Methods for Epidemiology Studies

流行病学研究方法

• 批准号: 9154202
• 负责人: Nilanjan Chatterjee
• 金额: $ 321.91万
• 依托单位: DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9154202
• 关键词: Accounting; Architecture; B-Lymphocytes; Big Data; Biometry; Breast; Breast Cancer Detection; Breast Cancer Education; Bronchi; Calibration; Cancer Detection; Case-Control Studies; Categories; Cells; Chi-Square Distribution; Colon; Complex; Data; Data Analyses; Data Sources; Diagnostic tests; Disease; Dose; Epidemiologic Methods; Epidemiologic Studies; Epidemiology; Equation; Evaluation; Genes; Genetic; Genetic Determinism; Genomics; Genotype; Heritability; Heterogeneity; Infection; International; Logistic Regressions; Lung; Lymphoma; Malignant neoplasm of lung; Malignant neoplasm of urinary bladder; Matched Case-Control Study; Measures; Mediating; Methodology; Methods; Mission; Modeling; Molecular; Patients; Performance; Pleura; Predisposition; Prevalence; Procedures; Rectum; Reporting; Risk; Risk Estimate; Risk Factors; Sampling; Series; Smoking; Statistical Study; Stratification; T-Cell Lymphoma; Testing; The Cancer Genome Atlas; Trachea; base; cancer risk; case control; cohort; disorder risk; disorder subtype; epidemiology study; gene environment interaction; genetic association; genetic risk factor; genome wide association study; improved; indexing; member; novel; predictive modeling; response; screening; statistics; trait; tumor

A study assessed the asymptotic bias of estimates of exposure effects conditional on covariates when summary scores of confounders (e.g. the propensity score or disease risk score) , instead of the confounders themselves, are used to analyze observational data. The study evaluated regression models for cohort data, case-control and matched case-control studies that are adjusted for (and matched on) summary scores and derive the asymptotic bias. A study evaluated omnibus goodness of fit test for linear mixed models (LMMs) by computing a quadratic form of the differences between the observed and expected values computed from the model within cells of a partition of the covariate space. It showed that under some mild conditions, the test statistic has an asymptotic chi-square distribution and derived analytic expressions for the power of the test statistic under a local alternative. A new method was developed for determining subtypes of disease that share common risk factors. This methodology was applied in International Lymphoma Epidemiology Consortium to show strong differences in the risk profiles for B-Cell and T-Cell lymphomas. A new method was also developed for estimating the proportion of disease heritability that can be attributed genetic causes of mediating risk factors, and used this methodology to show that approximately 24% of lung cancer and 7% of bladder cancer heritability can be attributed to the genetic determinants of smoking. A study developed a mixture model for estimating risk from screening data, separating risk of disease present at baseline from risk of onset of incident disease. Standard Kaplan-Meier estimates are biased in this situation. Another study developed a new framework for risk stratification called mean risk stratification (MRS), which is the average amount of extra disease that a diagnostic test reveals for a patient. Using MRS, it was shown that a big risk difference does not imply good risk stratification for tests that are rarely positive, that a large Youden's index (or AUC) does not imply good risk stratification if disease is too rare, and that the expected benefit of a diagnostic test is a function of the test solely through MRS. A report showed that measures of association for molecular studies that use material from tumors to detect infection in cases can over- or underestimate the relationship between infections and subsequent cancer risk. A statistical procedure has been proposed to improves the efficiency of the logistic regression model for a case-control study by utilizing auxiliary information on covariate-specific disease prevalence via a series of unbiased estimating equations. A method was developed for constrained maximum likelihood analysis for model calibration using external summary-level information from big-data sources.A number of studies statistical genetic and genomics were conducted A robust statistical procedure has been developed to identify genetic risk factors that have either a uniform effect for all disease subtypes or heterogeneous effects across different subtypes. A test for genetic association was proposed that can account for heterogeneity in genetic effects due to gene-environment interactions under alternative models. A study developed extensions of various methods for testing gene-environment interactions to account for imputed genotype data. A study developed method for estimation of effect-size distribution using summary-level results from GWAS. Application of the method to results from large GWAS of several diseases indicate highly polygenic architecture of complex traits involving thousands to tends of thousands of susceptibility SNPs. Several studies are ongoing to investigate how to improve performance of polygenic risk prediction models incorporating summary-level results from large GWAS and various types of prior information on effect-size-distribution. A likelihood-based test and a valid method for type-I error evaluation were developed for mutual exclusivity analysis in detection of cancer driver gene. The methods were developed and applied for analysis of data from the The Cancer Genome Atlas (TCGA) project leading to identification a number of novel driver genes.

