Shorter, E. & Tyrer, P. Separation of anxiety and depressive disorders: blind alley in psychopharmacology and classification of disease. BMJ 327, 158-160

History of Medicine Program, Faculty of Medicine, University of Toronto, Toronto ON, Canada M5G 1VJ.
BMJ (online) (Impact Factor: 17.45). 08/2003; 327(7407):158-60. DOI: 10.1136/bmj.327.7407.158
Source: PubMed


ne current division between anxiety and depression is increasingly recognised as inadequate. In the community, most mood disorders present as a combination of depression and anxiety. Yet the Food and Drug Administration in the United States, which has become the world bellwether of drug approval, indicates drugs either for major depression or for the various forms of anxiety recognised by the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders (DSM). As a result, the pharmaceutical industry is compelled to develop drugs for diagnoses that are of questionable clinical relevance. This is one reason for the big slowdown in drug discovery in psychiatric drugs. A return to the former unitary classification of mood and anxiety disorders as nervousness or cothymia might represent a way out of this blind alley.

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Available from: Edward Shorter, Oct 17, 2014
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    • "Perhaps the most important criticism of the DSM-5 regards the poor validity of its classification. Several researchers have even stressed that the DSM-5 hampers research into the underlying mechanisms in the etiology of psychopathology and that the current state of affairs is one of scientific stagnation [5]. We argue that the development of more valid psychiatric classifications is important in order to link mental states to specific causes in scientific research, and that this process should be evidence-based. "
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    ABSTRACT: The launch of the 5th version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) has sparked a debate about the current approach to psychiatric classification. The most basic and enduring problem of the DSM is that its classifications are heterogeneous clinical descriptions rather than valid diagnoses, which hampers scientific progress. Therefore, more homogeneous evidence-based diagnostic entities should be developed. To this end, data-driven techniques, such as latent class- and factor analyses, have already been widely applied. However, these techniques are insufficient to account for all relevant levels of heterogeneity, among real-life individuals. There is heterogeneity across persons (p:for example, subgroups), across symptoms (s:for example, symptom dimensions) and over time (t:for example, course-trajectories) and these cannot be regarded separately. Psychiatry should upgrade to techniques that can analyze multi-mode (p-by-s-by-t) data and can incorporate all of these levels at the same time to identify optimal homogeneous subgroups (for example, groups with similar profiles/connectivity of symptomatology and similar course). For these purposes, Multimode Principal Component Analysis and (Mixture)-Graphical Modeling may be promising techniques.
    Full-text · Article · Sep 2013 · BMC Medicine
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    • "Heterogeneity in depression leads to decreased clinical specificity and a loss of statistical power. Dichotomizing results in the dismissal of valuable information, which may lead to biased results (Shorter and Tyrer, 2003). A dimensional model of psychopathology resolves both issues by assuming that symptom severity follows a continuum rather than a dichotomy. "
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    ABSTRACT: We examined the association of cognitive vulnerability to depression with changes in homogeneous measures of depressive symptoms. Baseline and 1-year follow-up data were obtained from 2981 participants of the Netherlands study of depression and anxiety. Multivariate regression analyses were carried out on cognitive reactivity, locus of control and implicit and explicit self-depressive associations in combination with negative life events. The purpose of this analysis was to predict changes on the mood/cognition and anxiety/arousal subscales of the inventory of depressive symptomatology - self report. Cognitive reactivity, locus of control and explicit self-depressive associations were independently associated with changes in depressive symptoms after adjustment for covariates and baseline severity (all p<0.01). Negative life-events interacted with cognitive vulnerability to depression to predict depressive symptoms. Locus of control (b1=0.16, SE=0.02, η(2)=0.01; b2=0.10, SE=0.02, η(2)=0.004, F=8.69, p<0.01) and explicit self-depressive associations (b1=0.10, SE=0.03, η(2)=0.02; b2=0.02, SE=0.04, F=7.50, p<0.01) were more strongly associated with the cognitive (b1) than the somatic (b2) symptom dimension of depression. The study sample is over-inclusive of depressed patients. Therefore it might be problematic generalizing the findings to the general population. Cognitive etiological factors may play a role in a "cognitive" subtype of depression. The findings strengthen the notion that homogeneous measures of depressive symptoms enable a greater degree of discrimination between subtypes than a multidimensional conception of depression.
    Full-text · Article · Jun 2013 · Journal of Affective Disorders
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    • "This has led to much criticism of the models used. Likewise, there has been a growing discussion focused on whether anxiety and depression should be isolated from a drug development perspective (Shorter and Tyrer, 2003). Moreover, given the relative success of SSRIs, it is becoming clear that many pharmaceutical companies are compelled to develop a 'one pill fits all' approach to anxiety and mood disorders. "
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    ABSTRACT: Anxiety disorders are common, serious and a growing health problem worldwide. However, the causative factors, aetiology and underlying mechanisms of anxiety disorders, as for most psychiatric disorders, remain relatively poorly understood. Animal models are an important aid in giving insight into the aetiology, neurobiology and, ultimately, the therapy of human anxiety disorders. The approach, however, is challenged with a number of complexities. In particular, the heterogeneous nature of anxiety disorders in humans coupled with the associated multifaceted and descriptive diagnostic criteria, creates challenges in both animal modelling and in clinical research. In this paper, we describe some of the more widely used approaches for assessing the anxiolytic activity of known and potential therapeutic agents. These include ethological, conflict-based, hyponeophagia, vocalization-based, physiological and cognitive-based paradigms. Developments in the characterization of translational models are also summarized, as are the challenges facing researchers in their drug discovery efforts in developing new anxiolytic drugs, not least the ever-shifting clinical conceptualization of anxiety disorders. In conclusion, to date, although animal models of anxiety have relatively good validity, anxiolytic drugs with novel mechanisms have been slow to emerge. It is clear that a better alignment of the interactions between basic and clinical scientists is needed if this is to change.
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