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Precise Bone Density Reference Ranges to Reduce Systematic Disparities in Osteoporosis Healthcare for Hispanic Women

精确的骨密度参考范围可减少西班牙裔女性骨质疏松症医疗保健的系统性差异

基本信息

批准号：
10744719
负责人：
Qing Wu
金额：
$ 18.43万
依托单位：
OHIO STATE UNIVERSITY
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：
2021-12-08 至 2025-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10744719
关键词：
Address African American Aging Assessment tool Bone Density Calibration Caucasians Cessation of life Characteristics Classification Clinical Clinical Data Data Data Set Databases Diagnosis Diagnostic Errors Disparity Electronic Health Record Ethnic Origin Fracture Generations Goals Guidelines Healthcare Healthcare Systems Hispanic Hispanic Populations Individual Differences Knowledge Life Expectancy Methodology Methods Minority Minority Groups Modeling National Health and Nutrition Examination Survey Normal Range Osteoporosis Outcome Patients Performance Postmenopause Prevalence Prevention Public Health Race Reference Values Research Risk Risk Assessment Risk Management Running Sampling Scoring Method Specificity Statistical Models Systematic Bias Testing Validation Variant Woman Women&apos s Health bone clinical care clinical diagnosis cohort design disparity elimination epidemiology study ethnic health disparity ethnic minority fracture risk fragility fracture gradient boosting health care disparity health disparity improve minority health improved innovation large scale data novel osteoporosis with pathological fracture racial disparity racial minority random forest rapid growth screening statistics

项目摘要

Project Summary / Abstract Some Caucasian-based clinical guidelines have become the systematic underpinnings of racial and ethnic dis- parities in healthcare. A prime example is the T-score osteoporosis diagnosis criteria, which the WHO initially proposed only for postmenopausal Caucasian women in epidemiological research. However, the T-score diag- nosis criteria are currently used to help with osteoporosis diagnosis for all patients. The T-score approach defines the reference range (RR) of bone mineral density (BMD). Nonetheless, Caucasians-based RRs cannot account for normal variability in race/ethnicity. As a result, applying these Caucasian-based RRs to racial/ethnic minorities often causes errors in diagnosis and risk assessment. With a growing and increasingly diverse minority popula- tion in the US, Caucasian-based clinical guidelines run the risk of exacerbating racial and ethnic healthcare disparities. The existing RRs of BMD are incredibly controversial because many patients who sustain fragility fractures have a “normal” BMD as defined by the conventional T-score approach. This clinically utilized, Cauca- sian-based approach is flawed and, as such, causes systematic healthcare disparities. There is no empirical approach specifically designed to define the RRs of BMD for racial/ethnic minorities. Subsequent race/ethnicity- adjusted T-score thresholds remain controversial because they are not empirically validated, so consequently, their performance has been unsatisfactory on racial/ethnic minorities. Hispanic women have a similarly high fracture risk as Caucasian women; however, Hispanic women, as the most heterogeneous group, have a higher osteoporosis misclassification rate with the T-score diagnosis criteria. With the rapid growth of an increasingly diverse and aging Hispanic population, osteoporotic fractures in Hispanic women are rapidly becoming a signif- icant public health issue. Hence, this application aims to create precise RRs of BMD for Hispanic women to address this pressing issue. This application's central hypothesis is that new precise RRs will classify osteopo- rosis in Hispanic women more accurately than conventional thresholds. This hypothesis will be tested by pursu- ing three specific aims: 1) developing the best-performing model for normative BMD in Hispanic women; 2) determining the precise thresholds of BMD; and 3) evaluating the new RRs in Hispanic women. By replacing the conventional Caucasian-based threshold, the novel, precise RRs will fundamentally shift the current research and clinical care paradigm in RR from one fixed range for every patient to more precise thresholds that account for many individual differences. This application will leverage large samples of Hispanic women and innovative data-driven approaches in creating race/ethnicity-specific, precise RRs of BMD, thus systematically eliminating the corresponding root cause of healthcare disparities for Hispanic women. Of increased significance, the knowledge gained herein can be utilized to generate many other types of precise RRs for various minority groups. The new generation of RRs will directly contribute to improving minority health and reducing healthcare dispari- ties by eliminating such systematic bias in the healthcare system.

项目摘要/摘要