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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.

项目总结/文摘

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）

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.

DOI：
10.1007/s10654-022-00856-7
发表时间：
2022-06
期刊：
EUROPEAN JOURNAL OF EPIDEMIOLOGY
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.