Novel Tools for Familial Risk Prediction
家族风险预测的新工具
基本信息
- 批准号:8530798
- 负责人:
- 金额:$ 22.5万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-03-01 至 2015-02-28
- 项目状态:已结题
- 来源:
- 关键词:AccountingAddressAlgorithmsAttentionBRCA2 geneBehavioralBiological MarkersBreastCancer InterventionCancer PatientClinicalClinical ManagementColonoscopyColorectal CancerComputer softwareCounselingDana-Farber Cancer InstituteDataData CollectionDecision MakingDevelopmentDisciplineDiseaseDisorder by SiteEarly DiagnosisEarly treatmentEnvironmentFamilyFamily history ofFoundationsFundingFutureGenesGeneticGenetic screening methodGoalsGrantIndividualInformaticsInheritedInstitutesInterventionMalignant NeoplasmsMalignant neoplasm of ovaryMalignant neoplasm of pancreasMedicineMeta-AnalysisMethodsModelingMutationOncogenesPatientsPenetrancePopulationPredispositionPreventionPublishingQuantitative EvaluationsRecording of previous eventsResearchResearch InfrastructureResearch PersonnelResourcesReview LiteratureRiskRisk AssessmentRisk FactorsRisk ManagementSkin CancerStatistical MethodsSyndromeTestingTrainingTranslatingValidationbasecancer preventioncancer riskcancer sitecancer typeclinical applicationhigh riskimprovedinterestmalignant breast neoplasmmedical specialtiesneoplasm registrynovelnovel strategiesopen sourceprogramspublic health relevancescreeningsoftware developmenttool
项目摘要
DESCRIPTION (provided by applicant): Challenges: The vast majority of individuals in the developed world have a family history of at least one type of cancer. Aside from major cancer syndromes where family histories point clearly towards a specific cancer site, family history information is not systematically used for the purpose of managing risk, of wisely using genetic testing, and of improving prevention practices. Strong evidence is emerging that syndromes once thought to be distinct, are overlapping in terms of the cancer site, and that several genetic factors increase the risk of multiple cancers. This opens important opportunities for screening and management of risk across clinical disciplines. A critical obstacle is the lack of software infrastructures and analytical approaches for capturing family history information across a large number of disease sites, for assessing whether the occurrence of multiple cancers in a family is likely to be random or hereditary; and for translating family history across multiple disease sites
data into useful clinical decision tools. Aims: Investigators in this proposal have developed the most detailed, accurate, and widely used tools for the breast-ovarian, colorectal, pancreatic, and skin cancer syndromes and the most widely used clinical tools to implement them, including CancerGene and HRA. All are freely available for research. The overall goal of this proposal is to lay the informatics and statistical foundations for both model implementation and clinical application of more comprehensive approaches. This cannot simply be addressed by juxtaposing software and algorithms that have been successful for single-syndrome models, but it requires novel strategies. Specifically, AIM 1 Is to develop software, including a) a general purpose open source risk calculator that can cover simultaneously an arbitrary number of cancer sites and, at the individual level, cancer-specific biomarkers, preventative interventions, and covariates; and b) tools for the implementation of the calculator in both primary and high risk clinical environments. AIM 2 is to develop statistical methods to estimate the population parameters required by the general purpose calculator. AIM 3 is to develop a proof-of-principle model covering about 10 disease sites, based on a comprehensive literature review of penetrance, interventions, and cancer markers. This will allow testing and troubleshooting of the clinical implementation and permit quantification of the benefits of clinical approaches using information across clinical disciplines. Impact: This research will have a direct impact by generating freely available computational and methodological resources for developing and implementing models that consider multiple syndromes. The hypothesis behind this proposal is that making these tools available can have a significant effect on: what data is collected; what use is made of this data across disease-specific programs; and whether individuals at increased risk receive appropriate attention in both early detection and treatment.
描述(由申请人提供):挑战:发达国家的绝大多数人都有至少一种癌症的家族史。除了家族史明确指向特定癌症部位的主要癌症综合征之外,家族史信息没有系统地用于管理风险,明智地使用基因检测和改进预防措施。强有力的证据表明,曾经被认为是独特的综合征在癌症部位方面是重叠的,并且几种遗传因素增加了多种癌症的风险。这为跨临床学科的风险筛查和管理提供了重要机会。一个关键的障碍是缺乏软件基础设施和分析方法,无法获取大量疾病部位的家族史信息,无法评估一个家族中多种癌症的发生可能是随机的还是遗传性的,也无法将家族史转换为多个疾病部位的情况
将数据转化为有用的临床决策工具。 目的:该提案中的研究人员已经开发出最详细,准确和广泛使用的乳腺癌,结肠直肠癌,胰腺癌和皮肤癌综合征的工具,以及最广泛使用的临床工具来实施它们,包括CancerGene和HRA。所有这些都可供免费研究。该提案的总体目标是为模型实施和更全面方法的临床应用奠定信息学和统计学基础。这不能简单地通过并列已成功用于单一综合征模型的软件和算法来解决,但它需要新的策略。具体而言,AIM 1是开发软件,包括a)通用开源风险计算器,可同时涵盖任意数量的癌症部位,并在个体水平上涵盖癌症特异性生物标志物、预防性干预措施和协变量;以及B)用于在主要和高风险临床环境中实施计算器的工具。目的2是开发统计方法来估计通用计算器所需的总体参数。目的3是开发一个原理验证模型,覆盖约10个疾病部位,基于对癌症转移、干预和癌症标志物的全面文献综述。这将允许对临床实施进行测试和故障排除,并允许使用跨临床学科的信息量化临床方法的益处。 影响:这项研究将产生直接的影响,产生免费的计算和方法资源,用于开发和实施考虑多种综合征的模型。这一提议背后的假设是,提供这些工具可以对以下方面产生重大影响:收集哪些数据;在特定疾病的项目中如何使用这些数据;以及风险增加的个人是否在早期发现和治疗中得到适当的关注。
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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Giovanni Luigi PARMIGIANI其他文献
Giovanni Luigi PARMIGIANI的其他文献
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{{ truncateString('Giovanni Luigi PARMIGIANI', 18)}}的其他基金
Statistical methods for cancer mutational signatures
癌症突变特征的统计方法
- 批准号:
10662461 - 财政年份:2021
- 资助金额:
$ 22.5万 - 项目类别:
Statistical methods for cancer mutational signatures
癌症突变特征的统计方法
- 批准号:
10278549 - 财政年份:2021
- 资助金额:
$ 22.5万 - 项目类别:
Statistical methods for cancer mutational signatures
癌症突变特征的统计方法
- 批准号:
10439883 - 财政年份:2021
- 资助金额:
$ 22.5万 - 项目类别:
Bioinformatics Tools for Genomic Analysis of Tumor and Stromal Pathways in Cancer
用于癌症肿瘤和基质途径基因组分析的生物信息学工具
- 批准号:
8606837 - 财政年份:2013
- 资助金额:
$ 22.5万 - 项目类别:
Bioinformatics Tools for Genomic Analysis of Tumor and Stromal Pathways in Cancer
用于癌症肿瘤和基质途径基因组分析的生物信息学工具
- 批准号:
8458359 - 财政年份:2013
- 资助金额:
$ 22.5万 - 项目类别:
Core 5 - Biostatistics and Bioinformatics Core
核心 5 - 生物统计学和生物信息学核心
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10555739 - 财政年份:2011
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$ 22.5万 - 项目类别:
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7123200 - 财政年份:2006
- 资助金额:
$ 22.5万 - 项目类别:
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