Health Disparities of Patients with Fragile X from Diverse Racial & Ethnic Groups
Health Disparities of Patients with Fragile X from Diverse Racial & Ethnic Groups
批准号:
10645599
负责人:
AREZOO MOVAGHAR
金额:
$7.78万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-04-06 至 2023-11-13
关键词:
AccelerationAgeAreaArtificial IntelligenceBiometryBirthCaringCharacteristicsChicagoClinicClinicalClinical DataClinical ResearchCodeComplexDataDevelopmentDiagnosisDiagnosticDiseaseElectronic Health RecordEpidemiologyEthnic OriginEthnic PopulationFaceFamilyFemaleFragile X SyndromeFrequenciesGeneral PopulationGeneticGoalsGuidelinesHealthHealth systemHealthcare SystemsHeterogeneityHispanicIndividualInheritedInstitutionIntellectual functioning disabilityInvestigationKnowledgeLettersLinkMachine LearningMedicalMedical HistoryMeta-AnalysisModelingNot Hispanic or LatinoOutcomes ResearchPatient advocacyPatient-Focused OutcomesPatientsPatternPediatricsPenetrancePersonal SatisfactionPhenotypePhysiciansPopulationPopulation StudyPrevalenceROC CurveRaceRecommendationResearchSamplingScientistScreening procedureSiteSocial SciencesSourceStressSubgroupSymptomsTechniquesTestingTimeTranslational ResearchUniversitiesVariantWisconsinautism spectrum disorderbiomedical informaticsburden of illnesscase-basedclinical diagnosisclinical practiceclinical riskdevelopmental psychologyethnic diversityexperiencegenetic disorder diagnosisgenetic testinghealth care service utilizationhealth disparityimprovedinnovationinsightmalemedical specialtiesmetropolitanmultidisciplinarynovelnovel strategiespatient populationpatient subsetspredictive modelingpublic health prioritiesracial diversityracial populationscreeningsexsuccesstool
中文摘要
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英文摘要
Project Summary
Fragile X syndrome (FXS) is the most prevalent monogenic cause of intellectual disability and autism.
Clinical studies on patients being seen in specialized clinics have shown that this X-linked disorder has a
substantial impact on the health and well-being of patients and families. FXS remains significantly
underdiagnosed despite increased emphasis on identification of individuals with FXS, patient advocacy, and
accessibility of genetic testing. The impact of this condition across racial and ethnic groups is unknown and the
rate and prevalence of co-occurring conditions has not yet been characterized using representative populations.
An unmet need exists to develop novel pre-screening approaches that are able to alert physicians to potentially
undiagnosed cases and refer them for genetic testing. This application proposes research that will not only
advance knowledge of clinical risk associated with FXS but will also offer insight into development of innovative
pre-screening approaches that can improve diagnostic practices for other complex underdiagnosed conditions.
The present research will be the largest population-level study of health characteristics of individuals with
FXS from diverse racial and ethnic patient groups. The electronic health records (EHRs) from more than 15
million patients in CAPriCORN (the Chicago Area Patient-Centered Outcomes Research Network) will be used
for this study. CAPriCORN includes 11 different health care systems/sites (with one FXS Specialized Clinic) in
metropolitan Chicago. 1008 patients have been identified who have a diagnostic code for FXS in their
EHRs (318 females, 690 males) of whom 293 are Non-White, 110 are Hispanic, and the others are non-
Hispanic Whites. By including patients from diverse racial and ethnic groups, and by utilizing discovery-oriented
approaches and artificial intelligence (AI) techniques, our proposed research will evaluate phenotypic
characteristics of individuals with FXS more representative of the US population.
Our Specific Aims are: (1) To detect the rate of FXS diagnosis (and under-diagnosis) in patients from diverse
racial and ethnic groups; (2) To characterize the diagnostic patterns in FXS patients from diverse racial and
ethnic groups; and (3) To construct an AI-assisted pre-screening tool to find potential cases with FXS who have
not yet been diagnosed and validate the tool with racially and ethnically diverse patient groups. Additionally, we
will investigate the impact of access to specialty clinics by characterizing the differences/similarities in age of
diagnosis, diagnostic odyssey, and health care utilization between patients served by the Fragile X Clinic at Rush
University and patients from other CAPriCORN sites. We have organized a multidisciplinary team of scientists
with expertise in biostatistics, biomedical informatics, genetics, pediatrics, developmental psychology,
epidemiology, and social science. With substantial experience in using EHR data for clinical and translational
research, and with a long successful track record of conducting collaborative multi-institutional studies on FXS,
our team has exceptional ability to achieve these research goals.
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