Combining scales to assess suicide risk Hilario Blasco-Fontecilla a, * , David Delgado-Gomez b , Diego Ruiz-Hernandez c , David Aguado d , Enrique Baca-Garcia e, f , Jorge Lopez-Castroman e, g a Department of Psychiatry, Puerta de Hierro Hospital, CIBERSAM, Calle Manuel de Falla 1, 28222 Majadahonda, Spain b Department of Statistics, Carlos III University, Calle Madrid 126, Getafe 28903, Spain c Department of Statistics, CUNEF University, Serrano Anguita, 8, 28004 Madrid, Spain d Institute of Knowledge Engineering, Autonoma University, 28049 Madrid, Spain e Department of Psychiatry, IIS-Jimenez Diaz Foundation, CIBERSAM, 28040 Madrid, Spain f Department of Psychiatry, Columbia University Medical Center,1051 Riverside Drive, New York, USA g Inserm U888 & CHU Montpellier, Montpellier, France article info Article history: Received 20 November 2011 Received in revised form 22 May 2012 Accepted 19 June 2012 Keywords: Lars-en algorithm Suicidal behavior Personality traits Life events abstract Objectives: A major interest in the assessment of suicide risk is to develop an accurate instrument, which could be easily adopted by clinicians. This article aims at identifying the most discriminative items from a collection of scales usually employed in the assessment of suicidal behavior. Methods: The answers to the Barrat Impulsiveness Scale, International Personality Disorder Evaluation Screening Questionnaire, BrowneGoodwin Lifetime History of Aggression, and Holmes & Rahe Social Readjustment Rating Scale provided by a group of 687 subjects (249 suicide attempters, 81 non-suicidal psychiatric inpatients, and 357 healthy controls) were used by the Lars-en algorithm to select the most discriminative items. Results: We achieved an average accuracy of 86.4%, a specificity of 89.6%, and a sensitivity of 80.8% in classifying suicide attempters using 27 out of the 154 items from the original scales. Conclusions: The 27 items reported here should be considered a preliminary step in the development of a new scale evaluating suicidal risk in settings where time is scarce. Ó 2012 Elsevier Ltd. All rights reserved. 1. Introduction Suicide is a major health issue. One suicide is completed every 40 seconds, leading to approximately one million deaths every year worldwide (WHO, 2002). Moreover, suicide is the third most important cause of death worldwide among people aged 15e44 (Holmes et al., 2007). Notwithstanding human costs, the economic burden of suicidal behavior has been estimated annually in $33 billion in the United States (Coreil et al., 2001). Fortunately, suicidal behavior might be prevented to a great extent (Jamison, 2000). Treating subjects at risk with the appropriate preventive measures, such as cognitive behavior therapies (Brown et al., 2005) can reduce suicide rates up to 25% (Isaacson, 2000). More recently, a 75% reduction of suicide rates has been reported in a large depression care program (Hampton, 2010). In order to detect subjects at risk, researchers have investigated the factors underlying suicidal behavior. The most relevant risk factors are major depression (Mann et al., 1999b), high impulsiveness (Patton et al., 1995), aggressiveness (Mann et al., 1999b), personality disorders (Mann et al., 1999a), life events (Kolves et al., 2006), and social-demographic factors (Smith et al., 1988). Unfortunately, most of these studies did not measure the effectiveness of the risk factors to identify subjects at risk. They just tested if there was a statistically significant relationship between the studied variable (e.g. high impulsiveness) and suicidal behavior. Therefore, the clinical usefulness of these studies is limited. One notable exception is the seminal Pokorny’s article (Pokorny, 1983). Pokorny applied discriminant analysis to several features including, among others, socio-demographic variables, the 24 items of the brief psychiatric rating scale, and the items included in the nurses’ observation scale for inpatient evaluation. Although it was an innovative approach, his results showed a weak performance, with accuracy, sensitivity and specificity levels below 70%. More recently, Hendin (Hendin et al., 2010) slightly improved these results achieving an accuracy of 71.67% with a specificity of 74% and a sensitivity of 60%. The improvement was basically due to the use of a different set of predictive variables, as they used a simple * Corresponding author. Villalba MHC, Department of Psychiatry, Puerta de Hierro Hospital, CIBERSAM, Calle de Los Madroños 5, 28400 Collado Villalba, Spain. Tel.: þ34 918505161; fax: þ34 918514707. E-mail address: hmblasco@yahoo.es (H. Blasco-Fontecilla). Contents lists available at SciVerse ScienceDirect Journal of Psychiatric Research journal homepage: www.elsevier.com/locate/psychires 0022-3956/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jpsychires.2012.06.013 Journal of Psychiatric Research xxx (2012) 1e6 Please cite this article in press as: Blasco-Fontecilla H, et al., Combining scales to assess suicide risk, Journal of Psychiatric Research (2012), http://dx.doi.org/10.1016/j.jpsychires.2012.06.013