.

For instance, in an earlier study in the same population, some of these authors found that individuals with a full (adjusted OR 1.5, 95% CI 1.3-1.6) or half (adjusted OR 1.2, 95% CI 1.1-1.4) sibling with depression were themselves more likely to be convicted of violent crime, after controlling for age, sex, low family income and being born abroad. The influence of such familial risk can be misconstrued in a standard between-individual analysis.

This article supplemented between-individual analyses with within-individual stratified Cox proportional hazards regressions. Each individual exposed to antidepressants was considered separately and served as his/her own control. Thus, these within-individual analyses examined differences in violent crimes in the same individuals over time periods differing in whether they had exposure to an antidepressant prescription. Periods of exposure became the unit of analysis, not just individuals.

The linked Swedish data sets that were used are unusually rich. It would not be feasible to obtain such data in other countries, and certainly not the United States.

The results as summarized in the abstract

Using within-individual models, there was an overall association between SSRIs and violent crime convictions (hazard ratio [HR] = 1.19, 95% CI 1.08–1.32, p < 0.001, absolute risk = 1.0%). With age stratification, there was a significant association between SSRIs and violent crime convictions for individuals aged 15 to 24 y (HR = 1.43, 95% CI 1.19–1.73, p < 0.001, absolute risk = 3.0%). However, there were no significant associations in those aged 25–34 y (HR = 1.20, 95% CI 0.95–1.52, p = 0.125, absolute risk = 1.6%), in those aged 35–44 y (HR = 1.06, 95% CI 0.83–1.35, p = 0.666, absolute risk = 1.2%), or in those aged 45 y or older (HR = 1.07, 95% CI 0.84–1.35, p = 0.594, absolute risk = 0.3%). Associations in those aged 15 to 24 y were also found for violent crime arrests with preliminary investigations (HR = 1.28, 95% CI 1.16–1.41, p < 0.001), non-violent crime convictions (HR = 1.22, 95% CI 1.10–1.34, p < 0.001), non-violent crime arrests (HR = 1.13, 95% CI 1.07–1.20, p < 0.001), non-fatal injuries from accidents (HR = 1.29, 95% CI 1.22–1.36, p < 0.001), and emergency inpatient or outpatient treatment for alcohol intoxication or misuse (HR = 1.98, 95% CI 1.76–2.21, p < 0.001). With age and sex stratification, there was a significant association between SSRIs and violent crime convictions for males aged 15 to 24 y (HR = 1.40, 95% CI 1.13–1.73, p = 0.002) and females aged 15 to 24 y (HR = 1.75, 95% CI 1.08–2.84, p = 0.023). However, there were no significant associations in those aged 25 y or older. One important limitation is that we were unable to fully account for time-varying factors.

Hazard ratios (HRs) are explained hereand are not to be confused with odds ratios (ORs) explained here. Absolute risk (AR) is the most intuitive and easy to understand measure of risk and is explained here, along with reasons that hazard ratios don’t tell you anything about absolute risk.

Principal findings

  • There was an association between receiving a prescription for antidepressants and violent crime.
  • When age differences were examined, the 15-24 age range was the only one from which the association was significant.
  • No association was found for other age groups.
  • The association held for both males and females analyze separately in the 15 – 24 age range. But…

Things not to be missed in the details

Only a small minority of persons prescribed an antidepressant were convicted of a violent crime, but the likelihood of a conviction in persons exposed to antidepressants was increased in this 15 to 24 age range.

There isn’t a dose-response association between SSRI use and convictions for violent crimes. Even in the 15 to 24 age range, periods of moderate or high exposure to SSRIs were not associated with violent crimes any more than no exposure. Rather, the association occurred only in those individuals with low exposure.

A dose response association would be reflected in the more exposure to antidepressants an individual had, the greater the level of violent crimes. A dose response association is a formal criterion for a causal association adequate evidence of a causal relationship between an incidence and a possible consequence.

In the age bracket for which this association between antidepressant use and conviction of a violent crime was significant, antidepressant use was also associated with an increased risk of violent crime arrests, non-violent crime convictions, and non-violent crime arrests, using emergency inpatient and or outpatient treatment for alcohol intoxication or misuse.

Major caveats

The use of linked administrative data sets concerning both antidepressant prescription and violent crimes is a special strength of this study. It allows a nuanced look at an important question with evidence that could not otherwise be assembled. But administrative data have well-known limitations.

