Multifactoral breast cancer risk prediction accounting for ethnic and tumor diversity
考虑种族和肿瘤多样性的多因素乳腺癌风险预测
基本信息
- 批准号:10263893
- 负责人:
- 金额:$ 63.77万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-09-15 至 2024-05-31
- 项目状态:已结题
- 来源:
- 关键词:AccountingAfricaAsiaAssessment toolBiological MarkersBreast Cancer DetectionBreast Cancer ModelBreast Cancer Risk Assessment ToolBreast Cancer Risk FactorCalibrationCancer EtiologyCategoriesCessation of lifeCharacteristicsClinicalClinical TrialsCounselingDataData PoolingData ScienceEstrogen Receptor StatusEstrogen receptor negativeEstrogen receptor positiveEthicsEthnic OriginEthnic groupEuropeFaceFamilyFutureGuidelinesHealth SurveysHormonalIncidenceIndividualIntegrated Health Care SystemsInternetInterventionLatin AmericaLife StyleMalignant NeoplasmsMammographic DensityMammographic screeningMeta-AnalysisMethodologyMethodsModalityModelingNational Cancer InstituteOperative Surgical ProceduresOutputPatientsPharmaceutical PreparationsPhysiciansPopulationPreventive therapyProthrombinRaceRecording of previous eventsRegistriesReproductive HistoryResearchRiskRisk AssessmentRisk FactorsRunningSamplingStatistical ModelsSystemTranslationsUniversitiesUpdateValidationWomanbasecancer subtypesclinical applicationclinical practicecohortflexibilitygenetic testinggenome wide association studyhealth care deliveryhealth care settingshormone receptor-positivehormone therapylifestyle interventionmalignant breast neoplasmmammography registrymodel buildingmulti-ethnicneoplasm registrynovelovertreatmentpolygenic risk scorepopulation basedpredictive modelingpreventprophylacticprospectiverisk predictionrisk prediction modelrisk stratificationscreeningscreening programtooltumortumor heterogeneity
项目摘要
Abstract
Breast cancer risk assessment tools are widely used in clinical practice to guide decisions regarding screening
timing and modality, life-style interventions, genetic testing, preventive therapy, and risk-reducing surgery.
Although a number of tools are used in practice, they face various challenges including: (i) modest
discriminatory ability due to lack of a unified model that incorporates a comprehensive set of risk-factors; (ii)
inability to produce sub-type specific risk, especially considering aggressive subtypes of breast cancer and/or
prophylactic endocrine therapy that is effective only for hormone receptor positive tumors; (iii) lack of data to
build models for different ethnic populations; and, (iv) scant validation of models, especially in healthcare
settings where models can be widely disseminated in practice. In this proposal, we will assimilate and analyze
data on a large and diverse sample of women from studies participating in the NCI Cohort Consortium to
develop a comprehensive tool that will predict breast cancer risk, overall and by sub-types, across major ethnic
groups in the US. We further propose to prospectively validate the model in different clinical settings, including
a risk-stratified screening trial. In Aim 1 we will develop a comprehensive model for predicting absolute risk of
overall breast cancer for women from multiple ethnicities, incorporating information on family history; polygenic
risk-scores (PRS); anthropometric, life-style and reproductive factors; hormonal biomarkers; and
mammographic density. In Aim 2 we will tailor these risk models to specific breast cancer subtypes, notably
estrogen receptor negative and positive cancers. In Aim 3 we will evaluate the validity of these risk prediction
models in integrated health care systems, mammography registries, and an ongoing risk-based
mammographic screening trial in the US. The resulting models could be used in diverse clinical settings to
guide preventive therapy or risk-stratified screening programs, increasing the number of breast cancer deaths
prevented while minimizing overdiagnosis and overtreatment.
摘要
乳腺癌风险评估工具在临床实践中被广泛用于指导有关筛查的决策
时机和方式、生活方式干预、基因检测、预防性治疗和降低风险的手术。
虽然在实践中使用了一些工具,但它们面临着各种挑战,包括:
由于缺乏一个包含一整套风险因素的统一模式,歧视能力不足; ㈡
不能产生亚型特异性风险,特别是考虑到乳腺癌的侵袭性亚型和/或
仅对激素受体阳性肿瘤有效的预防性内分泌治疗;(iii)缺乏数据,
为不同的种族群体建立模型;以及(iv)模型的验证不足,特别是在医疗保健方面
在实践中可以广泛传播模型的环境。在这个建议中,我们将吸收和分析
来自参加NCI队列联盟研究的大量不同女性样本的数据,
开发一种全面的工具,预测乳腺癌的风险,总体和亚型,在主要种族
在美国的团体。我们进一步建议在不同的临床环境中前瞻性地验证该模型,包括
风险分层筛选试验在目标1中,我们将开发一个综合模型,用于预测
多种族女性的总体乳腺癌,纳入家族史信息;多基因
风险评分(PRS);人体测量、生活方式和生殖因素;激素生物标志物;以及
乳房摄影密度在目标2中,我们将针对特定的乳腺癌亚型定制这些风险模型,特别是
雌激素受体阴性和阳性癌症。在目标3中,我们将评估这些风险预测的有效性
综合卫生保健系统中的模型、乳房X光检查登记处和正在进行的基于风险的
在美国进行的乳房X光筛查试验。由此产生的模型可用于不同的临床环境,
指导预防性治疗或风险分层筛查计划,增加乳腺癌死亡人数
避免过度诊断和过度治疗。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Nilanjan Chatterjee其他文献
Nilanjan Chatterjee的其他文献
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{{ truncateString('Nilanjan Chatterjee', 18)}}的其他基金
Statistical Methods for Data Integration and Applications to Genome-wide Association Studies
数据集成的统计方法及其在全基因组关联研究中的应用
- 批准号:
10889298 - 财政年份:2023
- 资助金额:
$ 63.77万 - 项目类别:
Multifactoral breast cancer risk prediction accounting for ethnic and tumor diversity
考虑种族和肿瘤多样性的多因素乳腺癌风险预测
- 批准号:
10609504 - 财政年份:2020
- 资助金额:
$ 63.77万 - 项目类别:
Multifactoral breast cancer risk prediction accounting for ethnic and tumor diversity
考虑种族和肿瘤多样性的多因素乳腺癌风险预测
- 批准号:
10416066 - 财政年份:2020
- 资助金额:
$ 63.77万 - 项目类别:
Robust Methods for Polygenic Analysis to Inform Disease Etiology and Enhance Risk Prediction
多基因分析的稳健方法可告知疾病病因并增强风险预测
- 批准号:
9920753 - 财政年份:2019
- 资助金额:
$ 63.77万 - 项目类别:
Robust Methods for Polygenic Analysis to Inform Disease Etiology and Enhance Risk Prediction
多基因分析的稳健方法可告知疾病病因并增强风险预测
- 批准号:
10359748 - 财政年份:2019
- 资助金额:
$ 63.77万 - 项目类别:
Robust Methods for Polygenic Analysis to Inform Disease Etiology and Enhance Risk Prediction
多基因分析的稳健方法可告知疾病病因并增强风险预测
- 批准号:
10112944 - 财政年份:2019
- 资助金额:
$ 63.77万 - 项目类别:
Robust Methods for Polygenic Analysis to Inform Disease Etiology and Enhance Risk Prediction
多基因分析的稳健方法可告知疾病病因并增强风险预测
- 批准号:
10579942 - 财政年份:2019
- 资助金额:
$ 63.77万 - 项目类别:
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