Improving Patient Classification and Outcome Measurement in Traumatic Brain Injury (TBI)
改善创伤性脑损伤 (TBI) 的患者分类和结果测量
基本信息
- 批准号:10397525
- 负责人:
- 金额:$ 59.21万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-05-15 至 2024-03-31
- 项目状态:已结题
- 来源:
- 关键词:AcuteAddressAlzheimer&aposs DiseaseAreaBiological MarkersBloodClassificationClinicalClinical ResearchClinical TrialsCommon Data ElementDataData AnalysesData SetDevelopmentDiagnosisDiagnosticDimensionsDiseaseEquationFailureFutureGlasgow Outcome ScaleHeterogeneityInjuryKnowledgeLabelLeadMeasurementMeasuresMethodologyMethodsModelingModernizationMorbidity - disease rateNeurobiologyOutcomeOutcome MeasurePatient-Focused OutcomesPatientsPatternPharmaceutical PreparationsPhenotypePrognosisPsychometricsResearchSamplingSeveritiesStructural ModelsSubgroupSymptomsTBI PatientsTBI treatmentTestingTranslational ResearchTraumatic Brain InjuryWorkanalytical toolclinical outcome measuresclinical phenotypedisabilityeffective therapyexperiencefallsfunctional statusimprovedinnovationmild traumatic brain injurymortalitynovelnovel strategiespatient stratificationpatient subsetspersistent symptomprecision medicineprospectiveresponsesecondary analysissuccesstheoriestooltranslational studytreatment research
项目摘要
Abstract
Traumatic brain injury (TBI) is a common injury that causes chronic symptoms and disabilities
for many patients. Unfortunately, effective treatment options to reduce TBI-related mortality and
reduce morbidity are glaringly absent. The failure of prior clinical trials of TBI is thought to be a
consequence of inadequate understanding of patient heterogeneity, lack of objective biomarkers
of TBI, and blunt approaches to outcome measurement. The proposed R01 study will use
modern quantitative modeling approaches to (a) advance understanding of patterns of patient
heterogeneity and (b) improve the efficiency of clinical outcome measurement. The study will
perform secondary analyses of data from the Transforming Research and Clinical Knowledge in
TBI (TRACK-TBI) study, which has accrued the largest prospective sample of civilian patients
with TBI to date, and will additionally collect a smaller new sample to address the aims. The
specific aims of the study are to (1) identify the optimal clinical phenotypic model of TBI across
the continuum of severity, validating the model by demonstrating that patients with distinct
patterns of acute clinical presentation differ in their levels of acute TBI blood biomarkers and (2)
use item-response theory (IRT) analyses, an extension of the modeling tools used in Aim 1, to
develop new ways measure the full spectrum of TBI-related disability with more precision than
current approaches. The study will be innovative in leveraging advanced quantitative modeling
tools proven valuable in other settings to address current methodological challenges in TBI.
Although this work will leverage the expertise and data available through TRACK-TBI, it will
bring new expertise and an innovative approach that will go beyond the work being undertaken
in any existing study. Our investigative team is uniquely suited to lead this effort given our
extensive experience applying the proposed analytic approaches to TBI, psychiatric,
Alzheimer’s, and measurement research. The findings could transform how TBI is diagnosed,
how patients are selected for clinical and translational studies, and how outcomes are
measured, to fuel the development of precision medicine treatment studies and increase the
chances of identifying effective treatments for TBI.
摘要
项目成果
期刊论文数量(0)
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Lindsay Nelson其他文献
Lindsay Nelson的其他文献
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{{ truncateString('Lindsay Nelson', 18)}}的其他基金
Improving Patient Classification and Outcome Measurement in Traumatic Brain Injury (TBI)
改善创伤性脑损伤 (TBI) 的患者分类和结果测量
- 批准号:
10646155 - 财政年份:2019
- 资助金额:
$ 59.21万 - 项目类别:
Clinical Phenotyping of Mild Traumatic Brain Injury (mTBI)
轻度创伤性脑损伤 (mTBI) 的临床表型
- 批准号:
9281411 - 财政年份:2017
- 资助金额:
$ 59.21万 - 项目类别:
Psychometric and Neurobiological Mechanisms of Impulse Control Disorders
冲动控制障碍的心理测量和神经生物学机制
- 批准号:
8059356 - 财政年份:2010
- 资助金额:
$ 59.21万 - 项目类别:
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