The data were not originally captured with the research questions in mind and so key variables, including data concerning potential confounds were not necessarily collected. The quality control for the administrative purposes for which these data were collected, may differ greatly from what is needed in their use as research data. There may be systematic errors and incomplete data and inaccurate coding, including of the timing of these administrative events.

Administrative data do not always mesh well with the concepts with which we may be most concerned. This study does not directly assess violent behavior, only arrest and convictions. Most violent behavior does not result in an arrest or conviction and so this is a biased proxy for behavior.

This study does not directly assess diagnosis of depression, only diagnosis by specialists. We know from other studies that in primary and specialty medical settings, there may be no systematic effort to assess clinical depression by interview. The diagnoses that are recorded may simply be only serve to justify a clinical decision made on the basis other than a patient meeting research criteria for depression. Table 1 in the article suggests that only about a quarter of the patients exposed to antidepressants actually had a diagnosis of depression. And throughout this article, there was no distinction made between unipolar depression and the depressed phase of a bipolar disorder. This distinction may be important, given the small minority of individuals who were convicted of a violent crime while exposed to a SSRI.

Alcohol-and-Anti-DepressantsPerhaps one of the greatest weaknesses of this data set is its limited assessment of alcohol and substance use and abuse. For alcohol, we are limited to emergency inpatient or outpatient treatment for alcohol intoxication or misuse. For substance abuse, we have only convictions designated as substance-related. These are poor proxies for more common actual alcohol and substance use, which for a variety of reasons may not show up in these administrative data. Substance-related convictions are simply too infrequent to serve as a suitable control variable or even proxy for substance. It is telling that in the 15-24 age range, alcohol intoxication or misuse is associated with convictions for violent crimes with a strength (HR = 1.98, 95% CI 1.76–2.21, p < 0.001) greater than that found for SSRIs.

There may be important cultural differences between Sweden and other countries to which we want to generalize in terms of the determinants of arrest and conviction, but also treatment seeking for depression and the pathways for obtaining antidepressant medication. There may also be differences in institutional response to drug and alcohol use and misuse, including individuals’ willingness and ability to access services.

An unusual strength of this study is its use of within-individual analyses to escape some of the problems of more typical between-individual analyses not being able to adequately control for stable sources of differences. But, we can’t rely on these analyses to faithfully capture crucial sequences of events that happen quickly in terms of which events occurred first. The authors note that they

cannot fully account for time-varying risk factors, such as increased drug or alcohol use during periods of SSRI medication, worsening of symptoms, or a general psychosocial decline.

Findings examining non-fatal injuries from accidents as well as emergency inpatient or outpatient treatment for alcohol intoxication or misuse as time-varying confounders are tantalizing, but we reached the limits of the administrative data in trying to pursue them.

What can we learn from this study?

Readers seeking a definitive answer from the study to the question of whether antidepressants cause violent behavior or even violent crime will be frustrated.

There does not seem to be a risk of violent crime in individuals over 25 taking antidepressants.

The risk confined to individuals aged between 15 and 25 is, according to the authors, modest, but not insignificant. It represents a 20 to 40% increase in the low likelihood of being convicted of a violent crime. But it is not necessarily causal. The provocative data suggesting that low exposure, rather than no exposure or moderate or high exposure to antidepressants should give pause and suggest something more complex than simple causality may be going on.

This is an ambiguous but important point. Low exposure could represent non-adherence, inconsistent adherence, or periods in which there was a sudden stopping of medication, the effects of which might generate an association between the exposure and violent crimes. It could also represent the influence of time-dependent variables such as use of alcohol or substances that escaped control in the within-individual analyses.

There are parallels between results of the present study what is observed in other data sets. Most importantly, the data have some consistency with reports of suicidal ideation and deliberate self-harm among children and adolescents exposed to antidepressants. The common factor may be increased sensitivity of younger persons to antidepressants and particularly to their initiation and withdrawal or sudden stopping, the sensitivity reflected in impulsive and risk-taking behavior.

The take away message

Data concerning links between SSRIs and violent crime invite premature and exaggerated declarations of implications for public health and public policy.

At another blog, I’ve suggested that the British Medical Journal requirement that that observational studies have a demarcated section addressing these issues encourages authors to go beyond their data in order to increase the likelihood of publication – authors have to make public health and public policy recommendations to show that their data are newsworthy enough for publication. It’s interesting thata media watch group  criticized BMJ for using too strong causal language in covering this observational PLOS Medicine article.