一项研究评估了当混杂因素的摘要得分（例如倾向评分或疾病风险评分）而不是混杂因素本身时，评估了有条件地对协变量的暴露效应估计值的渐近偏差，用于分析观察数据。该研究评估了对队列数据，病例对照和匹配的病例对照研究的回归模型，这些研究经过调整（并匹配）摘要分数并得出渐近偏差。 一项研究通过计算从协变量空间分区的细胞内的模型计算出的二次形式来评估线性混合模型（LMM）的综合测试的综合测试。 它表明，在某些温和条件下，测试统计量具有渐近卡方分布和在局部替代方面的测试统计量的衍生分析表达式。开发了一种新方法来确定具有共同危险因素的疾病亚型。该方法应用于国际淋巴瘤流行病学联盟，以显示B细胞和T细胞淋巴瘤的风险谱图的强烈差异。还开发了一种新方法来估计可以归因于介导危险因素的遗传原因的疾病遗传力的比例，并使用这种方法证明，大约24％的肺癌和7％的膀胱癌遗传力可以归因于吸烟的遗传决定因素。 一项研究开发了一种混合模型，用于估算筛查数据的风险，将基线疾病的风险与入射疾病的风险分开。 在这种情况下，标准的Kaplan-Meier估计是有偏见的。 另一项研究开发了一种称为平均风险分层（MRS）的新风险分层框架，这是诊断测试对患者揭示的额外疾病的平均量。 使用MRS，结果表明，很大的风险差异并不意味着很少有正面的测试的风险分层，即如果疾病太罕见，那么大的Youden指数（或AUC）并不意味着良好的风险分层，并且诊断测试的预期益处是通过MRS进行测试的函数。一份报告显示，使用肿瘤中材料检测感染的分子研究的措施可以过多地或低估感染与随后的癌症风险之间的关系。已经提出了一种统计程序，通过利用一系列无偏见的估计方程利用有关协变量特异性疾病患病率的辅助信息来提高病例对照研究的逻辑回归模型的效率。开发了一种方法，用于使用来自大数据源的外部摘要级信息进行模型校准的最大可能性分析。进行了数量的统计遗传和基因组学研究数量，已经开发了可靠的统计方法，以识别对所有疾病亚型或不同子类型的所有疾病子类型或异构效应均具有统一作用的遗传风险因素。提出了对遗传关联的测试，该测试可以说明由于替代模型下基因环境相互作用而引起的遗传效应的异质性。一项研究开发了用于测试基因环境相互作用的各种方法的扩展，以说明估计的基因型数据。一项研究开发了使用GWAS的摘要级别的结果来估算效应大小分布的方法。该方法在多种疾病的大GWA中的应用表明，涉及数千种易感性SNP的复杂性状的高度多基因结构。 正在进行一些研究，以研究如何提高多基因风险预测模型的性能，这些模型结合了大型GWA的摘要级别的结果以及有关效应 - 大小分布的各种先验信息。开发了基于似然的测试和一种用于I型错误评估的有效方法，用于在检测癌症驱动基因时相互排他性分析。开发了这些方法并应用于分析癌症基因组图集（TCGA）项目的数据，从而导致许多新型驱动基因。