Refining the Diagnosis of Alcohol Use Disorder: A Comprehensive Approach

 描述（由申请人提供）：过度饮酒对健康有许多负面影响，包括死亡风险较高。此外，在高收入和中等收入国家，过量饮酒的估计经济成本超过国民生产总值的1%（雷姆等人，2009年）。该应用程序的主要目标是改善酒精使用障碍（AUD）的定义和评估。我们的建议与最新的NIAAA战略计划（2009-2014年）中概述的目标一致。最广泛地说，我们的研究将开发和验证用于诊断AUD的最佳诊断标准集和算法（ODCSA），我们预计这些标准集和算法的性能将大大优于现有的诊断标准（即DSM-5和ICD-10）。我们将采用新兴的方法，并开发和应用统计学和分类科学的新方法，以现有的大型人口流行病学数据集（国家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;全国药物使用和健康调查，NSDUH），富集高密度AUD的大型多位点样本（酒精中毒遗传学合作研究，COGA），一项主要的多中心治疗结果研究（联合用药和行为干预;联合收割机）和两个较小的非临床和临床数据集，跨越十年或更长时间的参与者生活，以完善评估方法，诊断标准和AUD的诊断算法。具体而言，通过采用数据协调和计算统计方面的最先进技术，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优化与酒精消费量的关联，无论是在数据集内还是在数据集之间。然后，这些新的ODCSA将对其结构有效性和外部有效性进行广泛评估。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，因为这些标准本身就很有意义，而且这将使我们能够用现行标准对新的ODCSA进行基准测试。我们相信，发展以肾脏为基础的AUD诊断将改善对AUD病因和相关因素的研究，并应导致临床实践的诊断标准得到改善。当没有明确的“金标准”时，为这一应用开发的方法应具有广泛的适用性，用于为一系列临床重要结构开发诊断标准或评估工具。“拟议的研究利用了数据共享的可用性增加，数据协调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.