I’m sure that the authors of this article felt pressure to address whether a black box warning inserted into the packaging of SSRIs was warranted by these data. I agree with them not recommending this at this time because of the strength of evidence and ambiguity in the interpretation of these administrative data. But I agree that the issue of young people being prescribed SSRIs needs more research and specifically elucidation of why low dose increases the likelihood of violence versus no or medium to high dose.

The authors do make some clinical recommendations, and their spokesperson Professor Fazel is particularly clear but careful in his interview with BBC World New Health Check News. My summary of what is said in the interview and in other media contacts is

  • Adolescents and young adults should be prescribed SSRIs should be on the basis of careful clinical interviews to ascertain a diagnosis consistent with practice guidelines for prescribing these drugs and that the drug be prescribed at therapeutic level.
  • These patients should be educated about the necessity of taking these medications consistently and advised against withdrawal or stopping the medication quickly without consultation and supervision of a professional.
  • These patients should be advised against taking these medications with alcohol or other drugs, with the explanation that there could be serious adverse reactions.

In general, young persons may be more sensitive to SSRIs, particularly when starting or stopping, and particularly when taken in the presence of alcohol or other drugs.

The importance of more research concerning nature of the sensitivity is highlighted by the findings of the PLOS Medicine article and the issues these findings point to but do not resolve.

Molero Y, Lichtenstein P, Zetterqvist J, Gumpert CH, Fazel S (2015) Selective Serotonin Reuptake Inhibitors and Violent Crime: A Cohort Study. PLoS Med 12(9): e1001875. doi:10.1371/journal.pmed.1001875

The views expressed in this post represent solely those of its author, and not necessarily those of PLOS or PLOS Medicine.

15 thoughts on “What we can learn from a PLOS Medicine study of antidepressants and violent crime”

  1. Jim, thank you for demonstrating clearly the problem in trying to wring experimental blood from a naturalistic stone. It is even shakier then you state since you accept the inference that above 25 there is no relationship between SSRIs and violence. However confounds may have obscured real positive or negative relationships , just as they might have produced a fallacious positive correlation.
    Nevertheless this problematic finding does stir a clinical hypothesis. Depression in this early age group is frequently of the atypical variety that our group at Columbia showed were unresponsive to TCAs and more than likely to SSRIs. I have clinically noted and Jonathan Stewart has found in a reanalysis of the old NIMH supported TDCRP clinical trial comparing imipramine placebo cognitive behavior therapy and the social support evaluation and correction psychotherapy developed by Myrna Weissman. Unfortunately the diagnosis of atypical depression was not made then so Jonathan had to reasonably reconstruct from the symptomatic reports. Trusting my recollection this group were non-significantly diferent from placebo and at times worse on TCAs , which in a very large sample might yield verbally reported symptomatology that could be interpreted ( misinterpreted ?) in terms of violent tendencies. In any case the MAOIs, that do seem specifically effective for early onset atypical depression, were not studied in this context. Regards ,
    Don

    Like

    1. Thanks Don, your poking into one of the many holes in this paper. It appears that only about a quarter of the individuals receiving an SSRI had a diagnosis of depression recorded and for that we rely on administrative data. Furthermore, given the overall low rate of violent crime and low elevation in absolute risk, lots of this kind of heterogeneity can be lurking in the data. I found the paper thought-provoking and useful for refining some hypotheses, but not on solid solid enough ground for any changes in practice a clinical policy, beyond the obvious that I stated in the blog..

      Like

      1. Thank you for a very thorough and insightful blog post about our paper, dr Coyne.
        Just a clarification about diagnoses – we didn’t have access to diagnoses made by general practitioners, only to inpatient diagnoses and diagnoses from specialized outpatient care. That is why we selected the cohort based on their prescriptions. There are probably a lot more than 25 % with a depression diagnosis. The association also remained significant, and of the same magnitude, when we removed individuals with other psychotropic medications.

        Like

    2. Thanks Don, this is an important comment to address. Even though different explanations are consistent with the data, we do not think that the association that we found is a chance finding as it was robust in our sensitivity analyses.

      “However confounds may have obscured real positive or negative relationships, just as they might have produced a fallacious positive correlation.”
      That confounding in different directions would cancel out a possible real effect for individuals over 25 is a quite strong statement as it assumes that the overall effect of confounding is of the same magnitude (but in the opposite direction) as the ‘true’ effect of exposure.

