Developing Model-based Bone Density Reference Values for African-American Women
Developing Model-based Bone Density Reference Values for African-American Women
批准号:
9305795
负责人:
Qing Wu
金额:
$44.83万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-01 至 2021-08-31
关键词:
African AmericanAgeAssessment toolBig DataBlood PressureBone DensityCaucasiansCessation of lifeCharacteristicsCholesterolClinicalComputerized Medical RecordCustomDataDatabasesDevelopmentDiagnosisDiseaseEnvironmentEthnic OriginFemaleFractureGoalsIndividualLife ExpectancyMeasurementMedicalMedical ResearchMethodologyMethodsMinorityMinority GroupsModelingNational Health and Nutrition Examination SurveyNormal RangeOsteoporosisOutcomePatientsPerformancePhysiologicalPilot ProjectsPlant RootsPopulation ResearchPostmenopausePreventionProceduresPublic HealthPublicationsPublishingRaceReference ValuesResearchResearch DesignSample SizeSamplingScoring MethodSpecificityStatistical ModelsStudentsSupervisionTestingValidationVariantWomanWorkWorld Health Organizationbaseboneclinical practicecohortdesignethnic minority populationexperiencefracture riskfragility fracturehands on researchhealth care disparityhealth disparityimprovedinnovationinterestnovelnovel strategiesosteoporosis with pathological fractureprecision medicineracial and ethnicracial disparitystandard carestatisticsstudy population
中文摘要
点击翻译按钮获取中文摘要
英文摘要
Project Summary / Abstract
Clinical reference values are typically derived from Caucasians, with limited sample sizes and simplistic
statistics. As a result, applying these reference values to racial/ethnic minorities often causes misdiagnosis.
Our long-term goal is to develop innovative methodologies to produce and validate precision reference values.
The reference values of bone mineral density (BMD) are proving increasingly inaccurate since a substantial
number of patients who sustain fragility fractures have what the standard T-score method defines as a normal
BMD value. The T-score method was originally proposed only for postmenopausal Caucasian women, and as
a result there is no empirical method designed specifically to define BMD reference values for racial/ethnic
minorities. Therefore, with life expectancy increasing, osteoporotic fractures in minorities including African-
American women are becoming a major public health issue. The objective of this application is to develop a
novel method to determine precision BMD reference values for African-American women, a group whose
osteoporotic fractures have previously been under-recognized and undertreated. On the basis of preliminary
data produced by the applicant, the central hypothesis is that for African-American women a new method
based on “the best statistical model” of normal BMD will be a significantly better predictor of osteoporotic
fracture than the T-Score method. This hypothesis will be tested by pursuing three specific aims: 1) identifying
the best statistical model of normal BMD; 2) determining the model-based precision threshold of BMD; and 3)
validating the precision reference values for African-American women. For Aim 1, this project will leverage
multiple existing NHANES databases to develop a highly accurate statistical model of normal BMD for African-
American women. For Aim 2, a precision threshold that matches an individual's characteristics will be
determined by utilizing the best BMD model and cohort data containing fracture outcome. Under Aim 3, Study
of Osteoporosis Fracture data will be utilized to validate the model-based method by comparing its predictive
accuracy for osteoporotic fracture with traditional methods. This innovative approach will replace the traditional
“one-size-fits-all” clinical reference value, fundamentally shifting current research and clinical practice
paradigms from one static cutoff point for everyone to precision thresholds fitting individual characteristics. The
new approach will overcome the limitations of the T-score method, thus increasing the prediction accuracy of
the WHO's Fracture Risk Assessment Tool, and the accuracy of osteoporosis diagnoses in general. The
approach developed herein can be extended to the development of many other types of precision reference
values. In addition, this project will engage students in the research of precision medicine through the use of
“big data,” thus providing them with hands-on research experience and stimulating their research interest in
health disparities.
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