Understanding the Multilevel Drivers of Liver Cancer Disparities

了解肝癌差异的多层次驱动因素

基本信息

批准号：
10524105
负责人：
Salma Shariff-Marco
金额：
$ 13.29万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-08-16 至 2024-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10524105
关键词：
Address Adherence Alcohols Asian Americans Behavioral Sciences Biological Biological Factors Biology Biometry Birth Black Populations Black race California Caring Characteristics Cirrhosis Clinical Data Data Set Diabetes Mellitus Diagnosis Education Electronic Health Record Environmental Risk Factor Epidemiologic Monitoring Ethnic Origin Ethnic group Federally Qualified Health Center Female Fibrinogen Future Geographic Factor Geography HIV Infections Hawaii Health Insurance Health Maintenance Organizations Health Services Research Healthcare Healthcare Systems Hepatitis B Infection Hepatitis B Virus Hepatitis C Hepatitis C virus Heterogeneity Hispanic Hispanic Populations Incidence Individual Infection Institution Insurance Coverage Interdisciplinary Study Intervention Investigation Knowledge Language Linear Regressions Link Liver neoplasms Malignant Neoplasms Malignant neoplasm of liver Metabolic Diseases Methods Modeling Native Hawaiian Neighborhoods Not Hispanic or Latino Pacific Islander Patients Pharmaceutical Preparations Prevention strategy Preventive measure Primary Prevention Primary carcinoma of the liver cells Race Research Resources Risk Risk Factors Sampling Sampling Studies Secondary Prevention Services Shapes Smoking Social Sciences System Tobacco smoking behavior Translating Translations United States built environment cancer epidemiology cancer health disparity chronic alcohol ingestion cohort community setting comorbidity data registry disparity reduction electronic data ethnic minority evidence base experience follow-up health care settings high risk innovation machine learning method male mortality neoplasm registry non-alcoholic fatty liver disease nonalcoholic steatohepatitis novel population based prospective racial and ethnic racial and ethnic disparities racial minority sex social social determinants social disparities social factors socioeconomics tertiary prevention

项目摘要

Project Summary/Abstract From 2000-2014, hepatocellular carcinoma, or HCC, incidence rates increased nearly 4% per year, while most cancers in the United States were on the decline. HCC disproportionately impacts minority racial/ethnic groups who are diagnosed at rates approximately twice that of non-Hispanic Whites. To inform primary prevention strategies that will reduce disparities in HCC risk, we need to determine the relative contribution of well- established and emerging (e.g., hepatitis B virus, hepatitis C virus, alcohol, smoking, cirrhosis, NAFLD, metabolic disorders, diabetes, HIV infection), and novel (e.g., medications, comorbidities, neighborhood attributes) risk factors to these disparities. To inform secondary and tertiary prevention strategies to reduce disparities in HCC burden, we need to understand the multilevel factors that contribute to HCC surveillance disparities. Answering these gaps in knowledge requires a robust high-quality study with a sample enriched for racial/ethnic minorities. Thus, we propose to leverage existing multi-disciplinary collaborations to develop an integrated dataset that includes electronic health records (EHR) data linked to population-based state cancer registry data and geospatial contextual data. This multilevel resource will include data on nearly 2.3 million individuals from three healthcare systems (mixed payer, integrated healthcare, federally qualified health centers) in California and Hawaii, thus providing diversity in healthcare settings and enrichment for racial/ethnic minorities: 59,400 are Black, 189,500 are Hispanic, and 441,700 are Asian American/Native Hawaiian/Pacific Islander (AANHPI). With this resource, we specifically aim to: (1) assess the relative importance of established and emerging examine the extent to which these factors independently and jointly contribute to racial/ethnic disparities in HCC risk; (2) discover novel risk factors and assess their relative importance to HCC risk; and (3) assess racial/ethnic disparities in adherence with surveillance for HCC as well as examine the extent to which these disparities are attributable to modifiable individual-, clinician-, system-, and neighborhood factors (Aim 3). For Aim 1, using prospective data, we will assess the relative importance of risk factors and their contribution to racial/ethnic disparities in HCC risk with causal inference methods. For Aim 2, we will apply innovative machine learning methods to identify novel factors and validate their associations with HCC risk using modeling strategy from Aim 1. For Aim 3, we will use multilevel generalized linear regression to investigate the patient, clinician, institutional and geographic factors that contribute to disparities in HCC surveillance. Given the importance of sex and age/birth cohort for HCC risk, these social determinants will be considered together with race/ethnicity using an intersectional approach. By applying a multilevel framework to understand how biological, clinical, and social factors at multiple levels contribute to HCC disparities in incidence and surveillance, the proposed study will identify modifiable factors that can be translated to the clinical and community settings to collaboratively identify strategies to ameliorate racial/ethnic disparities in HCC.

项目摘要/摘要从2000 - 2014年开始，肝细胞癌或HCC，发病率每年增加近4％，而大多数美国的癌症正在下降。 HCC不成比例地影响少数种族/族裔群体以大约是非西班牙裔白人的两倍的诊断率。通知初级预防将降低HCC风险差异的策略，我们需要确定良好的相对贡献建立和新兴（例如，丙型肝炎病毒，乙型肝炎病毒，酒精，吸烟，肝硬化，NAFLD，NAFLD，代谢疾病，糖尿病，艾滋病毒感染）和新颖（例如药物，合并症，邻里属性）这些差异的风险因素。告知二级和三级预防策略以减少 HCC负担的差异，我们需要了解有助于HCC监视的多层次因素差异。在知识中回答这些差距需要一项强大的高质量研究，并具有丰富的样本种族/族裔少数民族。因此，我们建议利用现有的多学科合作来开发包含电子健康记录（EHR）数据的集成数据集与基于人群的州癌有关注册表数据和地理空间上下文数据。此多级资源将包括有关近230万的数据来自三个医疗保健系统的个人（混合付款人，综合医疗保健，联邦合格的健康中心）在加利福尼亚和夏威夷，从而在医疗保健环境中提供多样性，并为种族/族裔提供丰富少数族裔：59,400人是黑色的，189,500是西班牙裔，441,700是亚裔美国人/本地夏威夷/太平洋岛民（Aanhpi）。有了此资源，我们专门针对以下目的：（1）评估已建立的相对重要性并新兴研究这些因素在多大程度上独立并共同促进了种族/种族 HCC风险的差异；（2）发现新颖的风险因素并评估其对HCC风险的相对重要性；（3）评估遵守HCC监视的种族/种族差异，并检查这些差异归因于可修改的个体，临床医生，系统和邻里因素（AIM 3）。对于AIM 1，使用前瞻性数据，我们将评估风险因素及其贡献的相对重要性通过因果推理方法，hcc风险中的种族/族裔差异。对于AIM 2，我们将应用创新使用机器学习方法来确定新因素并使用HCC风险验证其关联从AIM 1进行建模策略。对于AIM 3，我们将使用多级广义线性回归来研究患者，临床医生，机构和地理因素导致HCC监视的差异。给出性别和年龄/出生队列对HCC风险的重要性，这些社会决定因素将被考虑使用交叉方法的种族/种族。通过应用多级框架来了解如何生物学，临床和社会因素在多个层面上有助于发病率的HCC差异监视，拟议的研究将确定可修改的因素，这些因素可以转化为临床和社区环境以协作确定改善HCC种族/种族差异的策略。