Investigating Factors Associated With Spontaneous Remission in Individuals With Alcohol Use Disorder-Results From a Multi-Site Longitudinal Cohort Study.

Diagnostic performance of the Alcohol Use Disorders Identification Test (AUDIT) in detecting DSM-5 alcohol use disorders in the General population

Identifying and Reducing Bias in Genome-Wide Association Studies of Alcohol-Related Traits.

Wakefield & Schmitz's paper 1 contributes to the debate concerning the diagnosis of alcohol use disorders. Despite widespread use, the criteria selected to define an alcohol use disorder (AUD) continue to be contested. More generally, the nosology underpinning the Diagnostic and Statistical Manual of Mental Disorders (DSM) is disputed. If 'classification is diagnosis' in psychiatry 2, then many psychiatric classifications are being disputed, in terms similar to those raised in this paper. Prior to and even after the development of the DSM criteria (DSM-I was released in 1952), low reliability characterized many psychiatric diagnoses 2, 3. There were few explicit criteria for a large number of disorders in early editions of the DSM. Diagnoses were unreliable, partly because there was no agreed-upon set of clinical criteria 2. The development of Research Diagnostic Criteria (RDC) 4 was specifically intended to address this problem. The symptoms which defined a disorder represented a consensus produced by clinicians 5 and were created largely to enable the differentiation of disorders, to identify disorders which have a common clinical character and which were likely to have common underlying causes 6. The extent to which these symptoms contributed to particular outcomes, e.g. death, injury, loss of employment or affected intimate relationships, was not considered in the selection of the symptoms. The DSM-IV extended the RDC by listing not only specific symptoms for most clinical entities, but also adding such criteria as the duration that symptoms had been present. Once explicit diagnostic criteria had been developed, these were converted into a structured interview based upon the DSM and ICD criteria. The Composite International Diagnostic Interview (CIDI) incorporated not only a long list of symptoms, but qualifiers such as level of impairment and help-seeking behaviour 7. Typically, the validity of structured interviews is judged according to the extent to which they produce diagnoses consistent with clinical assessment 7. Where clinical assessments produce diagnoses which differ from those derived from structured interviews, it is not obvious which is to be preferred. Are clinical diagnoses a 'gold-standard' against which other measures should be judged, or should structured interviews be preferred because they may be more reliable? How should we interpret the high rates of mental disorders which appear to accompany successive population surveys documenting rates of mental and substance use disorder in a community setting 8? The paper by Wakefield & Schmitz suggests that if adverse consequences were included in the diagnostic criteria, the population estimates of those meeting the criteria for an AUD would be substantially lower 1. Wakefield & Schmitz 1 test some alternative approaches to validating AUD diagnoses. Their strategy is to identify a number of clinically relevant markers, including history of previous AUDs, prior attendance to various treatment services and comparison with a criterion group with more severe AUD symptoms. They test the hypothesis that a small number of harmful–dysfunction (HD) criteria could be used to determine whether an AUD diagnosis is valid. Harmful dysfunction is divided into behavioural dysfunction (symptoms consistent with alcohol withdrawal) and alcohol harm (symptoms similar to those associated with impaired functioning). It is relevant that the Alcohol Use Disorders Identification Test (AUDIT) 9 was developed with a somewhat similar intent, and that some of the items in the AUDIT are similar to the HD items used in the study by Wakefield & Schmitz. Wakefield & Schmitz compare their diagnostic criteria with those derived from the DSM-IV and DSM-V. Their findings are in three broad categories. First, the HD criteria produce life-time estimates of AUD that are a small fraction of those derived using DSM-IV and DSM-V criteria. Secondly, the HD diagnostic markers are much more likely to identify valid cases. For example, for those meeting the criteria for AUD on the DSM-IV, 10.8% had ever attended Alcoholics Anonymous/Narcotics Anonymous; for the DSM-V it was 9.6% and for the HD criteria it was 35.9%. Thirdly, the HD criteria were associated with better sensitivity (and much lower specificity) than the DSM-IV and DSM-V AUD diagnostic groups. Does it follow that the DSM-IV and DSM-V criteria are identifying too many less serious cases of disorder? This is almost certainly the case. Kessler, among others, have noted that the impairment criteria available in the DSM suggest that many of those with a disorder only have mild or moderate levels of impairment 10. Kessler et al. argue that disaggregating 'cases' into those that are mild, moderate and severe is possible. However, Kessler et al. note there are increased risks of adverse outcomes even for 'mild' cases of mental disorders. Whether this is also true for alcohol use disorders is less clear 10. Were the impairment measures in the DSM, used to screen for caseness, then estimates of rates of AUD (and other disorders) would be much lower than they are. The findings of this study contribute not only to the debate about the validity of the DSM criteria for AUD, but also to the debate about many of the other diagnostic categories in the DSM. Kendler & Gardner 11 have suggested that the reliance upon cut-offs and caseness criteria in the DSM is somewhat arbitrary. They argue that, for example, depression presents as a distribution of symptoms with no clear or obvious boundaries. The same is probably true of symptoms of AUD. One view 3 is that most psychiatric diagnoses lack validity because they fail the test of presenting as a distinct (categorical) entity; that is, they present as a continuous distribution of symptoms. It would also be naive to ignore the political and economic forces which influence the criteria used to determine the presence of an AUD. Funding for alcohol-related social problems (including treatment and prevention) depends upon the magnitude of the problem being addressed. If one in three people in the population has had an AUD, the case for resourcing services is much stronger than if only one in 10 or 20 of the population are affected. Arguably, it is in the interest of treatment professionals to select criteria which produce higher rather than lower estimates of the magnitude of the problem. The findings of this paper may be interpreted as yet another challenge to the diagnostic criteria that are currently employed in the DSM and the underlying conceptual basis of that diagnostic system. The reliability and validity of clinical interviews and structured clinical interviews will remain matters of debate. One could also suggest that the inclusion of minor and transient conditions in the AUD umbrella lowers the credibility of the category itself. If HD criteria were incorporated into the diagnosis of AUD, then the case for treatment (and prevention) would be more persuasive, albeit for a substantially reduced proportion of the population. The validity of a diagnostic entity would be supported if the diagnostic label were seen to have specific implications for either understanding aetiology, suggesting treatment or anticipating probable harms 3. It may be that the diagnostic criteria used to determine the presence of an alcohol use disorder should vary depending upon the specific purpose of the diagnosis. Different sets of criteria may be needed for determining the need for treatment services, population-orientated public health programmes, programmes to reduce harms to physical health, harms to others and harms to life course outcomes. None.

