Novel causal inference methods to inform clinical decision on when to discontinue symptomatic treatment for patients with dementia

新的因果推断方法可为痴呆患者何时停止对症治疗提供临床决策

基本信息

批准号：
10322425
负责人：
Xiaojuan Li
金额：
$ 16.6万
依托单位：
HARVARD PILGRIM HEALTH CARE, INC.
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：
2021-01-01 至 2024-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10322425
关键词：
Accounting Acetylcholinesterase Admission activity Adverse drug effect Adverse event Aftercare Age Alzheimer&apos s disease related dementia Area Australia Canada Caring Characteristics Clinical Clinical Trials Cloning Code Cognition Complex Consensus Country Data Data Set Databases Dementia Development Elderly Emergency department visit Ethnic Origin Event Feedback Fracture Funding Galantamine Guidelines Health Health and Retirement Study Hospitalization Impaired cognition Incidence Intervention Ischemic Stroke Level of Evidence Link Long-Term Effects Marital Status Measures Medicare Memantine Methods Nursing Homes Observation in research Outcome Outcome Study Patient-Focused Outcomes Patients Pattern Persons Pharmaceutical Preparations Population Provider Publishing Quality of life Race Randomized Controlled Trials Recommendation Retrospective cohort Risk Sample Size Surveys Time United States Weight arm base clinical center clinical risk cost cost efficient design donepezil evidence based guidelines falls frailty health care service utilization health data health service use human old age (65+)improved improved outcome medical specialties mortality multidimensional data multiple chronic conditions novel pill prevent rivastigmine sex symptom treatment treatment duration treatment effect treatment risk trial comparing

项目摘要

PROJECT SUMMARY/ABSTRACT Appropriate use of acetylcholinesterase (AChEIs) and memantine can meaningfully improve the health outcomes and quality of life among people with Alzheimer’s disease-related dementia (ADRD). Deprescribing of these symptomatic medications can help mitigate medication burden and associated adverse events in this population, particularly given the high level of multimorbidity and pill burden. However, no current US guideline exists on deprescribing of these medications in ADRD. Existing non-US guideline recommendations are largely consensus-based and should be strengthened through higher levels of evidence. Two pivotal questions need to be answered first: 1) what is the long-term effect of symptomatic dementia medications? and 2) when is suitable to discontinue these medications? Ideally, answers to these questions would come from randomized controlled trials, but conducting trials evaluating multiple treatment duration or discontinuation strategies simultaneously with large enough sample sizes in each arm would be cost-prohibitive. Observational data from dementia medication use in the real-world setting provides a unique opportunity. However, treatment duration or discontinuation strategies necessarily involve interventions on time-varying treatment decisions. Evaluating the time-varying medication use on health and patient-centered outcomes must appropriately control for complex time-varying confounding that renders conventional regression invalid. Novel causal inference methods, including Robins’ g-formula and a three-step weighting approach (cloning, censoring, weighting) can appropriately account for such time-varying confounding and generate estimates of absolute risks while preventing immortal time bias. By emulating the valid analyses of trials, causal analyses of observational data are also cost-efficient and have greater generalizability. Using data collected in a large survey linked with electronic health databases, we will characterize the utilization pattern of symptomatic dementia medications and examine factors that influenced treatment discontinuation (Aim 1). We will then use novel causal inference methods to estimate the long-term effect of continuous treatment (Aim 2), and to evaluate different treatment discontinuation strategies (Aim 3) with regard to incidence of clinical and patient-centered outcomes and health service utilization. We will use data from the Health and Retirement Study (HRS)-Medicare linked dataset. The nationally representative, longitudinal, NIA-funded HRS survey provides validated measures on cognitive impairment and dementia. The linkage to Medicare provides extensive information on medication, clinical characteristics, and health care utilization. The expected outcome of this study is an understanding of the effects of long-term use of dementia medications and the impact of different treatment discontinuation strategies on outcomes. The findings of this study will provide a scientific basis for the development of evidence-based guidelines and the planning of clinical trials in the deprescribing of symptomatic dementia medications in people with ADRD to improve their care.