      Like

      1. Molero and Zetterqvist stimulated a discussion indicating that methodological problems of such studies do not allow positive generally applicable conclusions even if supposedly justified by statistical analysis of the data relationships.
        I extended the general critique by pointing the symmetry out. Even the so-called non-significant relationships were open to similar objections.Unknown confounds ,such as poor data recording, that generate non-significant data relationships cannot be used to argue that this data indicates a lack of true relationships.I could have been clearer by pointing out that this was the well known mistake of “asserting the null”.
        This was contested by Molero and Zetterqvist who argued that my statement , “However confounds may have obscured real positive or negative relationships, just as they might have produced a fallacious positive correlation.” was incorrect.
        Their point was,
        “That confounding in different directions would cancel out a possible real effect for individuals over 25 is a quite strong statement as it assumes that the overall effect of confounding is of the same magnitude (but in the opposite direction) as the ‘true’ effect of exposure. “.

        I disagree . All sorts of confounding problems with such data are possible . For all we know flawed observational techniques, e.g. poor data recording,if done well would not shrink a directional negative effect . That assumes a very simple additive model of error generation. Improved techniques of data generation,or observation, or registration are clearly desirable , but this improvement may modify data direction , or variance , or component effects, or who knows ,of any magnitude.
        On the positive side I gave an example where such “findings” may reinforce parallel beliefs (even mine) and may lead to studies that can allow better estimates whether the conclusions follow from the data .
        Cordially,
        Don Klein

        Like

  2. Thanks, DJ, I had been uncomfortable with that particular assertion. But I think that most used were not on appropriate dosages of medication. I would welcome being corrected if I am wrong on that point as well

    Like

  3. You are correct. Numerous studies show it is untreated serious mental illness that is associated with violence, not treated serious mental illness. I am unaware of studies that particularly look at mass homicide, but there are many that looked at homicide and others that looked at violence. For example, in Sweden, a study of all 2,005 individuals convicted of homicide or attempted homicide from 1988 to 2001 reported that 229, or 11%, had schizophrenia or bipolar disorder. Substance abuse and medication noncompliance were significant risk factors. (Fazel and Grann 2004) (Fazel, Buxrud and Ruchkin 2010). One meta-analysis of 10 studies of homicides and psychotic illness reported that the homicide rate in individuals never treated was 22 times higher than the rate in individuals treated. (Nielssen and Large 2010) A study of 348 inpatients in a Virginia state psychiatric hospital found that patients who refused to take medication “were more likely to be assaultive, were more likely to require seclusion and restraint, and had longer hospitalizations.” (Kasper and Hoge 1997). A study of 82,000 patients found “violent crime fell by 45% in patients receiving antipsychotics…and by 24% in patients prescribed mood stabilizers.” (Fazel, et al. 2014). There are many more such studies that show those treated with medication are not as violent or homicidal as those not treated.

    Like

  4. I am always impressed when the Scandinavian registries are used for the investigation of major public problems including social and health problems. I have a couple of comments based on my own use of these data sources here in Denmark. It is not clear if the time of follow-up ends when the first outcome is noted or how the authors handled the fact that more crimes may be the outcome in one person. Did the authors assigned risk time for each outcome or how was this handled. It may actually influence the outcome of the study. On the other side of the equation one would like to know if inclusion into the study required one prescription only or more prescriptions in order to determine if the person was a user or just a person who tried the drug and then stopped using it. Did the authors validate the users of SSRI by looking at other anti-depressive drugs in order to establish a group of heavy users (?) I am not aware of criminal statistics in general but it would be important to know if crimes and SSRI use is most prevalent in the age group in which the association was significant. It would also be nice to know if the authors had a substantial reason from biology, studies of mechanism or other well conducted studies which indicated the association btw SSRI use and crime in order to evaluate, as a reader, if the results are purely ecological or point to some kind of an association. In such large cohort studies one is ofte seduced by large numbers and researchers in Scandinavia often publish these large scale studies missing a starting point which, based on old principles of causality, actually justifies that you carry them out.

    Like

    1. Some readers will immediately recognize Professor Johanson from his extensive publications using such Scandinavian registry and administrative data. Those who don’t can simply look him up on Google Scholar.

