Statistical Strategies for Establishing Etiologic Heterogeneity of Tumors
建立肿瘤病因异质性的统计策略
基本信息
- 批准号:8368187
- 负责人:
- 金额:$ 37.95万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2012
- 资助国家:美国
- 起止时间:2012-07-12 至 2016-05-31
- 项目状态:已结题
- 来源:
- 关键词:AffectAnatomic SitesAttentionBehaviorBiologic CharacteristicBiologicalCancer EtiologyCase-Control StudiesCharacteristicsClassificationClinicalCohort StudiesComputer softwareDataData SetEpidemiologic StudiesEtiologyExcisionGeneticGoalsHeterogeneityKnowledgeLeadLinkMalignant NeoplasmsMalignant neoplasm of brainMalignant neoplasm of pancreasMalignant neoplasm of prostateMapsMeasuresMedicalMethodsMolecularNatureOdds RatioOrganOutcomePatientsPopulationPrimary NeoplasmResearchResearch DesignResearch PersonnelRiskRisk FactorsSpeedTechniquesbasecancer riskcancer typedesignimprovedtooltumor
项目摘要
DESCRIPTION (provided by applicant): The fundamental premise of this proposal is that cancer types based on anatomic site may contain sub-types that are etiologically distinct. Indeed a lot of evidence for this has emerged in recent years. The goal of the proposal is to develop a strategy for optimally identifying such etiologically distinct tumor sub-types, and to develop the statistical techniques needed to accomplish this. In addition to clarifying cancer etiology, such an approach offers the promise of a more powerful strategy for detecting new risk factors, by focusing studies to discover these new risk factors on the sub-types that possess distinct etiology. Our research plan is motivated by a crucial new result regarding the occurrence of double primary malignancies. We show that the odds ratio linking tumor sub-types of pairs of independently occurring cancers is directly related to the underlying population
risk heterogeneity of the sub-types. Consequently data from studies of double primaries can be used to determine optimal tumor sub-classification from an etiologic perspective. In this proposal we build upon this result to develop multivariate clustering techniques that optimize the etiologic heterogeneity of the resulting clusters (Aim 1). We will develop analogous techniques for creating sub-types that maximize the degree of etiologic heterogeneity on the basis of known risk factors for use in settings where data on multiple primary cancers are unavailable or unobtainable (Aim 2). We will determine the implications of the use of sub-typing as a strategy for detecting new risk factors from the perspective of statistical power (Aim 3). Finally, we will develop freely-available software to allow other investigators easy access to the
methods that we develop (Aim 4). The research will lead ultimately to a conceptual framework for investigating etiologic heterogeneity, and a suite of statistical tools for conducting the dat analyses.
PUBLIC HEALTH RELEVANCE: Our research plan has the potential to change the landscape of how cancer epidemiologic investigations are conducted, by focusing on etiologic heterogeneity as a tool for improving the efficiency and statistical power of cancer epidemiologic investigations. As such, it can lead to greater speed in the discovery of factors affecting cancer risk.
