Understanding the Multilevel Drivers of Liver Cancer Disparities

了解肝癌差异的多层次驱动因素

• 批准号: 10453623
• 负责人: Salma Shariff-Marco
• 金额: $ 64.03万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 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/10453623
• 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

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.

项目总结/摘要 从2000年到2014年，肝细胞癌（HCC）的发病率每年增加近4%，而大多数人的发病率每年都在增加。 美国的癌症发病率在下降。HCC不成比例地影响少数种族/族裔群体 他们的确诊率大约是非西班牙裔白人的两倍。为初级预防提供信息 为了减少HCC风险的差异，我们需要确定良好的相对贡献， 已建立的和新兴的（例如，B型肝炎病毒、C型肝炎病毒、酒精、吸烟、肝硬化、NAFLD， 代谢紊乱、糖尿病、HIV感染），和新的（例如，药物、合并症、邻居 这些差异的风险因素。为二级和三级预防战略提供信息， 肝癌负担的差异，我们需要了解有助于肝癌监测的多层次因素 差距。填补这些知识空白需要一项强有力的高质量研究， 种族/少数民族。因此，我们建议利用现有的多学科合作， 一个综合数据集，包括与基于人群的状态癌症相关的电子健康记录（EHR）数据 登记册数据和地理空间背景数据。这个多层次的资源将包括近230万的数据 来自三个医疗保健系统的个人（混合支付者、综合医疗保健、联邦合格医疗保健） 在加州和夏威夷的中心），从而提供医疗保健设置的多样性和丰富的种族/民族 少数民族：59，400人是黑人，189，500人是西班牙裔，441，700人是亚裔美国人/夏威夷原住民/太平洋裔 岛民（AANHPI）。有了这个资源，我们的具体目标是：（1）评估建立的相对重要性 和新兴的研究在多大程度上这些因素独立和共同有助于种族/族裔 HCC风险的差异;（2）发现新的风险因素并评估其对HCC风险的相对重要性;以及（3） 评估坚持HCC监测的种族/民族差异，并检查 这些差异可归因于可改变的个体、临床医生、系统和邻近因素（目标3）。 对于目标1，使用前瞻性数据，我们将评估风险因素的相对重要性及其贡献 用因果推理方法对HCC风险中的种族/民族差异进行分析。对于目标2，我们将采用创新的 使用机器学习方法识别新因素并验证其与HCC风险的关联， 目标1的建模策略。对于目标3，我们将使用多水平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监测的差异。给定 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一起考虑 种族/民族使用交叉的方法。通过应用多层次框架来理解 多个层面的生物学、临床和社会因素导致HCC发病率的差异， 监测，拟议的研究将确定可改变的因素，可以转化为临床和 社区环境，以合作确定战略，以改善HCC中的种族/民族差异。