The findings of Tuithof et al. [1] are consistent with studies of the course of DSM-IV [2] alcohol use disorder (AUD) in the general population, demonstrating that many episodes of AUD are of limited duration and many individuals who have experienced remission of AUD symptoms drink at levels that may increase the risk of relapse [3–7]. A prospective study based on just two data points is of limited utility for yielding valid inferences about a dynamic process such as persistence/remission of AUD, in that at least three data points are necessary to chart the chronic relapsing pattern that characterizes a substantial proportion of individuals with lifetime AUD in long-term prospective studies [8–11]. In fact, retrospective data, despite limitations related to recall error and selective survival, may actually tell us more about the recovery process than prospective data with single follow-up [3]. Despite the inherent limitations of its study design, this study nonetheless raises some interesting questions about how the persistence of AUD is related to remission, how has this changed under the DSM-5 and what new research opportunities may arise out of these changes. Under the DSM-IV, individuals who meet the criteria for alcohol dependence at t1 but do not satisfy the requirements for persistent dependence or full remission (cessation of all AUD symptoms) at t2 fall into the category of partial remission, comprising alcohol abuse and/or subclinical dependence symptoms. Individuals who do not satisfy the requirements for persistent abuse include both those who have progressed to dependence and those in full remission. Thus, the absence of persistence does not necessarily signify full remission. Retrospective studies of US population samples have shown that partial remission of dependence is common, peaking in prevalence at ≈40% 5–9 years after onset of dependence [4]. Individuals in partial remission drink more and have a lower quality of life than those in full remission, but drink less and have a higher quality of life than those with persistent dependence [12,13]. Because individuals in partial remission are distinct from those with persistent or fully remitted AUD, a clearer picture of the significance of factors associated with the course of DSM-IV AUD could be obtained by excluding partial remission cases from analyses or including them as a separate outcome category in multinomial models. The proposed DSM-5 revision [14] does not recognize partial remission as a course specifier for AUD [15]. Among individuals with AUD (2+ positive criteria) at t1, those with subclinical levels of AUD symptoms at t2 count as fully remitted, along with those who are asymptomatic. In addition, the newly added criterion of craving, which may persist even after discontinuation of drinking, does not preclude achievement of remission. Thus, full remission and persistent AUD are more complementary under the DSM-5 than they were under the DSM-IV; i.e., there are no longer any cases that fall between these categories. However, regardless of whether partial remission is formally recognized or subsumed under full remission, the residual presence of cases with a subclinical level of symptoms reduces the contrast between persistent and asymptomatic cases. Thus, challenges remain with dichotomous outcome measures when modeling correlates of remission or persistence. However, the DSM-5 definition of AUD as a unitary latent construct whose symptoms vary along a continuum of severity suggests new approaches to the study of persistence/remission that may overcome some of the limitations of a dichotomous outcome measure. One such approach is to examine correlates of increase/decrease in AUD severity, and to see whether a change of a given magnitude has different correlates depending on the base level of severity. That is, does a drop from 8 to 5 positive criteria between t1 and t2 have the same correlates as a drop from 4 to 1? Similarly, does the impact of a given decrease in severity on changes in consumption and quality of live vary based on initial severity level? Results of such an approach would at least be suggestive of factors that differentially affect the early versus later stages of recovery, and they would clearly distinguish factors associated with remission of AUD of varying severity levels. The addition of craving as a criterion for DSM-5 AUD also suggests new opportunities for analyses. Unlike most AUD criteria, which reflect or result from but do not cause heavy drinking, craving can reinforce excessive consumption, which may in turn lead to the persistence of other AUD symptoms. By studying the unique contribution of craving to the course of AUD, i.e., its impact net of the number of other AUD criteria, we may be able to draw valuable inferences related to the benefits of medical treatment for the alleviation of craving. In summary, the proposed DSM-5 criteria for AUD should facilitate multiple new analytic approaches that will enhance our understanding of factors associated with the course of AUD and implications for treatment.

