Refining the Diagnosis of Alcohol Use Disorder: A Comprehensive Approach

 描述(由申请人提供)：过度饮酒有许多负面的健康后果，包括更高的死亡风险。此外，在高收入和中等收入国家，过度饮酒的估计经济成本超过国民生产总值的1%(Rehm等人，2009年)。该应用程序的总体目标是改进酒精使用障碍(AUD)的定义和评估。我们的建议与最新的NIAAA战略计划(2009-2014年)中概述的目标是一致的。更广泛地说，我们的研究将开发和验证用于AUD诊断的最佳诊断标准集和算法(ODCSA)，我们预计这些标准和算法的表现将显著好于现有的诊断标准(即DSM-5和ICD-10)。我们将采用新兴方法，开发和应用统计和分类科学中的新方法，将现有的大型人群流行病学数据集(全国酒精中毒及相关疾病流行病学调查，NESARC；国家纵向酒精流行病学调查，NLAES；全国药物使用与健康调查，NSDUH)，一个浓缩了高密度AUDS的大的多地点样本(酒精中毒遗传学合作研究，COGA)，一个主要的多地点治疗结果研究(结合药物和行为干预；合并)和两个较小的非临床和临床数据集，涵盖参与者生命的十年或更长时间，以完善AUDS的评估方法、诊断标准和诊断算法。具体地说，通过在数据协调和计算统计中使用最先进的技术，我们将确定那些标准集和决策规则，这些标准集和决策规则将在数据集内和跨数据集优化与酒精消费重度的关联。然后，将对这些新的OCSA的结构有效性和外部有效性进行广泛的评估。此外，我们将对DSM-5、ICD-10和ICD-11标准草案进行广泛的验证分析，因为这些标准本身是有意义的，而且这将使我们能够将我们新的ODCSA与当前标准进行基准比较。我们相信，AUD经验性诊断的发展将促进对AUD病因和相关性的研究，并将导致临床实践中更好的诊断标准。为这一应用开发的方法应该具有广泛的适用性，当没有明确的“黄金标准”时，为一系列临床重要结构制定诊断标准或评估工具。这项拟议的研究利用了数据共享的增加、数据协调方面的新发展以及计算科学的进步。

 DESCRIPTION (provided by applicant): Excessive alcohol use has many negative health consequences, including higher risk of mortality. In addition, the estimated economic cost of excessive drinking is more than 1% of the gross national product in high- income and middle-income countries (Rehm et al., 2009). The over-arching goal of this application is to improve the definition and assessment of alcohol use disorder (AUD). Our proposal is consistent with the goals outlined in the most recent NIAAA Strategic Plan (2009-2014). Most broadly, our study will develop and validate optimal diagnostic criteria sets and algorithms (ODCSAs) for the diagnosis of AUD that we anticipate will perform substantially better than existing diagnostic criteria (i.e. DSM-5 and ICD-10). We will employ emerging methods and develop and apply new methods in statistics and classification science to existing large population-based epidemiological data sets (the National Epidemiological Survey of Alcoholism and Related Conditions, NESARC; the National Longitudinal Alcohol Epidemiologic Survey, NLAES; the National Survey on Drug Use and Health, NSDUH), a large multi-site sample enriched for high density of AUDs (the Collaborative Study on the Genetics of Alcoholism, COGA), a major, multi-site treatment outcome study (Combining Medications and Behavioral Interventions; COMBINE) and two smaller non-clinical and clinical data sets spanning a decade or more of participants lives in order to refine assessment methods, diagnostic criteria, and diagnostic algorithms for AUDs. Specifically, by employing state-of-the art techniques in data harmonization and computational statistics, we will identify those criteria sets and decision rules that will optimize the associaton with heaviness of alcohol consumption, both within and across data sets. These new ODCSAs will then be subjected to extensive evaluation of their structural validity and external validity. n addition, we will conduct extensive validation analyses of DSM-5, ICD-10, and draft ICD-11 criteria, because these are of interest in their own right, and because that will allow us to benchmark our new ODCSAs with the current standards. We believe the development of empirically-based diagnosis for AUD will improve research on the causes and correlates of AUD and should lead to improved diagnostic criteria for clinical practice. The methods developed for this application should have broad applicability for developing diagnostic criteria or assessment instruments for a range of clinically important constructs when there are no clear "gold standards." The proposed research exploits increased availability of data sharing, new developments in data harmonization, and advances in computational science.