      I’ll be responding more to some of Professor Johanson ‘s point shortly. But for now, one indeed has to be careful using such data, and keep in mind that an administrative entry is not equivalent to a behavior. Being arrested or convicted for a violent crime is not the equivalent to behavior and seriously underrepresents violent behavior. The mediators between behavior and registering as a arrest or conviction are many and varied. Much behavior that would qualify for an arrest or conviction is never identified or correctly matched to an individual. Many arrest and convictions occur long after the commission of a crime. The authors of this particular article try to get around some of these issues in their within individual analyses using time-varying covariates. Just as an example of many that could be generated, an individual who is distressed by the prospects of being arrested and convicted may obtain a prescription for antidepressants prior to actually being arrested. The sequence of exposure to antidepressants and subsequent conviction would be seriously misrepresented in even individual analyses with time varying covariates.

      But they seemed well aware that many rapid sequences and instances of reverse causality cannot be disentangled. There is a certain strength in numbers of individuals and events, but we should not place more confidence in these data than they deserve. The authors showed appropriate caution.

      Like

    2. Thank you for your comments, professor Johansen. We see that our paper has raised a few questions, and we would like to take the opportunity to answer them:

      “I am always impressed when the Scandinavian registries are used for the investigation of major public problems including social and health problems. I have a couple of comments based on my own use of these data sources here in Denmark. It is not clear if the time of follow-up ends when the first outcome is noted or how the authors handled the fact that more crimes may be the outcome in one person. Did the authors assigned risk time for each outcome or how was this handled. It may actually influence the outcome of the study”.

      Reply:
      In brief, we use stratified Cox regression in order to study the effects of SSRI medication on the (hazard) rate of violent crime within each individual. The underlying “survival” time was therefore time since last event. In order to measure this effect, we needed to compare different time points for the same individual. Since we split time for each crime date, only individuals with at least one convicted crime contributed to the association measure. We used all observable time. We have explained this in the methods section (and see Allison (1996) or the supplementary materials for the paper Lichtenstein et al. (2012) for more information).

      “On the other side of the equation one would like to know if inclusion into the study required one prescription only or more prescriptions in order to determine if the person was a user or just a person who tried the drug and then stopped using it”.

      Reply:
      This is also described clearly in our methods section. In our initial analysis, we included all individuals with dispensed SSRI prescriptions. However, as prescriptions are typically restricted to at most 3 months and we wanted to restrict the sample to those adherent to SSRIs, we then excluded individuals with a single SSRI prescription within a 6-month period from stratified and sensitivity analyses as no assumptions could be made about their medication adherence. A treatment period was thus defined as a series of SSRI prescriptions with no more than 6 months between two consecutive prescriptions. In addition, a separate analysis was also carried out including only individuals with a single dispensed prescription (Table 2).

      “Did the authors validate the users of SSRI by looking at other anti-depressive drugs in order to establish a group of heavy users (?)”

      Reply:
      No, this was not done. However, in sensitivity analyses we found that the association remained significant and when adjusting for concomitant medication or when polypharmacy patients were removed. We also examined associations between periods of low SSRI exposure (2 DDD/day) and convicted violent crimes and violent arrests (Table 3).

      “I am not aware of criminal statistics in general but it would be important to know if crimes and SSRI use is most prevalent in the age group in which the association was significant”.

      Reply:
      Crimes were most prevalent in the youngest age group (Table 3), but SSRI use was most prevalent in the oldest age group (Table 1). The number of events in the 15-24 groups was 2,798 and around 1,900 for each of the older age groups, but the association in the younger age groups was highly significant, and not significant at all in the older age groups. Therefore we don’t think that the different results for the age groups can be entirely explained by statistical power.

      “It would also be nice to know if the authors had a substantial reason from biology, studies of mechanism or other well conducted studies which indicated the association btw SSRI use and crime in order to evaluate, as a reader, if the results are purely ecological or point to some kind of an association. In such large cohort studies one is often seduced by large numbers and researchers in Scandinavia often publish these large scale studies missing a starting point which, based on old principles of causality, actually justifies that you carry them out”.

      Reply:
      The possible mechanisms of this association are discussed at length in the paper, which is open access.
      Regarding reverse causality; we excluded all persons who received SSRIs within 7, 14, 30, or 60 days after committing a violent crime, and the association between SSRI treatment and violent crime convictions remained significant.
      Even if different explanations are consistent with the found association, we do not believe that it is a chance finding since the association remained in the many sensitivity analyses.

      Like

  5. A careful and thoughtful analysis of a careful and thoughtful study. Well done. Many of the reported attempts to look at the impact of SSRIs are obviously agenda driven, particularly the population studies. This group of authors had an innovative design and let their results speak for themselves. What a concept!

    Like

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s