描述(申请人提供):这项建议的基本前提是,基于解剖部位的癌症类型可能包含病因上不同的亚型。事实上,近年来出现了大量关于这一点的证据。该提案的目标是开发一种策略,以最佳地识别这些病因学上不同的肿瘤亚型,并开发实现这一目标所需的统计技术。除了澄清癌症病因学之外,这种方法还提供了一种更强大的策略来检测新的风险因素,通过将研究重点放在具有不同病因学的子类型上来发现这些新的风险因素。我们的研究计划是由一个关于双原发恶性肿瘤发生的关键新结果所推动的。我们表明,独立发生的癌症对的肿瘤亚型之间的优势比与潜在人群直接相关。
子类型的风险异质性。因此,来自双原发灶研究的数据可以用来从病因学的角度确定最佳的肿瘤亚型。在这项建议中,我们以这一结果为基础来开发多变量聚类技术,以优化结果簇的病因学异质性(目标1)。我们将开发类似的技术,在已知风险因素的基础上创建亚型,最大限度地提高病因异质性的程度,用于无法获得或无法获得多原发癌数据的情况下(目标2)。我们将从统计能力的角度确定将分型作为发现新风险因素的一种战略的影响(目标3)。最后,我们将开发免费提供的软件,使其他调查人员能够轻松访问
我们开发的方法(目标4)。这项研究最终将导致一个调查病因学异质性的概念框架,以及一套用于进行DAT分析的统计工具。
公共卫生相关性:我们的研究计划有可能改变癌症流行病学调查的进行方式,将病因学异质性作为提高癌症流行病学调查的效率和统计能力的工具。因此,它可以更快地发现影响癌症风险的因素。
项目成果
期刊论文数量(0)
专著数量(0)
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专利数量(0)
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Colin B Begg其他文献
Adaptation of a Mutual Exclusivity Framework to Identify Driver Mutations within Biological Pathways
采用相互排斥框架来识别生物途径中的驱动突变
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Xinjun Wang;Caroline E Kostrzewa;Allison Reiner;R. Shen;Colin B Begg - 通讯作者:
Colin B Begg
InterMEL: An international biorepository and clinical database to uncover predictors of survival in early-stage melanoma
InterMEL:一个国际生物储存库和临床数据库,用于揭示早期黑色素瘤的生存预测因素
- DOI:
10.1101/2022.05.21.22275329 - 发表时间:
2022 - 期刊:
- 影响因子:7.9
- 作者:
Irene Orlow;Keimya Sadeghi;S. Edmiston;Jessica M. Kenney;Cecilia Lezcano;J. Wilmott;A. E. Cust;R. Scolyer;Graham J. Mann;Tim K. Lee;H. Burke;V. Jakrot;Pin Shang;P. Ferguson;T. Boyce;Jennifer S. Ko;Peter Ngo;P. Funchain;J. R. Rees;Kelli O’Connell;Honglin Hao;E. Parrish;K. Conway;P. Googe;D. Ollila;S. Moschos;Eva Hernando;D. Hanniford;D. Argibay;Christopher I. Amos;Jeffrey E. Lee;Iman Osman;Li;14;Luo;P.;Arshi Aurora;B. G. Rothberg;M. Bosenberg;R. Gerstenblith;C. Thompson;Paul N. Bogner;I. Gorlov;Sheri L. Holmen;E. Brunsgaard;Yvonne M Saenger;R. Shen;V. Seshan;M. Ernstoff;K. J. Busam;Colin B Begg;N. Thomas;Marianne;18;Berwick - 通讯作者:
Berwick
Colin B Begg的其他文献
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{{ truncateString('Colin B Begg', 18)}}的其他基金
Leveraging the Hidden Genome to Recover the Missing Heritability of Cancer
利用隐藏的基因组来恢复癌症缺失的遗传性
- 批准号:
10586348 - 财政年份:2023
- 资助金额:
$ 37.95万 - 项目类别:
Harnessing Rare Variants for Tumor Classification
利用罕见变异进行肿瘤分类
- 批准号:
10206386 - 财政年份:2021
- 资助金额:
$ 37.95万 - 项目类别:
Harnessing Rare Variants for Tumor Classification
利用罕见变异进行肿瘤分类
- 批准号:
10599861 - 财政年份:2021
- 资助金额:
$ 37.95万 - 项目类别:
Harnessing Rare Variants for Tumor Classification
利用罕见变异进行肿瘤分类
- 批准号:
10374906 - 财政年份:2021
- 资助金额:
$ 37.95万 - 项目类别:
Quantitative Sciences Summer Undergraduate Research Experience (QSURE) Fellowship
定量科学暑期本科生研究经验(QSURE)奖学金
- 批准号:
10517498 - 财政年份:2017
- 资助金额:
$ 37.95万 - 项目类别:
Quantitative Sciences Summer Undergraduate Research Experience (QSURE) Fellowship
定量科学暑期本科生研究经验(QSURE)奖学金
- 批准号:
10057361 - 财政年份:2017
- 资助金额:
$ 37.95万 - 项目类别:
Quantitative Sciences Summer Undergraduate Research Experience (QSURE) Fellowship
定量科学暑期本科生研究经验(QSURE)奖学金
- 批准号:
10311503 - 财政年份:2017
- 资助金额:
$ 37.95万 - 项目类别:
Statistical Strategies for Establishing Etiologic Heterogeneity of Tumors
建立肿瘤病因异质性的统计策略
- 批准号:
8509633 - 财政年份:2012
- 资助金额:
$ 37.95万 - 项目类别:
Statistical Strategies for Establishing Etiologic Heterogeneity of Tumors
建立肿瘤病因异质性的统计策略
- 批准号:
8677807 - 财政年份:2012
- 资助金额:
$ 37.95万 - 项目类别:
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