Innovative precision medicine methods in subgroup identification for Alzheimer's disease
阿尔茨海默病亚组鉴定的创新精准医学方法
基本信息
- 批准号:10740649
- 负责人:
- 金额:$ 23.33万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-09-01 至 2025-06-30
- 项目状态:未结题
- 来源:
- 关键词:AccelerationAddressAducanumabAffectAgingAlzheimer&aposs DiseaseAmericanAreaBehavioralBiologicalCause of DeathCharacteristicsClinical DataClinical TrialsCognitiveCollaborationsCommunitiesComputer softwareCountryDataDementiaDevelopmentDiseaseDisease ProgressionFutureGoalsGroupingHealthHealthcareIndividualInvestigational DrugsInvestigational TherapiesKnowledgeMachine LearningMeasuresMethodologyMethodsModelingOutcomePatient SelectionPatientsPersonsPharmaceutical PreparationsPharmacotherapyPopulationPopulation HeterogeneityPublic HealthReportingResearchResearch PersonnelSelection for TreatmentsSubgroupTherapeutic AgentsTreatment outcomeTreesanalytical methodanalytical tooldata miningdesigndonepezilevidence baseflexibilityimprovedindividual variationindividualized medicineinnovationinterestnovelnovel therapeuticspaymentprecision medicinepreventprimary outcomeprospectiveresponsetooltreatment effecttreatment researchtreatment responsetreatment trialuser-friendly
项目摘要
is a major and rapidly increasing public health concern: over 30 million individuals
worldwide suffer from AD, which is projected to quadruple by 2050. AD has been reported to be the third leading
cause of death in the US. With this impending global public health crisis, treatments that prevent onset or slow
progression of AD are urgently needed but rarely available until the recent accelerated approval for aducenumab.
Therefore, it is of great interest to identify subpopulations which benefit most from a medication when the overall
treatment effect is minimum or not clinically meaningful. If such subpopulations can be identified, some of the
treatments from the negative trials can be proven to at least help a portion of the AD population. In this proposal
we will employ non-parametric interaction tree (IT)-based methods on mixed models for repeated measures
(MMRM) and regression-based methods to identify such subpopulations. IT for MMRM builds on the assessment
of the treatment-by-covariates interactions and can automatically seek subgroups of individuals in whom the
treatment shows heterogeneous effects. We also explore a new and more attractive fusion penalty approach for
final tree determination without any prior knowledge of grouping information. The regression-based methods aim
to identify subpopulations who will benefit from AD treatment based on their characteristics, which is very flexible
to make individualized treatment selection. Finally, we will develop and disseminate a user-friendly statistical
software package that will enable researchers to implement these methods with ease. Our extensions will better
capture individual heterogeneity in disease progression and facilitate evidence-based precision medicine in
future AD studies and other research areas.
是一个主要且迅速增长的公共卫生问题:超过 3000 万人
全世界患有 AD 的人数预计到 2050 年将增加四倍。 据报道 AD 是第三大疾病
美国的死因。随着这场迫在眉睫的全球公共卫生危机,预防发病或减缓发病的治疗方法
AD 进展的研究是迫切需要的,但在 aducenumab 最近加速批准之前很少可用。
因此,当整体情况
治疗效果极小或没有临床意义。如果能够识别出这样的亚群,那么其中一些
阴性试验的治疗方法已被证明至少可以帮助一部分 AD 人群。在这个提案中
我们将在混合模型上采用基于非参数交互树(IT)的方法来进行重复测量
(MMRM)和基于回归的方法来识别此类亚群。 MMRM 的 IT 建立在评估的基础上
协变量相互作用的治疗,并且可以自动寻找个体的亚组,其中
治疗显示出异质性效果。我们还探索了一种新的、更具吸引力的融合惩罚方法
最终的树确定无需任何分组信息的先验知识。基于回归的方法的目标
根据亚群的特征来确定哪些亚群将从 AD 治疗中受益,这是非常灵活的
从而做出个体化的治疗选择。最后,我们将开发并传播一个用户友好的统计数据
软件包将使研究人员能够轻松实施这些方法。我们的扩展会更好
捕捉疾病进展中的个体异质性并促进基于证据的精准医学
未来的AD研究和其他研究领域。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Lei Liu其他文献
Development of indirect competitive immunoassay for highly sensitive determination of ractopamine in pork liver samples based on surface plasmon resonance sensor
基于表面等离子共振传感器的间接竞争免疫分析法高灵敏测定猪肝样品中的莱克多巴胺
- DOI:
10.1016/j.snb.2011.09.078 - 发表时间:
2012-01 - 期刊:
- 影响因子:0
- 作者:
Ming Liu;Baoan Ning;Lijie Qu;Yuan Peng;Jianwei Dong;Na Gao;Lei Liu;Zhixian Gao - 通讯作者:
Zhixian Gao
Lei Liu的其他文献
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{{ truncateString('Lei Liu', 18)}}的其他基金
Innovative Analytical Methods for DNA Methylation Age
DNA 甲基化时代的创新分析方法
- 批准号:
10226664 - 财政年份:2021
- 资助金额:
$ 23.33万 - 项目类别:
Innovative Analytical Methods for DNA Methylation Age
DNA 甲基化时代的创新分析方法
- 批准号:
10414080 - 财政年份:2021
- 资助金额:
$ 23.33万 - 项目类别:
A previously unrecognized β/γ-secretases complex as a therapeutic target for AD
以前未被认识的 β/γ 分泌复合物作为 AD 的治疗靶点
- 批准号:
9902298 - 财政年份:2019
- 资助金额:
$ 23.33万 - 项目类别:
Innovative methods for modeling longitudianl medical costs
纵向医疗成本建模的创新方法
- 批准号:
8337204 - 财政年份:2011
- 资助金额:
$ 23.33万 - 项目类别:
Innovative methods for modeling longitudianl medical costs
纵向医疗成本建模的创新方法
- 批准号:
8723753 - 财政年份:2011
- 资助金额:
$ 23.33万 - 项目类别:
Innovative methods for modeling longitudianl medical costs
纵向医疗成本建模的创新方法
- 批准号:
8529465 - 财政年份:2011
- 资助金额:
$ 23.33万 - 项目类别:
Innovative methods for modeling longitudianl medical costs
纵向医疗成本建模的创新方法
- 批准号:
8088732 - 财政年份:2011
- 资助金额:
$ 23.33万 - 项目类别:
Statistical Analysis of Longitudinal Medical Cost Data
纵向医疗费用数据统计分析
- 批准号:
7323323 - 财政年份:2007
- 资助金额:
$ 23.33万 - 项目类别:
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