项目概要/摘要适当使用乙酰胆碱酯酶（AChEI）和美金刚可以有意义地改善健康阿尔茨海默病相关痴呆症 (ADRD) 患者的结果和生活质量。这些对症药物可以帮助减轻药物负担和相关的不良事件人口，特别是考虑到高水平的多重发病率和药物负担。然而，美国目前没有指南。 ADRD 中现有的非美国指南建议主要是取消这些药物的处方。需要以共识为基础，并应通过更高水平的证据予以加强。首先要回答：1）对症痴呆药物的长期效果是什么？2）何时？理想情况下，这些问题的答案应该来自随机试验？对照试验，但进行评估多种治疗持续时间或停药策略的试验同时，如果每个组的样本量都足够大，那么观察数据的成本就会过高。现实世界中痴呆症药物的使用提供了独特的机会，但是治疗持续时间较长。或停药策略必然涉及对随时间变化的治疗决策进行干预。随时间变化的药物使用对健康和以患者为中心的结果的影响必须适当控制复杂的时变混杂使得传统回归无效。方法，包括 Robins 的 g 公式和三步加权方法（克隆、审查、加权）可以适当地考虑这种随时间变化的混杂因素并生成绝对风险的估计，同时通过模拟试验的有效分析、观察数据的因果分析来防止不朽的时间偏差。使用在大型调查中收集的数据也具有成本效益，并且具有更大的普遍性。电子健康数据库，我们将描述症状性痴呆药物的使用模式并检查影响治疗中断的因素（目标 1）。评估持续治疗的长期效果（目标 2）并评估不同治疗的方法关于临床和以患者为中心的结果和健康的发生率的停药策略（目标 3）我们将使用健康与退休研究 (HRS)-医疗保险关联数据集的数据。由 NIA 资助的全国代表性纵向 HRS 调查提供了经过验证的认知测量方法与医疗保险的联系提供了有关药物、临床的广泛信息。本研究的预期结果是了解医疗保健的利用。长期使用痴呆药物的影响以及不同治疗中断的影响本研究的结果将为制定战略提供科学依据。症状性痴呆处方的循证指南和临床试验规划 ADRD 患者服用药物以改善他们的护理。

项目成果

期刊论文数量（4）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Trends in Labor Unionization Among US Health Care Workers, 2009-2021.

2009-2021 年美国医护人员加入工会的趋势。

DOI：
发表时间：
2022-12-27
期刊：
影响因子：
0
作者：
Ahmed, Ahmed M;Kadakia, Kushal;Ahmed, Alwiya;Shultz, Blake;Li, Xiaojuan
通讯作者：
Li, Xiaojuan

Analysis of Reported Voting Behaviors of US Physicians, 2000-2020.

2000-2020 年美国医生投票行为报告分析。

DOI：
发表时间：
2022-01-04
期刊：
影响因子：
13.8
作者：
Ahmed, Ahmed;Chouairi, Fouad;Li, Xiaojuan
通讯作者：
Li, Xiaojuan

Statin use is associated with lower risk of dementia in stroke patients: a community-based cohort study with inverse probability weighted marginal structural model analysis.

他汀类药物的使用与中风患者患痴呆症的风险较低相关：一项基于社区的队列研究，采用逆概率加权边际结构模型分析。

DOI：
发表时间：
2022-06
期刊：
影响因子：
13.6
作者：
Yang, Zhirong;Toh, Sengwee;Li, Xiaojuan;Edwards, Duncan;Brayne, Carol;Mant, Jonathan
通讯作者：
Mant, Jonathan

Association Between Regular Laxative Use and Incident Dementia in UK Biobank Participants.

英国生物银行参与者定期使用泻药与痴呆症之间的关联。

DOI：
发表时间：
2023-04-18
期刊：
影响因子：
9.9
作者：
Yang, Zhirong;Wei, Chang;Li, Xiaojuan;Yuan, Jinqiu;Gao, Xuefeng;Li, Bingyu;Zhao, Ziyi;Toh, Sengwee;Yu, Xin;Brayne, Carol;Yang, Zuyao;Sha, Feng;Tang, Jinling
通讯作者：
Tang, Jinling