NIAAA Definition of Recovery Provides Measurable Endpoints for AUD Researchers

OBJECTIVES: This study examined the utilization of and the perceived need for alcohol treatment services among college-age young adults (18–22 years) according to their educational status: full-time college students, part-time college students, noncollege students (currently in school with the highest grade level below college), and nonstudents (N=11,337). This breakdown of young adults had not been addressed previously. METHODS: Secondary analyses were conducted on data from the 2002 National Survey on Drug Use and Health. RESULTS: Full-time college students (21%) were as likely to have an alcohol use disorder as nonstudents (19%), but were more likely than part-time college students (15%) and noncollege students (12%). Only 4% of full-time college students with an alcohol use disorder received any alcohol services in the past year. Of those with an alcohol use disorder who did not receive treatment services, only 2% of full-time college students, close to 1% of part-time college students, and approximately 3% of young adults who were not in college reported a perceived need for alcohol treatment. Full-time college students were less likely than noncollege students to receive treatment for alcohol use disorders. All young adults with an alcohol use disorder were very unlikely to perceive a need for alcohol treatment or counseling. CONCLUSIONS: College-age adults have a high prevalence of alcohol use disorders, yet they are very unlikely to receive alcohol treatment or early intervention services or to perceive a need for such services. Underutilization of alcohol-related services among college-age young adults deserves greater research attention.

Identification of Risky Alcohol Consumption in the Preoperative Assessment

Background. Revision of the DSM diagnostic criteria is underway; proposed changes have been posted for review. Data from clinical, general population, family and twin samples from the USA and across the world have been analyzed by the substance-related workgroup to inform the proposed revisions to criteria for substance use disorders. Data from both adults and adolescents have been studied. In this presentation, we will examine the proposed criteria for alcohol use disorder (AUD) in a young sample from the Collaborative Study on the Genetics of Alcoholism (COGA), a high-risk family study established to identify the genes for alcoholism, and in which data are being collected every 2 years from youth aged 12–25. The proposed changes to be studied include: combining abuse and dependence into a single disorder, eliminating as a criterion recurrent legal problems, adding a new item reflecting craving and using a cut point of 2 or more (of 11) symptoms to indicate affected status. Method. Data on AUD symptoms from adolescents and young adults were analyzed using factor analysis and IRT models. One- to four-factor models were fitted to 12 lifetime symptoms (n = 1635 individuals drinkers, mean age 17.9, 48% female). Agreement (kappa) with DSM-IV abuse/dependence was examined. Results. Exploratory factor analysis revealed strong evidence for one factor, with loadings substantial (>0.70) for most items. Craving fit well with the other items. Results were unchanged when legal problems were eliminated. IRT results indicated good fit and craving had good discrimination but high difficulty. The cutpoint of two symptoms achieved the highest agreement (kappa) with DSM-IV abuse/dependence diagnosis and evinced a modest 5.6% increase in prevalence. Conclusions. Proposed changes for DSM-V appear to work well in a young sample for AUD, but analyses need to be repeated in a less-selected sample and for other substances to ensure that these results are generalizable.

