Identifying Patient Subgroups That Are Most Likely To Benefit From Medications Used To Treat Alcohol Use Disorder

确定最有可能从用于治疗酒精使用障碍的药物中受益的患者亚组

基本信息

  • 批准号:
    10334521
  • 负责人:
  • 金额:
    $ 2.21万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-02-01 至 2022-08-31
  • 项目状态:
    已结题

项目摘要

PROJECT SUMMARY/ABSTRACT The objective of this K01 award is to provide Dr. Joshua Wallach, an Assistant Professor of Epidemiology at the Yale School of Public Health, with the protected time necessary to become an independent expert in synthesizing, evaluating, and establishing the best evidence to inform clinical practice in the field of alcohol use disorder (AUD). Although AUD is a common and morbid disease, for which medication treatment is available, uncertainties about whether and for whom treatments work may be causing AUD medication underutilization. To advance the evidence base to support AUD medication treatment, research is needed to identify patient subgroups that are most likely to benefit from each medication used to treat AUD. However, traditional subgroup analyses often consider only one patient characteristic at a time and are conducted in small clinical trials with strict exclusion criteria, short durations, and outcomes that may not reflect how patients feel or function. This proposed K01 will address these limitations by conducting subgroup analyses using multiple data sources, outcomes, and analytical techniques. In Aim 1, Dr. Wallach will identify and assess the validity of already published subgroup analyses to establish promising patient subgroups that are most likely to benefit from each medication used to treat AUD. In Aim 2, existing data from the largest AUD trial in the US (the COMBINE study) will be used to (a) corroborate promising patient subgroup differences identified in Aim 1 and (b) explore new differences between patient subgroups, using multiple methods (i.e. traditional and statistical learning, which can consider multiple characteristics) and outcome measures (abstinence, heavy drinking, and 2-shift reduction in World Health Organization drinking levels). In Aim 3, claims data from OptumLabs, a database of over 150 million privately insured and Medicare Advantage enrollees, will be used to determine whether the same, similar, or new differences between patient subgroups are observed in real-world settings when hospital and ambulatory care outcomes are considered. These aims will clarify uncertainties among patients and clinicians regarding the adoption of AUD medications, which can decrease the public health burden associated with AUD. To support these aims, Dr. Wallach’s career development plan will include training in: (1) AUD medications and addiction medicine, (2) novel statistical learning techniques that can be used to inform individualized clinical decision making, and (3) pharmacoepidemiology and observational research methods for real-world medical product evaluation. The candidate has identified an interdisciplinary team of mentors and advisors, including co-primary mentors Dr. Joseph Ross, a health services researcher and administrative data expert, and Dr. Stephanie O’Malley, an AUD treatment and addiction medicine expert. The Yale Schools of Public Health and Medicine provide the ideal environment for career development. This K01 will prepare Dr. Wallach for an R01 submission, and will facilitate his long-term goal of developing an innovative research program combining meta-research and real-world evaluation to improve AUD clinical care.
项目总结/文摘

项目成果

期刊论文数量(0)
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会议论文数量(0)
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Joshua David Wallach其他文献

Joshua David Wallach的其他文献

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{{ truncateString('Joshua David Wallach', 18)}}的其他基金

Identifying patient subgroups that are most likely to benefit from medications used to treat alcohol use disorder
确定最有可能从用于治疗酒精使用障碍的药物中受益的患者亚组
  • 批准号:
    10555243
  • 财政年份:
    2021
  • 资助金额:
    $ 2.21万
  • 项目类别:
Identifying patient subgroups that are most likely to benefit from medications used to treat alcohol use disorder
确定最有可能从用于治疗酒精使用障碍的药物中受益的患者亚组
  • 批准号:
    10698725
  • 财政年份:
    2021
  • 资助金额:
    $ 2.21万
  • 项目类别:

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