Classification Trees Distinguish Suicide Attempters in Major Psychiatric Disorders: A Model of Clinical Decision Making

J. John Mann, M.D.; Steven P. Ellis, Ph.D.; Christine M. Waternaux, Ph.D.; Xinhua Liu, Ph.D.; Maria A. Oquendo, M.D.; Kevin M. Malone, M.D.; Beth S. Brodsky, Ph.D.; Gretchen L. Haas, Ph.D.; and Dianne Currier, Ph.D.

Objective: Determining risk for a suicide attempt in psychiatric patients requires assessment of multiple risk factors and knowledge of their relative importance. Classification and regression tree (CART) analysis generates decision trees that select the variables that perform best in identifying the group of interest and model clinical decision making. Hypothetical decision trees to identify recent and remote suicide attempters, weighted to increase sensitivity, were generated for psychiatric patients using correlates of past suicidal behavior.

Method: Correlates of past suicide attempts were identified in 408 patients with mood, schizophrenia spectrum, or personality disorders (DSM-IV). Correlated variables were entered into recursive partitioning statistical models to generate equally weighted and unequally weighted hypothetical decision trees for distinguishing recent (<= 30 days prior to study) and remote (> 250 days prior to study) suicide attempters from nonattempters. The study was conducted from December 1989 to November 1998.

Results: In equally weighted trees, a recent past suicide attempt was best predicted by current suicidal ideation (sensitivity = 56%, specificity = 91%, positive predictive value = 69%), and no adequate model was found for remote attempts. In unequally weighted models, recent attempters were identified by suicidal ideation and comorbid borderline personality disorder (sensitivity = 73%, specificity = 80%, positive predictive value = 58%). Remote attempters were identified by lifetime aggression and current subjective depression (sensitivity = 89%, specificity = 36%, positive predictive value = 44%).

Conclusion: Current suicidal ideation is the best indicator of a recent suicide attempt in psychiatric patients. Indicators of a remote attempt are aggressive traits and current depression. Weighted decision trees can improve sensitivity and miss fewer attempters but with a cost in specificity.

(J Clin Psychiatry 2008;69:23-31; online ahead of print January 3, 2008)

Received Jan. 29, 2007; accepted April 16, 2007. From the Department of Neuroscience, New York State Psychiatric Institute, New York (Drs. Mann, Ellis, Oquendo, Brodsky, and Currier); the Department of Psychiatry, Columbia University, New York, N.Y. (Drs. Mann, Ellis, Waternaux, Liu, Oquendo, Brodsky, and Currier); the Department of Psychiatry and Mental Health Research, St. Vincent's University Hospital, Dublin, Ireland (Dr. Malone); and Western Psychiatric Institute and Clinic, Pittsburgh, Pa. (Dr. Haas).

Supported by National Institute of Mental Health grants MH62185 and MH48514 and by the Audrey Wallace Otto Fund of the St. Louis Community Foundation and The Diane Goldberg Foundation.

Patient assessments were performed by Donna Abbondanza, R.N.; Tom Kelly, Ph.D.; Diane Dolata, R.D.; and Elizabeth Radomsky, Ph.D.

The authors report no additional financial or other relationships relevant to the subject of this article.

Corresponding author and reprints: J. John Mann, M.D., Department of Neuroscience, NYS Psychiatric Institute, 1051 Riverside Dr., Box 42, New York, NY 10032 (e-mail: jjm@columbia.edu).