DIAGNOSIS AND MANAGEMENT OF ALCOHOL PROBLEMS

Background: Comorbidities such as mental illness and alcohol use disorders (AUD) worsen the prognosis of both conditions. There is a need to identify early alcohol use disorders in psychiatric patients to prevent the development of dual diagnosis diseases, which are more difficult to treat. The Alcohol Use Disorders Identification Test (AUDIT) was developed by the World Health Organisation to promote early identification of alcohol use disorders and has been validated mainly in primary care settings. No study has validated the AUDIT in a French-speaking psychiatric setting. There is also a need to identify the risk factors of heavy drinking with psychiatric disorders. Purpose: This study aims at (1) validating the French version of the Alcohol Use Disorders Identification Test (AUDIT) for psychiatric inpatients and (2) determining the frequency of alcohol use disorders in four major psychiatric ICD-10 diagnostic categories: neurotic and depressive disorders (F3 and F4), personality disorders (F6), psychotic disorders (F2) and other disorders (n = 10). Subjects and methods: Of 383 consecutive psychiatric admissions, 219 completed the AUDIT. A subset was also interviewed with the CIDI (gold standard) and was retested with the AUDIT. Psychiatric diagnoses were recorded from hospital medical records. Results: Validation of the AUDIT showed a very good sensitivity (94.1%) and specificity (91.7%) in this psychiatric inpatient population. Frequency of alcohol use disorders was 35.1%. Personality disorders had the highest rate of AUDIT scores ≥8 (50.7%). Gender was the only statistically significant outcome in a multivariate model. Discussion: Male sex as an outcome associated with the presence of alcohol use disorders, is consistent with the other AUDIT studies in psychiatry. The uniqueness of the present study is the evaluation of personality disorders among the psychiatric diagnostic categories. Conclusion: This study strengthens the evidence that the AUDIT is reliable and valid with psychiatric patients and confirms the high frequency of alcohol use disorders in this population. Drinking habits of patients with emotionally labile personality disorders should be screened.

To determine if the clinical course of DSM-5 alcohol use disorders (AUD) in select populations of young adults (18-30 years) differed based on gender, diagnostic severity (mild, moderate, severe), and ethnicity. Native Americans (NA) and Mexican Americans (MA) (n = 1,129) were recruited from the community and completed a structured diagnostic interview. Participants with DSM-5 AUDs were compared based on gender, severity of the disorder (mild, moderate, severe), and ethnicity for differences in drinking levels, as well as the clinical course of AUD as defined by the occurrence and sequence of 36 alcohol-related life events. Seventy percent of the NA men, 64% of the NA women, 56% of the MA men, and 42% of the MA women met lifetime diagnostic criteria for a DSM-5 AUD. NA reported more alcohol-related life events and at an earlier age than MA. A high degree of similarity in the clinical course was found between men and women and between those with severe or moderate disorder, but not with those with mild disorder. NA had higher drinking levels and more alcohol problems at an earlier age than MA. A similar clinical course was seen based on gender and ethnicity in these young adults, but not based on diagnostic severity. The DSM-5 mild AUD category differs from the moderate and severe categories on drinking history, clinical course, gender, and ethnic distribution. Mild AUD may not be in the same clinical continuum as moderate and severe AUD in these populations.

Prevention and early intervention of alcohol use disorder (AUD) is a public health priority, yet there are gaps in our understanding of how AUD emerges, which symptoms of AUD come first, and whether there are modifiable risk factors that forecast the development of the disorder. This study investigated potential early-warning-sign symptoms for the development of AUD. Data were from the RADAR study, a prospective cohort study of contemporary emerging adults across Australia (n = 565, mean age = 18.9, range = 18-21 at baseline, 48% female). Participants were interviewed five times across a 2.5-year period. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) AUD criteria and diagnoses were assessed by clinical psychologists using the Structured Clinical Interview for DSM-IV (SCID-IV), modified to cover DSM-5 criteria. Hazard analyses modeled the time from first alcoholic drink to the emergence of any AUD criteria and determined which first-emergent AUD criteria were associated with a faster transition to disorder. By the final time point, 54.8% of the sample had experienced at least one DSM-5 AUD criterion and 26.1% met criteria for DSM-5 AUD. The median time from first AUD criterion to a diagnosis of AUD was 4 years. Social problems from drinking (hazard ratio [HR] = 3.24, CI95 = 2.14, 4.92, p < 0.001), major role (HR = 2.53, CI95 = 1.58, 4.06, p < 0.001), and drinking larger amounts/for longer than intended (HR = 2.04, CI95 = 1.20, 3.46, p = 0.008) were first-onset criteria associated with a faster transition to AUD. In the context of a prospective general population cohort study of the temporal development of AUD, alcohol-related social problems, major role problems, and using more or for longer than intended are key risk factors that may be targeted for early intervention.

