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. 2019 Mar;114(3):534-552.
doi: 10.1111/add.14482. Epub 2018 Dec 9.

Concordance between the diagnostic guidelines for alcohol and cannabis use disorders in the draft ICD-11 and other classification systems: analysis of data from the WHO's World Mental Health Surveys

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Concordance between the diagnostic guidelines for alcohol and cannabis use disorders in the draft ICD-11 and other classification systems: analysis of data from the WHO's World Mental Health Surveys

Louisa Degenhardt et al. Addiction. 2019 Mar.

Abstract

Background and aims: The World Health Organization's (WHO's) proposed International Classification of Diseases, 11th edition (ICD-11) includes several major revisions to substance use disorder (SUD) diagnoses. It is essential to ensure the consistency of within-subject diagnostic findings throughout countries, languages and cultures. To date, agreement analyses between different SUD diagnostic systems have largely been based in high-income countries and clinical samples rather than general population samples. We aimed to evaluate the prevalence of, and concordance between diagnoses using the ICD-11, The WHO's ICD 10th edition (ICD-10) and the Diagnostic and Statistical Manual of Mental Disorders, 4th and 5th editions (DSM-IV, DSM-5); the prevalence of disaggregated ICD-10 and ICD-11 symptoms; and variation in clinical features across diagnostic groups.

Design: Cross-sectional household surveys.

Setting: Representative surveys of the general population in 10 countries (Argentina, Australia, Brazil, Colombia, Iraq, Northern Ireland, Poland, Portugal, Romania and Spain) of the World Mental Health Survey Initiative.

Participants: Questions about SUDs were asked of 12 182 regular alcohol users and 1788 cannabis users.

Measurements: Each survey used the World Mental Health Survey Initiative version of the WHO Composite International Diagnostic Interview version 3.0 (WMH-CIDI).

Findings: Among regular alcohol users, prevalence (95% confidence interval) of life-time ICD-11 alcohol harmful use and dependence were 21.6% (20.5-22.6%) and 7.0% (6.4-7.7%), respectively. Among cannabis users, 9.3% (7.4-11.1%) met criteria for ICD-11 harmful use and 3.2% (2.3-4.0%) for dependence. For both substances, all comparisons of ICD-11 with ICD-10 and DSM-IV showed excellent concordance (all κ ≥ 0.9). Concordance between ICD-11 and DSM-5 ranged from good (for SUD and comparisons of dependence and severe SUD) to poor (for comparisons of harmful use and mild SUD). Very low endorsement rates were observed for new ICD-11 feature for harmful use ('harm to others'). Minimal variation in clinical features was observed across diagnostic systems.

Conclusions: The World Health Organization's proposed International Classification of Diseases, 11th edition (ICD-11) classifications for substance use disorder diagnoses are highly consistent with the ICD 10th edition and the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV). Concordance between ICD-11 and the DSM 5th edition (DSM-5) varies, due largely to low levels of agreement for the ICD harmful use and DSM-5 mild use disorder. Diagnostic validity of self-reported 'harm to others' is questionable.

Keywords: Alcohol; DSM; ICD; World Mental Health Surveys; cannabis; diagnosis; substance use disorder.

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Conflict of interest statement

Declaration of Interests: In the past three years, LD has received investigator-initiated untied educational grants for studies of opioid medications in Australia from Indivior, Mundipharma and Seqirus. RK received support for his epidemiological studies from Sanofi Aventis; was a consultant for Johnson & Johnson Wellness and Prevention, Shire, Takeda; and served on an advisory board for the Johnson & Johnson Services Inc. Lake Nona Life Project. RK is a co-owner of DataStat, Inc., a market research firm that carries out healthcare research. VP is a staff member of the World Health Organization involved in the development and field testing of ICD-11 for disorders due to substance use and addictive behaviours. SC is also a staff member of the World Health Organization. MG’s role on this study is through his involvement as a Science Officer on U01-MH60220. He had no involvement in the other cited grants. All other authors declare no competing interests.

Figures

Figure 1:
Figure 1:. Venn diagrams showing the overlap between cases defined by ICD-10 and ICD-11 dependence definitions, and DSM-5 moderate-severe use disorder, for alcohol and cannabis
Note: Total cases (unweighted n) were as follows. Alcohol: ICD-10 dependence n=890; ICD-11 dependence n=974; DSM-5 moderate-severe use disorder n=1,749. Cannabis: ICD-10 dependence n=61; ICD-11 dependence n=61; DSM-5 moderate-severe use disorder n=98. Diagrams produced in BioVenn.

Comment in

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