BACKGROUND: Substance use disorders (SUDs) may be characterized by onset age, severity, substance type, course, and outcomes. SUD phenotypes in the literature typically consider each of these features in isolation. Conceptual frameworks and data collection procedures for assessing SUD phenotypes are increasingly "diachronic" in approach, providing for characterizations "throughout time". The recent availability of statistical procedures for the identification of latent classes offers the possibility of developing SUD phenotypes integrating these developmental features. This article illustrates the utilization of SAS-TRAJ mixture modeling to characterize variations in SUD symptom trajectories to define phenotypes. METHODS: The subjects were 332 adult males with SUDs. Their course of symptoms from early adolescence through middle adulthood was retrospectively determined. Symptom trajectories were defined by the number of DSM-IV SUD symptoms by year of age. SAS-TRAJ mixture models identified trajectory classes. Model development, evaluation, and selection using this approach are discussed. RESULTS: Among these men with SUDs, six trajectory classes were identified, including groups characterized by early-onset and severe SUD symptoms persisting into adulthood, an early-onset group similar in adolescence but improving in adulthood, and other groups with symptoms emerging later with varying degrees of severity and persistence. The SUD trajectory classes were significantly different on comorbid psychopathology, particularly childhood disruptive behavior disorders. CONCLUSION: The results present a new method for the comprehensive depiction of heterogeneity in SUD symptoms. Future studies may determine the extent to which SUDs phenotypes based on the course of symptom development inform etiology, prevention and treatment research.
BACKGROUND: Substance use disorders (SUDs) may be characterized by onset age, severity, substance type, course, and outcomes. SUD phenotypes in the literature typically consider each of these features in isolation. Conceptual frameworks and data collection procedures for assessing SUD phenotypes are increasingly "diachronic" in approach, providing for characterizations "throughout time". The recent availability of statistical procedures for the identification of latent classes offers the possibility of developing SUD phenotypes integrating these developmental features. This article illustrates the utilization of SAS-TRAJ mixture modeling to characterize variations in SUD symptom trajectories to define phenotypes. METHODS: The subjects were 332 adult males with SUDs. Their course of symptoms from early adolescence through middle adulthood was retrospectively determined. Symptom trajectories were defined by the number of DSM-IV SUD symptoms by year of age. SAS-TRAJ mixture models identified trajectory classes. Model development, evaluation, and selection using this approach are discussed. RESULTS: Among these men with SUDs, six trajectory classes were identified, including groups characterized by early-onset and severe SUD symptoms persisting into adulthood, an early-onset group similar in adolescence but improving in adulthood, and other groups with symptoms emerging later with varying degrees of severity and persistence. The SUD trajectory classes were significantly different on comorbid psychopathology, particularly childhood disruptive behavior disorders. CONCLUSION: The results present a new method for the comprehensive depiction of heterogeneity in SUD symptoms. Future studies may determine the extent to which SUDs phenotypes based on the course of symptom development inform etiology, prevention and treatment research.
Authors: Donald M Dougherty; Charles W Mathias; Dawn M Marsh-Richard; R Michael Furr; Sylvain O Nouvion; Michael A Dawes Journal: Addict Disord Their Treat Date: 2009-06-01
Authors: Thomas M Maddox; Colleen Ross; Heather M Tavel; Ella E Lyons; Maggie Tillquist; P Michael Ho; John S Rumsfeld; Karen L Margolis; Patrick J O'Connor; Joe V Selby; David J Magid Journal: Circ Cardiovasc Qual Outcomes Date: 2010-05-20
Authors: Rina D Eiden; Gregory G Homish; Craig R Colder; Pamela Schuetze; Teresa R Gray; Marilyn A Huestis Journal: Subst Use Misuse Date: 2013-04-12 Impact factor: 2.164