Aims: The Alcohol Use Disorders Identification Test (AUDIT) is a well-established and widely used screening instrument. It has been shown that AUDIT has good criterion validity in relation to alcohol abuse and dependence according to DSM-IV, but it has not yet been validated following the introduction of the DSM-5 diagnostic system. The aim of this study was to evaluate concurrent validity for the AUDIT in relation to self-reported DSM-5 severity levels for Alcohol Use Disorder (AUD) in a Swedish general population sample.Methods: A postal questionnaire, containing the AUDIT and the 13-item brief DSM-5 AUD diagnostic assessment screener, was sent to a random sample of 1,500 persons drawn from the Swedish population, aged between 17 and 80 years and having a public residence address in Sweden. To evaluate the concurrent validity of AUDIT in relation to DSM-5 severity criteria for AUD, a Receiver Operating Characteristics (ROC) curve analysis was conducted.Results: Area under the curve (AUROC) showed excellent differentiation between AUD or not, mild (.93), moderate (.92) and severe (.99). Higher individual AUDIT scores were associated with more severe levels of AUD according to the DSM-5 screener. The optimal cutoff scores approximate earlier research on the DSM-IV and were identified as 5, 7 and 13 points, respectively, for mild, moderate and severe AUD.Conclusions: Our findings indicate that AUDIT is a valid screener for detecting concurrent AUD at three severity levels in the Swedish general population.

Screening and brief intervention (SBI) is effective in reducing alcohol use, particularly among moderate risk patients. Results of SBI are inconsistent among patients with alcohol use disorders (AUDs). The Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) is used as a screening tool in many existing SBI programs. ASSIST validation studies have identified risk level cutoff scores using criteria for AUD and have not included a criterion measure for at-risk drinking (ARD), the group for whom SBI is most effective. This study examines the ability of the ASSIST to identify unhealthy alcohol use (ARD or AUD) and AUD in patients presenting to urgent care. Data were obtained from interviews with 442 adult drinkers presenting to 1 of 3 urgent care clinics. Subjects completed the ASSIST, a 90-day timeline follow-back interview to detect ARD, and a modified Diagnostic Interview Schedule to identify AUD. Validity measures compared the specificity and sensitivity of cutoff scores for the ASSIST in detecting unhealthy alcohol use and AUDs. The optimal ASSIST score for detecting unhealthy alcohol use is 6+ for males (sensitivity and specificity 68 and 66%, respectively) and 5+ for females (62%/70%). Sensitivity, specificity, and receiver operating characteristic values were lower than those previously reported for the Alcohol Use Disorders Identification Test (AUDIT). For AUD, the optimal ASSIST cutoff scores are 10+ for males (63%/85%) and 9+ for females (63%/85%). While higher scores provided increased specificity, thereby reducing the percentage of false positives, sensitivity dropped sharply as scores increased. Optimal ASSIST cutoff scores for unhealthy alcohol use are lower than those commonly used in many SBI programs. Use of lower ASSIST cutoff scores may increase detection of unhealthy alcohol use and increase the numbers served by SBI programs.

There is a wide discrepancy in the epidemiology of alcohol use disorders (AUDs) due to diverse scales and survey approaches. We estimated the prevalence of AUDs by comparing the pooled prevalence based on the alcohol use disorders identification test (AUDIT) Vs. non-AUDIT (all scales other than AUDIT). This review searched the community-based prevalence of AUDs in PubMed, Web of Science, PsycINFO, Scopus, Ovid, and Google Scholar. Articles published during the years from 2000 to 2020 were included. The methodological quality of each study was scored, and data were extracted from the published reports. Pooled prevalence was estimated, and the publication bias was evaluated. Twenty-one studies conducted in different states of India included 73997 community-based respondents, which estimated the overall prevalence of AUDs as 12.5% (95% CI: 9 to 17.3%). The pooled prevalence based on AUDIT was 12.4% (AUDIT ≥8; 95% CI: 8.8 to 17.1%) in which the magnitude of hazardous and harmful alcohol use (8.6%; 95% CI: 5.7 to 12.8%; AUDIT 8-19) was significantly higher than dependent alcohol use (2.3%; 95% CI: 1.1 to 4.8%; AUDIT ≥ 20). The pooled prevalence using the non-AUDIT tool was 14.2(95%; CI: 6-30%). Our findings further reveal that about one in twelve of the population of India have AUDs, and there is a gross variation in the patterns of alcohol use across the country. The high prevalence of AUDs suggests developing a national policy to benefit alcohol use, justifying regional variations. Supplemental data for this article is available online at https://doi.org/10.1080/15332640.2022.2056105 .