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Abstract: The serotonin transporter 5-HTTLPR polymorphism moderates response to SSRIs and side-effect burden. The aim of this study is to quantify the cost-utility of incorporating 5-HTTLPR genotyping in drug treatment of major depressive disorder (MDD). We previously reported a theoretical model to simulate antidepressant treatment with citalopram or bupropion for 12weeks. The drugs were alternatively selected according to an ‘as usual’ algorithm or based on response and tolerability predicted by 5-HTTLPR profile. Here we apply this model to conduct a cost-utility analysis in three European regions with high GDP (Euro A), middle GDP (Euro B) and middle-high GDP (Euro C).. In addition we test a verification scenario in which citalopram+bupropion augmentation is administered to individuals with the least favorable 5-HTTLPR genotype. Treatment outcomes are remission and Quality Adjusted-Life Weeks (QALW). Cost data (international $, year 2009) are retrieved from the World Health Organization (WHO) and national official sources. In base-case scenario incremental cost-effectiveness ratio (ICER) values are $1147 (Euro A), $ 1185 (Euro B) and $1178 (Euro C). From cost-effectiveness acceptability curve (CEAC), the probability of having an ICER value below WHO recommended cost-utility threshold (3 GDP per capita=$1926) is >90% in high-income countries (Euro A). In middle- income regions, these probabilities are <30% (Euro B) and <55% (Euro C) respectively. All estimates are robust against variations in treatment parameters, but if genetic test cost decreases to $100, pharmacogenetic approach becomes cost-effective in middle-income countries (Euro B). This simulation using data from 27 European states suggests that choosing antidepressant treatment from the results of 5-HTTLPR might be a cost-effective solution in high income countries. Its feasibility in middle income countries needs further research. [Copyright &y& Elsevier]

Abstract: Suicide is one of the leading causes of death worldwide, mortality from suicide being approximately 2%. Attempted suicide appears to be a major risk factor for suicide completion. Anger, aggression and impulsivity are personality traits associated with suicide attempt. In this study we analysed a part of a previously reported sample in order to test anger, impulsivity and temperament/character scales as predictors of aggression and self-aggression in suicide attempters and to compare anger- and aggression-related traits between impulsive and premeditated suicide attempts as well as between violent and non-violent suicide methods. One-hundred-eleven consecutively admitted inpatients with a lifetime history of attempted suicide were assessed for anger (State-Trait Anger Expression Inventory, STAXI), aggression (Questionnaire for Measuring Factors of Aggression, FAF) and temperament/character (Temperament and Character Inventory, TCI). Higher aggression scores, as measured by FAF, were predicted by being male, meeting criteria for borderline personality disorder and having higher angry temperament scores as assessed by STAXI; low cooperativeness was also associated with aggression but not after controlling for STAXI scales. TCI dimensions associated with self-aggression were high harm avoidance, high impulsivity and low self-directedness; state anger, inwardly directed anger and inhibition of aggression were also predictors of self-aggression. In conclusion, impulsivity and harm avoidance have emerged as temperament dimensions independently associated with self-aggressive tendencies in personality. Such interactions could explain the correlation between temperament and suicidality but further research is needed. Anger and self-directedness appear to have some effects on suicide attempt. [Copyright &y& Elsevier]

Abstract: Predicting the outcome of antidepressant treatment by pre-treatment features would be of great usefulness for clinicians as up to 50% of major depressives may not have a satisfactory response in spite of adequate trials of antidepressant drugs. In the present article we compared a linear multivariate model of predictors with a few artificial neural network (ANN) models differing from one another by outcome definition and validation procedure. The sample consisted of a reanalysis of 116 inpatients with a major depressive episode included in a 6-week open-label trial with fluvoxamine. With the original outcome definition (responders/non-responders), ANN performed better than logistic regression (90% of correct classifications in the training sample vs. 77%). However only 62% of new patients were correctly predicted by ANN for their outcome class. Length of the index episode, psychotic features and suicidal behavior emerged as outcome predictors in both models, while demographic characteristics, personality disorders and concomitant somatic morbidity were pointed to only by ANN analysis. Increase of classes in the outcome field resulted in a more elevated error: 46.4% for three classes, 60.4% for four classes and 70.3% for five classes. Overall, our findings suggest that antidepressant outcome prediction based on clinical variables is poor. The ANN approach is as valid as traditional multivariate techniques for the analysis of psychopharmacology studies. The complex interactions modelled through ANN may eventually be applied at the clinical level for individualized therapy. However, the accuracy of prediction is still far from satisfactory from a clinical point of view. [Copyright &y& Elsevier]

The symptoms of major psychosis aggregate in factors. Models of one to eight dimensions have been reported. In the present study, we tested six competing factor models, based on the psychotic and affective items of the OPCRIT checklist, in a large sample (N=1294) of patients diagnosed with DSM-IV schizophrenia (n=460), bipolar disorder (n=726) and delusional disorder (n=108). Confirmatory factor analysis was used to test the following models: (1) unique psychotic dimension; (2) positive-manic items, negative–depressive items; (3) model 2 with the addition of a disorganized factor; (4A) positive, negative, depressive and manic dimensions; (4B) model 4A with loss of pleasure (Anhedonia) and loss of energy (Apathy) included among depressive instead of negative symptoms; and (5) same as model 4B except for the addition of a disorganized domain. The four- and five-factor models fit the data much better than simpler ones. Between the two four-factor models, M4B emerged as more appropriate than M4A. The five-factor solution (M5) displayed the best fit. In conclusion, our confirmatory factor analysis in a large sample of psychotic subjects indicated that the symptomatology of major psychoses is composed of the following five factors: mania, positive symptoms, disorganization, depression and negative symptoms. [Copyright &y& Elsevier]

Abstract: The short variant of the serotonin transporter gene (SERTPR) has been consistently associated with a poorer response to treatment with various selective serotonin reuptake inhibitors (SSRIs). Antidepressant response is not a unitary phenomenon, however, and we here hypothesized that the SERTPR effect could be specific to some types of symptomatology. The sample comprised 281 inpatients affected by mood disorders and treated for major depression with SSRIs. The total depressive scores for all patients were analyzed in previous reports, but symptomatologic clusters were not examined previously. The 21-item Hamilton Rating Scale for Depression (HAM-D) was administered to evaluate depressive symptoms at baseline and weekly over 6 weeks of treatment. All patients were genotyped for the SERTPR polymorphism. Compared with patients with the SERTPR l/l and l/s polymorphisms, s/s patients showed a selective and slower improvement of depressive “core” and somatic anxiety symptoms, but they did not differ from other patients regarding other symptomatologic clusters such as insomnia and motor retardation. These findings support the view that response to SSRIs is not a unitary phenomenon and that improvement of symptomatologic clusters as, at least in part, genetically driven. SERTPR may be hypothesized as concurrently participating to the activity of anatomic brain regions differentially involved in depression and somatic symptoms of anxiety; however, further studies are required to examine these complex interactions. [Copyright &y& Elsevier]