Quantifying cardiovascular calcification at very old age for personalized risk classification
Quantifying cardiovascular calcification at very old age for personalized risk classification
批准号:
10153851
负责人:
MICHAEL J BLAHA
金额:
$73.86万
依托单位:
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:
2017-05-01 至 2024-03-31
关键词:
AdultAgeAge-YearsAgingAncillary StudyAspirinAtherosclerosisAtherosclerosis Risk in CommunitiesBiologicalBlood VesselsCardiacCardiovascular DiseasesCardiovascular systemClassificationClinicalCommunitiesCoronary heart diseaseDataDecision MakingDementiaDiscriminationDrug InteractionsElderlyElectronic Health RecordEquilibriumHeart failureIndividualInferiorKnowledgeLifeLife StyleLung diseasesMalignant NeoplasmsMeasuresModelingMorbidity - disease rateNatriuretic PeptidesOlder PopulationParticipantPatient PreferencesPatient-Focused OutcomesPharmaceutical PreparationsPharmacotherapyPhenotypePlant RootsPopulationPredispositionPrevalencePreventivePreventive therapyPreventive treatmentPrimary PreventionPrognosisRecording of previous eventsRiskRisk FactorsScanningStrokeSurveysThoracic aortaTimeTroponinUnited States National Institutes of HealthVariantVisitWeightX-Ray Computed Tomographyagedbasecalcificationcardiovascular disorder preventioncardiovascular risk factorclinical riskcohortcomorbiditycoronary artery calciumcoronary calcium scoringdensitydesignevidence basehigh riskhuman very old age (85+)improvedmiddle agemortality riskpredictive modelingpreferenceprognosticrisk predictionrisk prediction modelrisk stratificationshared decision makingtool
中文摘要
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英文摘要
ABSTRACT: Quantifying cardiovascular calcification at very old age for personalized risk classification
Predicted risk is central to decision-making in primary prevention of atherosclerotic cardiovascular disease
(ASCVD). However, classifying risk in older adults ≥75 years remains extremely challenging. By placing heavy
weight on age, existing risk prediction models universally assign high risk status and therefore recommend
treatment for nearly all older adults, raising concerns about overmedication, drug-drug interactions, and lack of
personalization. Competing risk of mortality and morbidity due to other conditions (e.g., cancer, lung disease,
and dementia) is another issue in this population, requiring a fine balance between prevention of CVD based
on accurate risk prediction vs. management of other comorbidities. Unfortunately, such accurate risk prediction
is not achievable with one-time assessment of traditional cardiovascular risk factors at older ages because this
approach does not capture cumulative lifetime exposures and individuals' susceptibility.
In this context, coronary artery calcium (CAC) is promising, as it directly quantifies a composite of cumulative
exposure and an individual's susceptibility to risk factors. Indeed, a high CAC score is one of the most potent
predictors of ASCVD. Recently, zero and low CAC has been shown to be useful for “de-risking”, identifying
individuals who are at low absolute risk in whom preventive therapy may not result in net benefit. Recent
studies also demonstrate that extra-coronary calcium (ECC) (i.e., aortic root/valve, mitral annulus, and thoracic
aorta) detected on a routine CAC scan provides risk information beyond CAC. However, prevalence and
prognostic data for CAC and ECC among very old adults are surprisingly sparse. Thus, we propose to perform
non-contrasted cardiac-gated computed tomography among ~3,100 participants in the Atherosclerosis Risk in
Communities (ARIC) Study during forthcoming visits between 2017-19 and to develop a dedicated CVD risk
classification tool incorporating CAC and ECC for older adults ≥75 years. To maximize the usefulness of our
CVD risk classification tool, we will develop benefit-harm charts incorporating our prediction models and patient
preferences for two representative scenarios, preventive statin and aspirin pharmacotherapy.
Aim 1: To develop risk classification models for CVD risk in the 75-and-older population.
Aim 2: To evaluate the interplay between 30-year cumulative exposures and CAC/ECC for assessment of
healthy vascular aging (e.g., low or zero CAC) and estimation of CVD prognosis.
Aim 3: To evaluate the effect of preventive treatment preferences and CAC/ECC-based risk information on the
balance of benefits and harms of preventive pharmacotherapy in adults ≥75 years of age.
This project will deliver accurate risk classification tools for CVD based on established risk factors and
CAC/ECC for the 75-and-older population. The comparison of 30-year cumulative risk factor exposures vs.
CAC/ECC will be of value clinically and biologically. Our benefit-harm charts will directly inform evidence-based
shared decision-making in the context of primary prevention of CVD among older adults aged 75 and older.
期刊论文(3)
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