BACKGROUND: Proposed International Classification of Diseases, 11th edition (ICD-11), criteria for substance use disorder (SUD) radically simplify the algorithm used to diagnose substance dependence. Major differences in case identification across DSM and ICD impact determinations of treatment need and conceptualizations of substance dependence. This study compared the draft algorithm for ICD-11 SUD against DSM-IV, DSM-5, and ICD-10, for alcohol and cannabis. METHODS: Adolescents (n = 339, ages 14 to 18) admitted to intensive outpatient addictions treatment completed, as part of a research study, a Structured Clinical Interview for DSM SUDs adapted for use with adolescents and which has been used to assess DSM and ICD SUD diagnoses. Analyses examined prevalence across classification systems, diagnostic concordance, and sources of diagnostic disagreement. RESULTS: Prevalence of any past-year proposed ICD-11 alcohol or cannabis use disorder was significantly lower compared to DSM-IV and DSM-5 (ps < 0.01). However, prevalence of proposed ICD-11 alcohol and cannabis dependence diagnoses was significantly higher compared to DSM-IV, DSM-5, and ICD-10 (ps < 0.01). ICD-11 and DSM-5 SUD diagnoses showed only moderate concordance. For both alcohol and cannabis, youth typically met criteria for an ICD-11 dependence diagnosis by reporting tolerance and much time spent using or recovering from the substance, rather than symptoms indicating impaired control over use. CONCLUSIONS: The proposed ICD-11 dependence algorithm appears to "overdiagnose" dependence on alcohol and cannabis relative to DSM-IV and ICD-10 dependence, and DSM-5 moderate/severe use disorder, generating potential "false-positive" cases of dependence. Among youth who met criteria for proposed ICD-11 dependence, few reported impaired control over substance use, highlighting ongoing issues in the conceptualization and diagnosis of SUD.
BACKGROUND: Proposed International Classification of Diseases, 11th edition (ICD-11), criteria for substance use disorder (SUD) radically simplify the algorithm used to diagnose substance dependence. Major differences in case identification across DSM and ICD impact determinations of treatment need and conceptualizations of substance dependence. This study compared the draft algorithm for ICD-11 SUD against DSM-IV, DSM-5, and ICD-10, for alcohol and cannabis. METHODS: Adolescents (n = 339, ages 14 to 18) admitted to intensive outpatient addictions treatment completed, as part of a research study, a Structured Clinical Interview for DSM SUDs adapted for use with adolescents and which has been used to assess DSM and ICD SUD diagnoses. Analyses examined prevalence across classification systems, diagnostic concordance, and sources of diagnostic disagreement. RESULTS: Prevalence of any past-year proposed ICD-11 alcohol or cannabis use disorder was significantly lower compared to DSM-IV and DSM-5 (ps < 0.01). However, prevalence of proposed ICD-11 alcohol and cannabis dependence diagnoses was significantly higher compared to DSM-IV, DSM-5, and ICD-10 (ps < 0.01). ICD-11 and DSM-5 SUD diagnoses showed only moderate concordance. For both alcohol and cannabis, youth typically met criteria for an ICD-11 dependence diagnosis by reporting tolerance and much time spent using or recovering from the substance, rather than symptoms indicating impaired control over use. CONCLUSIONS: The proposed ICD-11 dependence algorithm appears to "overdiagnose" dependence on alcohol and cannabis relative to DSM-IV and ICD-10 dependence, and DSM-5 moderate/severe use disorder, generating potential "false-positive" cases of dependence. Among youth who met criteria for proposed ICD-11 dependence, few reported impaired control over substance use, highlighting ongoing issues in the conceptualization and diagnosis of SUD.
Authors: Sharon M Kelly; Jan Gryczynski; Shannon Gwin Mitchell; Arethusa Kirk; Kevin E O'Grady; Robert P Schwartz Journal: Drug Alcohol Depend Date: 2014-04-13 Impact factor: 4.492
Authors: Louisa Degenhardt; Chrianna Bharat; Raimondo Bruno; Meyer D Glantz; Nancy A Sampson; Luise Lago; Sergio Aguilar-Gaxiola; Jordi Alonso; Laura Helena Andrade; Brendan Bunting; Jose Miguel Caldas-de-Almeida; Alfredo H Cia; Oye Gureje; Elie G Karam; Mohammad Khalaf; John J McGrath; Jacek Moskalewicz; Sing Lee; Zeina Mneimneh; Fernando Navarro-Mateu; Carmen C Sasu; Kate Scott; Yolanda Torres; Vladimir Poznyak; Somnath Chatterji; Ronald C Kessler Journal: Addiction Date: 2018-12-09 Impact factor: 6.526